1 . NHIỆM VỤ 2.1

1.1 . Tóm Tắt

Nhiệm vụ 2.1 thao tác trên datasets “bwt_co_dieu_chinh.xlsx” là datasets thống kê những thuộc tính trong quá trình mang thai của phụ nữ giai đoạn 1925-2004.

1.2 . Mô tả cơ bản

Các thông số từ datasets có 640 quan sát và 9 biến như sau:

id: Khu vực (có 8 khu vực).
year: Năm lấy số liệu.
bwt: Trọng lượng lúc sinh tính bằng ounces, 1 ounces=28.3495 gram).
gestation: Thời gian mang thai(tính bằng ngày).
parity: Số lần sinh (có hai giá trị, 1=sinh lần đầu, 0=không phải lần đầu).
age: Tuổi của mẹ.
height: Chiều cao của mẹ (tính bằng inches, 1 inch=2.54cm).
weight: Cân nặng của bà mẹ khi mang thai (tính bằng pounds, 1 pound=0.453592kg).
smoke: Hút thuốc lúc mang thai (1=có, 0=không).

Không có dữ liệu trống

1.3 . Đọc dữ liệu từ file Excel

library(openxlsx)
vy1 <- read.xlsx("/Users/xuyenchi/Library/Containers/com.microsoft.Excel/Data/Downloads/R Code/bwt_co_dieu_chinh.xlsx") #đọc dữ liệu từ excel và gán vào object vy1
table <- knitr::kable(vy1,format="markdown")
table

id	year	bwt	gestation	parity	age	height	weight	smoke
1	1925	120	284	0	27	62	100	0
2	1925	112	267	1	22	62	138	0
3	1925	119	286	0	26	64	123	1
4	1925	124	287	0	27	62	105	1
5	1925	105	276	0	22	67	130	0
6	1925	120	289	1	31	59	102	0
7	1925	82	274	0	31	64	101	1
8	1925	111	278	0	29	65	145	1
1	1926	113	282	0	33	64	135	0
2	1926	134	297	0	27	67	170	1
3	1926	97	279	0	29	68	178	1
4	1926	125	292	0	22	65	122	0
5	1926	93	246	0	37	65	130	0
6	1926	146	280	0	23	61	145	0
7	1926	100	274	0	24	63	113	0
8	1926	103	250	0	40	59	140	0
1	1927	128	279	0	28	64	115	1
2	1927	145	308	0	35	64	110	1
3	1927	99	252	0	21	64	120	0
4	1927	110	262	0	25	66	140	0
5	1927	122	281	0	42	63	103	1
6	1927	112	283	1	21	62	102	1
7	1927	114	271	0	32	61	130	0
8	1927	114	276	0	26	62	127	0
1	1928	108	282	0	23	67	125	1
2	1928	116	295	0	32	65	120	0
3	1928	115	264	1	23	67	134	1
4	1928	125	279	0	23	63	104	1
5	1928	133	293	0	23	64	110	1
6	1928	132	278	0	20	64	150	1
7	1928	97	269	0	20	65	137	1
8	1928	75	247	0	36	64	120	1
1	1929	136	286	0	25	62	93	0
2	1929	126	278	0	26	64	150	1
3	1929	139	284	0	37	61	121	0
4	1929	138	294	0	40	64	125	0
5	1929	130	296	1	22	66	117	1
6	1929	146	263	0	39	53	110	1
7	1929	126	298	0	24	61	112	0
8	1929	169	296	0	33	67	185	0
1	1930	138	244	0	33	62	178	0
2	1930	111	285	0	29	65	130	0
3	1930	144	304	1	27	58	102	1
4	1930	142	284	0	39	66	132	0
5	1930	104	307	0	24	59	122	0
6	1930	122	275	0	30	68	140	0
7	1930	122	275	1	20	65	127	0
8	1930	94	271	0	36	61	130	1
1	1931	132	245	0	23	65	140	0
2	1931	126	282	0	33	62	117	0
3	1931	99	270	0	22	63	115	1
4	1931	115	278	0	23	60	102	1
5	1931	106	278	0	31	65	110	1
6	1931	128	292	0	32	66	130	0
7	1931	152	295	0	39	62	140	0
8	1931	150	287	0	36	62	135	0
1	1932	120	289	0	25	62	125	0
2	1932	109	291	0	39	64	107	0
3	1932	105	280	1	22	63	116	0
4	1932	102	280	0	38	67	140	0
5	1932	120	281	0	33	63	113	0
6	1932	119	277	0	24	63	120	1
7	1932	116	274	0	21	62	110	1
8	1932	144	248	0	30	70	145	0
1	1933	143	299	0	30	66	136	1
2	1933	136	291	0	41	66	191	0
3	1933	89	275	0	34	66	170	0
4	1933	140	294	0	25	61	103	0
5	1933	118	276	1	18	63	128	0
6	1933	135	278	0	27	66	148	0
7	1933	132	302	0	36	63	145	1
8	1933	144	291	0	28	67	130	0
1	1934	140	351	0	27	68	120	0
2	1934	119	286	0	22	63	185	1
3	1934	129	270	0	43	67	160	0
4	1934	133	276	1	22	63	119	0
5	1934	140	290	1	19	67	132	1
6	1934	129	235	0	24	66	135	0
7	1934	84	260	1	37	66	140	0
8	1934	143	313	0	20	68	150	0
1	1935	144	282	0	32	64	124	1
2	1935	103	267	1	21	66	150	1
3	1935	119	270	1	20	64	109	0
4	1935	127	290	0	35	66	165	0
5	1935	114	268	0	22	64	104	0
6	1935	116	293	1	28	62	108	0
7	1935	119	277	1	18	61	89	1
8	1935	145	304	1	25	63	109	1
1	1936	141	279	0	23	63	128	1
2	1936	124	284	1	17	62	112	0
3	1936	114	291	0	35	60	112	0
4	1936	104	274	1	20	62	115	1
5	1936	116	280	0	40	62	159	0
6	1936	100	275	0	27	64	111	1
7	1936	106	312	0	24	62	135	1
8	1936	121	285	0	34	64	110	0
1	1937	110	281	0	36	61	99	1
2	1937	155	286	0	31	66	127	0
3	1937	106	289	0	28	67	120	1
4	1937	119	275	0	42	67	156	1
5	1937	129	284	0	24	64	115	0
6	1937	138	257	0	38	67	138	0
7	1937	139	291	0	24	65	160	0
8	1937	105	256	0	31	66	142	0
1	1938	114	273	0	30	63	154	0
2	1938	122	282	1	21	66	110	0
3	1938	122	292	1	34	65	133	0
4	1938	152	301	0	29	65	150	0
5	1938	120	286	0	22	62	115	1
6	1938	123	282	0	22	65	130	0
7	1938	103	273	0	36	65	158	1
8	1938	134	286	0	25	64	125	0
1	1939	115	285	0	38	63	130	0
2	1939	113	285	0	26	66	140	0
3	1939	136	261	0	24	65	110	0
4	1939	123	284	1	20	65	120	1
5	1939	127	281	0	24	63	112	1
6	1939	113	288	1	21	61	120	0
7	1939	112	299	0	24	67	145	1
8	1939	129	294	1	21	65	132	0
1	1940	92	255	0	25	65	125	1
2	1940	122	273	0	26	66	210	0
3	1940	121	286	1	22	69	130	1
4	1940	143	273	0	19	66	135	0
5	1940	71	234	0	32	64	110	1
6	1940	129	280	1	24	65	140	1
7	1940	96	276	0	33	64	127	1
8	1940	114	276	0	24	63	110	0
1	1941	115	261	0	33	60	125	1
2	1941	126	293	1	27	62	111	0
3	1941	112	282	0	26	65	122	0
4	1941	131	308	0	40	65	160	0
5	1941	88	274	0	30	66	130	0
6	1941	122	280	0	24	67	127	1
7	1941	102	281	1	19	67	135	1
8	1941	97	265	0	30	61	110	0
1	1942	144	261	0	33	68	170	0
2	1942	116	277	0	41	64	124	1
3	1942	112	266	0	26	64	122	0
4	1942	141	319	1	20	67	140	1
5	1942	122	286	0	23	64	145	0
6	1942	132	281	1	21	67	140	0
7	1942	120	300	0	34	63	150	1
8	1942	160	292	0	28	64	120	0
1	1943	119	288	0	43	66	142	1
2	1943	102	294	0	21	65	130	1
3	1943	123	314	0	22	61	121	1
4	1943	129	277	0	30	66	142	1
5	1943	106	302	1	19	66	147	0
6	1943	120	269	1	40	63	130	0
7	1943	102	338	0	19	64	170	0
8	1943	65	237	0	31	67	130	0
1	1944	105	270	0	22	56	93	0
2	1944	110	181	0	27	64	133	0
3	1944	139	286	0	33	65	125	1
4	1944	113	282	1	36	59	140	0
5	1944	135	285	0	30	66	130	0
6	1944	114	283	1	20	65	115	0
7	1944	97	255	1	22	63	107	1
8	1944	145	288	0	28	64	116	0
1	1945	115	274	0	27	67	175	1
2	1945	133	285	1	30	64	160	0
3	1945	125	290	0	36	59	105	0
4	1945	119	292	0	33	62	118	1
5	1945	107	290	0	26	63	112	0
6	1945	130	280	0	29	66	135	0
7	1945	113	285	0	22	70	145	0
8	1945	95	273	0	23	60	90	0
1	1946	137	287	0	25	66	145	0
2	1946	125	283	0	29	65	125	0
3	1946	105	295	1	20	64	112	1
4	1946	109	295	1	23	63	103	1
5	1946	129	294	0	32	62	170	1
6	1946	117	286	0	32	66	127	1
7	1946	130	297	0	32	58	130	0
8	1946	139	293	1	21	69	130	0
1	1947	122	276	0	30	68	182	0
2	1947	164	286	1	32	66	143	0
3	1947	130	276	0	41	68	130	0
4	1947	104	280	1	27	68	146	1
5	1947	126	274	0	39	62	122	0
6	1947	142	285	0	33	63	124	0
7	1947	97	260	1	25	63	115	1
8	1947	123	288	0	27	63	125	0
1	1948	131	294	0	23	65	122	0
2	1948	133	297	0	36	61	125	0
3	1948	146	294	0	22	66	145	1
4	1948	131	282	1	21	66	126	0
5	1948	116	293	1	26	64	125	0
6	1948	144	273	0	27	62	118	1
7	1948	116	273	0	31	61	120	0
8	1948	109	283	0	23	65	112	1
1	1949	103	261	0	27	65	112	1
2	1949	124	293	1	19	65	150	0
3	1949	133	290	0	21	64	145	0
4	1949	110	293	1	28	64	135	1
5	1949	124	294	0	26	62	122	0
6	1949	127	262	1	32	64	125	0
7	1949	114	266	0	29	64	113	0
8	1949	110	268	0	34	64	127	0
1	1950	146	280	0	26	58	106	0
2	1950	122	306	1	22	62	100	0
3	1950	147	296	1	19	67	124	0
4	1950	148	279	0	27	71	189	0
5	1950	123	281	0	23	68	136	0
6	1950	115	270	0	25	67	165	1
7	1950	127	242	0	17	61	135	1
8	1950	122	296	1	24	65	132	0
1	1951	114	266	0	20	65	175	1
2	1951	121	271	1	34	63	129	1
3	1951	109	269	0	23	63	113	0
4	1951	137	283	1	20	65	157	0
5	1951	145	315	0	39	67	143	1
6	1951	85	258	0	41	67	137	0
7	1951	87	247	1	18	66	125	1
8	1951	115	307	0	34	65	128	1
1	1952	125	292	0	32	65	125	0
2	1952	100	272	0	30	64	150	1
3	1952	122	286	0	23	64	120	1
4	1952	117	283	0	27	63	108	0
5	1952	102	278	0	27	67	135	1
6	1952	99	274	0	28	66	118	1
7	1952	141	281	0	29	54	156	1
8	1952	108	279	1	19	64	115	0
1	1953	114	274	0	28	66	132	1
2	1953	90	266	1	26	67	135	0
3	1953	135	260	0	43	65	135	0
4	1953	115	302	1	22	67	135	0
5	1953	129	293	0	30	65	130	1
6	1953	123	323	1	17	64	140	0
7	1953	144	283	1	25	66	140	0
8	1953	120	287	0	23	67	116	1
1	1954	122	270	0	26	61	105	0
2	1954	128	272	1	18	67	109	0
3	1954	117	272	0	32	66	118	0
4	1954	98	280	0	35	64	122	1
5	1954	98	276	1	22	61	121	0
6	1954	112	281	1	23	61	150	0
7	1954	116	273	0	33	66	130	1
8	1954	131	269	0	36	68	145	0
1	1955	93	278	0	34	61	146	0
2	1955	86	276	1	23	65	125	1
3	1955	138	284	0	30	66	133	1
4	1955	136	303	1	20	68	148	1
5	1955	110	272	0	28	60	108	0
6	1955	68	223	0	32	66	149	1
7	1955	75	265	0	21	65	103	1
8	1955	136	283	1	24	63	119	0
1	1956	130	268	0	30	66	123	0
2	1956	123	282	0	30	63	118	0
3	1956	120	283	0	28	64	122	1
4	1956	121	276	1	23	71	152	1
5	1956	135	282	0	24	67	128	1
6	1956	102	283	1	19	65	127	1
7	1956	138	286	1	28	68	120	0
8	1956	125	290	0	32	63	135	0
1	1957	119	275	0	23	60	105	0
2	1957	87	275	0	28	63	110	1
3	1957	119	273	0	35	65	125	1
4	1957	132	285	1	25	63	140	0
5	1957	101	278	1	20	62	105	0
6	1957	109	273	0	37	65	138	1
7	1957	99	271	0	39	69	151	0
8	1957	96	285	1	20	66	117	1
1	1958	113	281	0	24	65	120	0
2	1958	128	291	1	27	63	132	0
3	1958	118	278	1	19	62	126	0
4	1958	91	264	0	36	60	100	1
5	1958	96	266	0	26	65	125	0
6	1958	102	267	1	25	60	93	1
7	1958	118	293	0	21	63	103	0
8	1958	102	282	1	29	65	125	1
1	1959	134	283	0	22	67	130	0
2	1959	120	288	0	28	63	125	0
3	1959	105	330	0	23	64	112	1
4	1959	119	294	0	34	59	105	0
5	1959	104	276	1	18	60	109	1
6	1959	99	275	0	23	61	125	1
7	1959	97	266	0	24	62	109	0
8	1959	102	288	1	18	65	117	0
1	1960	107	279	0	24	63	115	0
2	1960	125	301	1	35	68	181	0
3	1960	113	306	1	21	65	137	0
4	1960	85	273	0	26	60	105	1
5	1960	100	249	0	24	67	100	0
6	1960	78	256	1	29	65	123	0
7	1960	146	319	0	28	66	145	0
8	1960	112	277	1	22	67	120	0
1	1961	134	288	0	23	63	92	1
2	1961	118	265	0	27	61	123	0
3	1961	148	291	1	21	63	115	0
4	1961	106	271	1	26	61	110	1
5	1961	154	292	0	40	66	145	0
6	1961	128	284	1	19	66	111	1
7	1961	81	285	0	19	63	150	1
8	1961	135	272	0	30	65	130	0
1	1962	122	267	0	27	65	101	1
2	1962	116	284	1	24	66	117	0
3	1962	140	281	1	22	69	135	0
4	1962	132	284	0	29	64	122	0
5	1962	127	293	0	31	67	137	0
6	1962	107	303	1	25	67	133	0
7	1962	110	321	0	28	66	180	0
8	1962	91	266	0	23	60	120	1
1	1963	129	293	0	30	61	160	0
2	1963	131	262	0	22	67	135	0
3	1963	134	287	1	33	67	131	0
4	1963	80	266	1	25	62	125	0
5	1963	126	288	0	31	62	150	0
6	1963	136	295	0	23	64	147	0
7	1963	135	284	1	19	60	95	0
8	1963	129	276	0	31	63	125	0
1	1964	110	278	0	23	63	177	0
2	1964	151	286	1	22	66	130	0
3	1964	120	280	0	31	61	111	0
4	1964	109	286	0	24	64	125	1
5	1964	126	282	1	23	66	115	1
6	1964	101	278	0	27	61	99	1
7	1964	114	290	1	21	65	120	1
8	1964	155	290	0	26	66	129	1
1	1965	111	270	0	27	61	119	0
2	1965	88	273	0	20	66	110	1
3	1965	123	296	1	26	64	110	1
4	1965	111	306	0	27	61	102	0
5	1965	127	279	0	26	67	155	1
6	1965	100	275	1	25	64	125	0
7	1965	124	288	1	21	64	116	1
8	1965	109	274	0	33	69	144	1
1	1966	87	248	0	37	65	130	1
2	1966	137	284	0	30	67	110	0
3	1966	102	275	0	43	64	160	0
4	1966	143	292	1	21	65	125	0
5	1966	98	275	0	25	65	112	1
6	1966	109	272	0	41	66	154	1
7	1966	115	262	1	23	64	136	1
8	1966	80	262	1	31	61	100	1
1	1967	143	274	0	27	63	110	1
2	1967	127	289	0	23	67	140	0
3	1967	55	204	0	35	65	140	0
4	1967	136	290	0	26	66	135	0
5	1967	127	288	1	21	66	130	0
6	1967	117	281	1	21	70	141	1
7	1967	143	281	0	28	65	135	1
8	1967	125	273	0	30	64	145	0
1	1968	155	294	0	32	66	150	0
2	1968	96	278	1	18	60	120	1
3	1968	103	276	1	19	63	149	1
4	1968	110	285	1	19	64	130	0
5	1968	129	299	0	22	68	145	0
6	1968	88	252	1	21	60	115	1
7	1968	113	287	1	29	70	145	1
8	1968	94	284	0	24	63	104	1
1	1969	110	272	0	25	60	90	0
2	1969	129	281	0	31	67	155	0
3	1969	123	283	0	21	65	110	0
4	1969	98	257	0	29	66	130	1
5	1969	131	292	1	22	64	124	1
6	1969	95	270	0	35	65	135	1
7	1969	109	244	1	21	63	102	1
8	1969	148	281	0	27	63	110	1
1	1970	122	275	0	26	66	147	0
2	1970	128	288	1	26	65	114	0
3	1970	105	270	1	27	65	134	1
4	1970	108	305	1	24	65	112	0
5	1970	132	289	1	19	66	145	0
6	1970	127	291	1	24	66	135	1
7	1970	103	278	0	30	60	87	1
8	1970	73	277	0	29	65	145	0
1	1971	145	291	0	26	63	119	1
2	1971	85	255	0	24	68	159	0
3	1971	138	289	0	33	65	155	0
4	1971	101	295	0	18	62	145	1
5	1971	127	280	0	27	62	118	0
6	1971	107	293	0	20	65	155	1
7	1971	118	276	0	34	64	116	0
8	1971	123	267	1	19	66	132	1
1	1972	115	258	0	26	62	130	0
2	1972	111	281	1	27	64	112	0
3	1972	128	281	0	28	63	150	0
4	1972	71	281	0	32	60	117	1
5	1972	99	313	1	34	59	100	1
6	1972	126	262	0	37	66	135	1
7	1972	127	290	0	27	65	121	0
8	1972	65	232	0	24	66	125	1
1	1973	108	283	0	31	65	148	1
2	1973	124	275	0	28	61	116	0
3	1973	139	285	0	30	65	129	1
4	1973	124	292	0	29	68	176	1
5	1973	115	290	0	30	64	140	1
6	1973	98	278	0	27	63	110	1
7	1973	132	270	0	27	65	126	0
8	1973	118	279	1	21	64	108	0
1	1974	102	282	0	28	61	110	0
2	1974	112	292	1	28	62	110	1
3	1974	104	288	1	27	61	122	1
4	1974	106	276	0	30	66	130	0
5	1974	145	290	1	24	67	125	0
6	1974	96	241	0	23	64	130	1
7	1974	113	275	1	27	60	100	0
8	1974	102	283	0	39	60	119	0
1	1975	143	286	0	31	64	126	0
2	1975	115	281	0	28	61	128	1
3	1975	159	296	1	27	64	112	0
4	1975	101	278	0	25	62	112	1
5	1975	102	249	1	23	67	134	1
6	1975	104	282	0	24	63	144	0
7	1975	128	265	0	24	67	120	0
8	1975	120	280	0	24	61	118	0
1	1976	146	267	0	30	67	132	0
2	1976	72	271	0	39	61	136	0
3	1976	118	276	0	29	62	130	1
4	1976	100	277	0	31	62	100	1
5	1976	136	299	0	29	64	115	0
6	1976	133	273	1	33	63	135	0
7	1976	130	291	0	30	65	150	1
8	1976	108	270	1	21	65	130	1
1	1977	124	275	0	22	60	130	0
2	1977	122	281	1	24	65	137	1
3	1977	99	285	0	25	69	128	1
4	1977	104	269	0	35	63	110	1
5	1977	121	282	0	22	66	133	0
6	1977	93	267	0	25	63	135	1
7	1977	125	281	1	21	65	110	0
8	1977	122	280	1	45	62	128	0
1	1978	124	278	0	26	70	145	1
2	1978	116	291	0	26	66	153	0
3	1978	144	281	0	20	63	120	0
4	1978	117	270	0	24	67	135	1
5	1978	120	286	0	25	62	105	0
6	1978	101	280	1	24	65	123	1
7	1978	117	297	0	38	65	129	0
8	1978	103	268	0	32	62	97	1
1	1979	145	257	0	33	65	140	0
2	1979	127	272	0	20	64	130	1
3	1979	121	270	0	25	62	108	1
4	1979	117	267	0	29	65	120	1
5	1979	118	261	0	26	60	104	0
6	1979	118	277	0	21	64	155	0
7	1979	141	277	0	38	66	162	0
8	1979	105	312	0	41	61	115	1
1	1980	106	273	0	28	60	116	0
2	1980	90	266	0	23	61	99	1
3	1980	117	265	1	24	66	98	0
4	1980	149	279	0	25	67	135	0
5	1980	127	304	1	26	62	105	0
6	1980	130	289	0	21	61	130	1
7	1980	130	270	1	19	66	130	0
8	1980	126	273	1	25	68	135	0
1	1981	75	232	0	33	61	110	0
2	1981	99	273	1	27	59	115	0
3	1981	119	293	1	23	65	127	0
4	1981	135	284	0	25	66	123	0
5	1981	132	281	1	24	63	117	0
6	1981	125	288	0	22	63	128	1
7	1981	139	299	1	20	67	112	0
8	1981	145	316	0	22	67	142	0
1	1982	107	273	0	24	61	96	0
2	1982	144	307	1	26	66	125	0
3	1982	105	281	1	19	61	130	0
4	1982	110	283	1	21	66	129	0
5	1982	102	258	1	22	65	135	0
6	1982	140	291	1	19	65	122	0
7	1982	130	283	0	32	65	118	0
8	1982	139	293	0	34	66	131	0
1	1983	124	288	0	22	67	118	0
2	1983	138	280	1	30	65	175	0
3	1983	125	283	0	37	63	145	1
4	1983	121	276	0	31	67	130	0
5	1983	143	279	0	39	65	129	1
6	1983	115	290	1	19	65	118	0
7	1983	113	289	1	26	59	91	0
8	1983	124	290	0	26	65	165	0
1	1984	122	280	0	23	65	125	1
2	1984	58	245	0	34	64	156	1
3	1984	119	259	0	37	62	130	0
4	1984	142	285	1	24	66	136	0
5	1984	118	277	0	25	62	120	0
6	1984	130	293	0	26	63	123	0
7	1984	77	238	1	23	63	103	1
8	1984	121	282	0	30	65	122	0
1	1985	101	245	0	23	63	130	1
2	1985	109	265	1	24	63	107	1
3	1985	101	273	0	39	60	113	0
4	1985	104	260	0	33	64	145	0
5	1985	102	286	1	22	64	140	0
6	1985	114	277	1	31	64	125	0
7	1985	62	228	0	24	61	107	0
8	1985	126	299	1	21	60	114	0
1	1986	128	283	0	28	63	125	1
2	1986	110	277	1	19	62	160	0
3	1986	105	277	1	25	64	156	0
4	1986	138	296	0	34	66	120	0
5	1986	163	280	0	35	69	139	0
6	1986	105	278	0	21	64	120	0
7	1986	93	245	0	33	61	100	1
8	1986	119	286	1	33	67	137	0
1	1987	104	282	0	36	65	115	1
2	1987	129	278	0	27	63	128	0
3	1987	110	281	0	27	60	110	0
4	1987	112	278	1	21	63	120	0
5	1987	132	294	0	32	64	116	0
6	1987	101	289	1	31	60	125	0
7	1987	109	275	1	37	63	112	1
8	1987	114	277	1	19	63	107	0
1	1988	97	246	0	37	63	150	0
2	1988	150	284	0	40	67	130	0
3	1988	100	270	1	21	65	132	1
4	1988	117	293	0	39	60	120	1
5	1988	116	276	0	33	61	180	0
6	1988	132	286	0	26	67	122	1
7	1988	145	283	0	27	65	125	1
8	1988	118	272	0	23	64	113	0
1	1989	137	274	0	26	69	137	1
2	1989	128	279	0	27	66	135	0
3	1989	98	284	0	29	68	140	0
4	1989	109	282	0	25	62	106	1
5	1989	138	288	1	19	66	124	0
6	1989	112	252	0	37	64	162	0
7	1989	92	224	0	19	63	134	1
8	1989	127	295	0	36	65	145	0
1	1990	103	273	0	31	63	170	1
2	1990	142	284	1	31	66	137	1
3	1990	127	276	0	37	64	159	0
4	1990	131	266	1	28	67	135	0
5	1990	139	279	0	20	64	143	0
6	1990	69	232	0	31	59	103	1
7	1990	120	281	0	26	61	115	0
8	1990	117	290	1	22	67	110	0
1	1991	142	276	0	38	63	170	0
2	1991	115	268	1	31	64	125	0
3	1991	117	324	0	22	62	164	1
4	1991	120	273	0	29	64	130	1
5	1991	132	298	1	23	61	137	0
6	1991	114	264	0	26	63	110	1
7	1991	135	284	0	39	67	141	0
8	1991	137	277	0	41	65	126	0
1	1992	130	289	0	27	66	130	0
2	1992	108	283	0	35	62	108	0
3	1992	122	278	0	37	68	114	0
4	1992	116	270	0	29	63	132	0
5	1992	87	282	0	27	63	104	1
6	1992	123	267	0	29	63	111	1
7	1992	113	287	0	36	63	118	0
8	1992	133	292	0	29	65	135	0
1	1993	156	292	0	26	63	118	0
2	1993	139	281	0	27	63	137	0
3	1993	122	273	1	23	64	130	1
4	1993	140	290	0	23	65	110	0
5	1993	131	297	0	30	67	132	0
6	1993	129	284	1	20	66	130	1
7	1993	126	251	1	28	64	123	0
8	1993	100	264	0	28	60	111	1
1	1994	133	284	0	25	66	125	1
2	1994	115	275	0	25	61	155	1
3	1994	118	281	1	36	66	140	1
4	1994	103	273	1	22	64	110	1
5	1994	130	282	0	26	67	147	1
6	1994	114	283	1	15	64	117	1
7	1994	143	270	1	27	70	148	0
8	1994	107	273	1	26	65	135	0
1	1995	120	274	0	24	62	120	0
2	1995	136	288	0	23	62	217	0
3	1995	137	303	1	23	66	127	1
4	1995	120	279	1	23	67	135	0
5	1995	123	290	0	28	66	107	1
6	1995	115	290	0	31	62	95	0
7	1995	128	282	1	25	64	125	0
8	1995	115	276	1	20	62	105	1
1	1996	91	270	0	24	60	149	1
2	1996	163	289	1	25	64	126	1
3	1996	120	275	0	32	63	115	1
4	1996	139	260	1	32	64	127	0
5	1996	115	276	1	18	63	110	0
6	1996	98	272	1	35	64	129	0
7	1996	98	262	0	22	67	120	0
8	1996	91	292	1	26	61	113	1
1	1997	127	274	0	21	62	110	0
2	1997	131	285	0	26	64	130	0
3	1997	143	285	0	27	68	185	0
4	1997	123	254	0	26	62	130	1
5	1997	116	272	0	27	64	130	1
6	1997	128	283	0	27	67	126	0
7	1997	110	306	1	32	61	122	0
8	1997	112	287	0	27	64	110	1
1	1998	153	286	0	26	63	107	1
2	1998	77	238	0	38	67	135	1
3	1998	108	270	0	29	67	124	1
4	1998	104	280	1	23	64	107	1
5	1998	119	286	1	20	67	130	0
6	1998	119	271	0	28	64	175	1
7	1998	162	284	0	27	64	126	0
8	1998	125	289	1	31	61	120	0
1	1999	121	276	0	39	63	130	0
2	1999	124	283	1	33	67	156	1
3	1999	131	284	1	19	61	114	1
4	1999	111	270	0	22	59	103	0
5	1999	125	279	1	19	67	135	0
6	1999	154	288	0	25	65	147	0
7	1999	116	292	1	20	65	118	0
8	1999	157	291	0	33	65	121	0
1	2000	120	277	0	27	63	126	0
2	2000	104	270	1	26	62	115	0
3	2000	110	277	0	36	61	116	0
4	2000	122	277	0	32	63	157	1
5	2000	144	282	0	33	66	155	1
6	2000	127	247	1	21	63	140	0
7	2000	128	284	0	23	62	110	0
8	2000	108	256	1	26	67	130	0
1	2001	99	272	0	27	62	103	1
2	2001	102	267	1	24	61	109	1
3	2001	105	276	0	20	62	112	1
4	2001	116	271	1	30	67	144	1
5	2001	123	269	0	26	67	132	0
6	2001	131	263	0	29	64	180	1
7	2001	111	275	1	18	61	108	1
8	2001	130	279	0	31	62	122	0
1	2002	149	293	0	35	65	116	0
2	2002	94	268	0	30	62	105	1
3	2002	125	255	0	23	63	133	0
4	2002	129	277	0	27	68	130	1
5	2002	120	276	0	23	66	114	0
6	2002	129	288	0	28	59	102	0
7	2002	137	280	0	34	60	107	0
8	2002	135	289	0	25	64	127	0
1	2003	129	280	0	23	64	104	0
2	2003	158	295	1	37	70	137	0
3	2003	78	258	1	24	66	115	1
4	2003	133	292	0	30	65	112	1
5	2003	140	251	0	28	63	210	0
6	2003	114	286	1	22	64	116	1
7	2003	100	264	0	29	64	120	1
8	2003	123	277	0	24	66	122	0
1	2004	139	292	0	25	68	135	0
2	2004	112	275	1	21	68	143	1
3	2004	114	289	0	36	60	115	0
4	2004	110	277	0	25	61	130	0
5	2004	120	271	1	17	64	142	1
6	2004	110	280	0	29	62	110	1
7	2004	160	271	0	32	67	215	0
8	2004	100	281	0	24	61	115	0

is.data.frame(vy1) #kiểm tra "vy1" có phải là data frame không, nếu đúng thì true và ngược lại

## [1] TRUE

1.4 . Thông tin tổng quan

length(vy1) #cho ra số biến của "vy1"

## [1] 9

names(vy1) #cho ra tên các biến của "vy1"

## [1] "id"        "year"      "bwt"       "gestation" "parity"    "age"      
## [7] "height"    "weight"    "smoke"

dim(vy1) #cho ra số quan sát và số biến của "vy1"

## [1] 640   9

sum(is.na(vy1)) #cho ra tổng số object của "vy1"

## [1] 0

library(skimr) 
skim(vy1)

Data summary
Name	vy1
Number of rows	640
Number of columns	9
_______________________
Column type frequency:
numeric	9
________________________
Group variables	None

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
id	1	4.50	2.29	1	2.75	4.5	6.25	8	▇▃▇▃▇
year	1	1964.50	23.11	1925	1944.75	1964.5	1984.25	2004	▇▇▇▇▇
bwt	1	118.89	18.14	55	107.75	120.0	131.00	169	▁▂▇▆▁
gestation	1	279.33	15.80	181	273.00	280.0	288.00	351	▁▁▇▅▁
parity	1	0.31	0.46	0	0.00	0.0	1.00	1	▇▁▁▁▃
age	1	27.28	5.86	15	23.00	26.0	31.00	45	▃▇▅▂▁
height	1	64.10	2.50	53	62.00	64.0	66.00	71	▁▁▅▇▁
weight	1	128.22	19.49	87	115.00	126.0	137.00	217	▃▇▃▁▁
smoke	1	0.40	0.49	0	0.00	0.0	1.00	1	▇▁▁▁▆

Mô tả

n_missing: số ô dữ liệu trống
complete_rate: tỷ lệ ô có dữ liệu
mean: trung bình
sd: độ lệch chuẩn
p0: giá trị min
p25: phân vị thứ nhất
p50: phân vị thứ hai(trung vị)
p75: phân vị thứ ba
p100: giá trị max
hist: biểu đồ Histogram

head(vy1,28) #lấy 28 dòng đầu từ "vy1"

##    id year bwt gestation parity age height weight smoke
## 1   1 1925 120       284      0  27     62    100     0
## 2   2 1925 112       267      1  22     62    138     0
## 3   3 1925 119       286      0  26     64    123     1
## 4   4 1925 124       287      0  27     62    105     1
## 5   5 1925 105       276      0  22     67    130     0
## 6   6 1925 120       289      1  31     59    102     0
## 7   7 1925  82       274      0  31     64    101     1
## 8   8 1925 111       278      0  29     65    145     1
## 9   1 1926 113       282      0  33     64    135     0
## 10  2 1926 134       297      0  27     67    170     1
## 11  3 1926  97       279      0  29     68    178     1
## 12  4 1926 125       292      0  22     65    122     0
## 13  5 1926  93       246      0  37     65    130     0
## 14  6 1926 146       280      0  23     61    145     0
## 15  7 1926 100       274      0  24     63    113     0
## 16  8 1926 103       250      0  40     59    140     0
## 17  1 1927 128       279      0  28     64    115     1
## 18  2 1927 145       308      0  35     64    110     1
## 19  3 1927  99       252      0  21     64    120     0
## 20  4 1927 110       262      0  25     66    140     0
## 21  5 1927 122       281      0  42     63    103     1
## 22  6 1927 112       283      1  21     62    102     1
## 23  7 1927 114       271      0  32     61    130     0
## 24  8 1927 114       276      0  26     62    127     0
## 25  1 1928 108       282      0  23     67    125     1
## 26  2 1928 116       295      0  32     65    120     0
## 27  3 1928 115       264      1  23     67    134     1
## 28  4 1928 125       279      0  23     63    104     1

tail(vy1,28) #lấy 28 dòng cuối từ "vy1"

##     id year bwt gestation parity age height weight smoke
## 613  5 2001 123       269      0  26     67    132     0
## 614  6 2001 131       263      0  29     64    180     1
## 615  7 2001 111       275      1  18     61    108     1
## 616  8 2001 130       279      0  31     62    122     0
## 617  1 2002 149       293      0  35     65    116     0
## 618  2 2002  94       268      0  30     62    105     1
## 619  3 2002 125       255      0  23     63    133     0
## 620  4 2002 129       277      0  27     68    130     1
## 621  5 2002 120       276      0  23     66    114     0
## 622  6 2002 129       288      0  28     59    102     0
## 623  7 2002 137       280      0  34     60    107     0
## 624  8 2002 135       289      0  25     64    127     0
## 625  1 2003 129       280      0  23     64    104     0
## 626  2 2003 158       295      1  37     70    137     0
## 627  3 2003  78       258      1  24     66    115     1
## 628  4 2003 133       292      0  30     65    112     1
## 629  5 2003 140       251      0  28     63    210     0
## 630  6 2003 114       286      1  22     64    116     1
## 631  7 2003 100       264      0  29     64    120     1
## 632  8 2003 123       277      0  24     66    122     0
## 633  1 2004 139       292      0  25     68    135     0
## 634  2 2004 112       275      1  21     68    143     1
## 635  3 2004 114       289      0  36     60    115     0
## 636  4 2004 110       277      0  25     61    130     0
## 637  5 2004 120       271      1  17     64    142     1
## 638  6 2004 110       280      0  29     62    110     1
## 639  7 2004 160       271      0  32     67    215     0
## 640  8 2004 100       281      0  24     61    115     0

is.na(vy1) # tìm ô không có dữ liệu trong "vy1", nếu "False" là có dữ liệu và ngược lại

##        id  year   bwt gestation parity   age height weight smoke
## 1   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 2   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 3   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 4   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 5   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 6   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 7   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 8   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 9   FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 10  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 11  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 12  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 13  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 14  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 15  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 16  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 17  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 18  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 19  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 20  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 21  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 22  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 23  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 24  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 25  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 26  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 27  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 28  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 29  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 30  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 31  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 32  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 33  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 34  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 35  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 36  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 37  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 38  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 39  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 40  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 41  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 42  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 43  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 44  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 45  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 46  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 47  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 48  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 49  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 50  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 51  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 52  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 53  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 54  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 55  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 56  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 57  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 58  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 59  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 60  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 61  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 62  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 63  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 64  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 65  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 66  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 67  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 68  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 69  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 70  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 71  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 72  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 73  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 74  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 75  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 76  FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 587 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 589 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 590 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 591 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 592 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 594 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 595 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 596 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 598 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 599 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 600 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 602 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 604 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 605 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 606 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 616 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 617 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 618 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 619 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 620 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 621 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
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## 625 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 626 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 627 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 628 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 629 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 630 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 631 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 632 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 633 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 634 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 635 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 636 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 637 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 638 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 639 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE
## 640 FALSE FALSE FALSE     FALSE  FALSE FALSE  FALSE  FALSE FALSE

sum(is.na(vy1)) # cho biết tổng số ô trống trong "vy1'

## [1] 0

which(is.na(vy1)) # cho biết vị trí ô trống trong "vy1"

## integer(0)

1.5 . Xử lý dữ liệu bị trùng lắp

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.0
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

vy <- unique(vy1) #lấy lượng biến của "vy1"
str(vy)

## 'data.frame':    640 obs. of  9 variables:
##  $ id       : num  1 2 3 4 5 6 7 8 1 2 ...
##  $ year     : num  1925 1925 1925 1925 1925 ...
##  $ bwt      : num  120 112 119 124 105 120 82 111 113 134 ...
##  $ gestation: num  284 267 286 287 276 289 274 278 282 297 ...
##  $ parity   : num  0 1 0 0 0 1 0 0 0 0 ...
##  $ age      : num  27 22 26 27 22 31 31 29 33 27 ...
##  $ height   : num  62 62 64 62 67 59 64 65 64 67 ...
##  $ weight   : num  100 138 123 105 130 102 101 145 135 170 ...
##  $ smoke    : num  0 0 1 1 0 0 1 1 0 1 ...

vyy <- distinct(vy1) #Loại bỏ trung lắp trong "vy1"
str(vyy)

## 'data.frame':    640 obs. of  9 variables:
##  $ id       : num  1 2 3 4 5 6 7 8 1 2 ...
##  $ year     : num  1925 1925 1925 1925 1925 ...
##  $ bwt      : num  120 112 119 124 105 120 82 111 113 134 ...
##  $ gestation: num  284 267 286 287 276 289 274 278 282 297 ...
##  $ parity   : num  0 1 0 0 0 1 0 0 0 0 ...
##  $ age      : num  27 22 26 27 22 31 31 29 33 27 ...
##  $ height   : num  62 62 64 62 67 59 64 65 64 67 ...
##  $ weight   : num  100 138 123 105 130 102 101 145 135 170 ...
##  $ smoke    : num  0 0 1 1 0 0 1 1 0 1 ...

1.6 . Rút trích dữ liệu

Mục đích của việc rút trích dữ liệu là để thu được những trường thông tin cần thiết nhằm phục vụ cho các mục tác vụ phân tích hoặc lưu trữ.

names(vy1) <- c("i", "y","b","g","p","a","h","w","s")
names(vy1)

## [1] "i" "y" "b" "g" "p" "a" "h" "w" "s"

vy2 <- vy1[5,3] #gán "vy2" là giá trị quan sát 5, biến 3
str(vy2)

##  num 105

vy3 <- vy1[1:5,4] # lấy giá trị 5 hàng đầu tiên biến "g"
str(vy3)

##  num [1:5] 284 267 286 287 276

vy4 <- vy1[c(1,2,3,4), c(3,4)] # lấy giá trị các quan sát 1,2,3,4 của biến "b" và "g"
str(vy4)

## 'data.frame':    4 obs. of  2 variables:
##  $ b: num  120 112 119 124
##  $ g: num  284 267 286 287

vy5 <- vy1[vy1$w >=100 & vy1$w <=108,] #Lấy giá trị những quan sát có giá trị ở biến "w" lớn hơn bằng 100 và bé hơn bằng 108
str(vy1)

## 'data.frame':    640 obs. of  9 variables:
##  $ i: num  1 2 3 4 5 6 7 8 1 2 ...
##  $ y: num  1925 1925 1925 1925 1925 ...
##  $ b: num  120 112 119 124 105 120 82 111 113 134 ...
##  $ g: num  284 267 286 287 276 289 274 278 282 297 ...
##  $ p: num  0 1 0 0 0 1 0 0 0 0 ...
##  $ a: num  27 22 26 27 22 31 31 29 33 27 ...
##  $ h: num  62 62 64 62 67 59 64 65 64 67 ...
##  $ w: num  100 138 123 105 130 102 101 145 135 170 ...
##  $ s: num  0 0 1 1 0 0 1 1 0 1 ...

vy6 <- vy1[vy1$w >130,] # lấy giá trị quan sát có giá trị ở biến "w" lớn hơn 130
str(vy6)

## 'data.frame':    233 obs. of  9 variables:
##  $ i: num  2 8 1 2 3 6 8 4 3 6 ...
##  $ y: num  1925 1925 1926 1926 1926 ...
##  $ b: num  112 111 113 134 97 146 103 110 115 132 ...
##  $ g: num  267 278 282 297 279 280 250 262 264 278 ...
##  $ p: num  1 0 0 0 0 0 0 0 1 0 ...
##  $ a: num  22 29 33 27 29 23 40 25 23 20 ...
##  $ h: num  62 65 64 67 68 61 59 66 67 64 ...
##  $ w: num  138 145 135 170 178 145 140 140 134 150 ...
##  $ s: num  0 1 0 1 1 0 0 0 1 1 ...

vy7 <- vy1[vy1$a == 30 | vy1$a == 40,] #lấy giá trị những quan sát ở biến "a" bằng 30 hoặc bằng 40
str(vy1)

## 'data.frame':    640 obs. of  9 variables:
##  $ i: num  1 2 3 4 5 6 7 8 1 2 ...
##  $ y: num  1925 1925 1925 1925 1925 ...
##  $ b: num  120 112 119 124 105 120 82 111 113 134 ...
##  $ g: num  284 267 286 287 276 289 274 278 282 297 ...
##  $ p: num  0 1 0 0 0 1 0 0 0 0 ...
##  $ a: num  27 22 26 27 22 31 31 29 33 27 ...
##  $ h: num  62 62 64 62 67 59 64 65 64 67 ...
##  $ w: num  100 138 123 105 130 102 101 145 135 170 ...
##  $ s: num  0 0 1 1 0 0 1 1 0 1 ...

vy8 <- filter(vy1,vy1$a >= 27 & vy1$g > 290) # lấy những quan sát có tuổi của mẹ lớn hơn hoặc bằng 27 và thời gian mang thai lớn hơn 290 ngày
str(vy8)

## 'data.frame':    61 obs. of  9 variables:
##  $ i: num  2 2 2 4 8 3 6 7 2 1 ...
##  $ y: num  1926 1927 1928 1929 1929 ...
##  $ b: num  134 145 116 138 169 144 128 152 109 143 ...
##  $ g: num  297 308 295 294 296 304 292 295 291 299 ...
##  $ p: num  0 0 0 0 0 1 0 0 0 0 ...
##  $ a: num  27 35 32 40 33 27 32 39 39 30 ...
##  $ h: num  67 64 65 64 67 58 66 62 64 66 ...
##  $ w: num  170 110 120 125 185 102 130 140 107 136 ...
##  $ s: num  1 1 0 0 0 1 0 0 0 1 ...

library(dplyr)

vy9 <- select(vy1,a,y,s) #chỉ lấy những biến tuổi của mẹ, năm lấy số liệu và hút thuốc lúc mang thai trong object "vy1"
str(vy9)

## 'data.frame':    640 obs. of  3 variables:
##  $ a: num  27 22 26 27 22 31 31 29 33 27 ...
##  $ y: num  1925 1925 1925 1925 1925 ...
##  $ s: num  0 0 1 1 0 0 1 1 0 1 ...

vy10 <- filter(vy1,a < 27 & w > 170) %>% select (i,a,h) # lấy những biến khu vực, tuổi, chiều cao với điều kiện quan sát có tuổi bé hơn 27 và cân nặng lớn hơn 170 pound
str(vy10)

## 'data.frame':    5 obs. of  3 variables:
##  $ i: num  2 2 1 1 2
##  $ a: num  22 26 20 23 23
##  $ h: num  63 66 65 63 62

1.7 . Tạo dữ liệu mới từ dữ liệu có sẵn

Tạo ra object mới là “vyx” từ object cũ là “vy1”. Có thêm các biến mới là: - tmg: thời gian mang thai tính bằng tháng - gra: trọng lượng lúc sinh tính bằng gram - kha: khả năng mang thai ở mức 30 tuổi ( trên 30 tuổi và dưới 30 tuổi) - dukien: dự kiến thời gian sinh em bé

vyx <- mutate(vy1, tmg= g/30) %>% mutate(vy1, gra= b*28.3495) #thêm biến thời gian mang thai tính bằng tháng và trọng lượng lúc sinh tính bằng gram
str(vyx)

## 'data.frame':    640 obs. of  11 variables:
##  $ i  : num  1 2 3 4 5 6 7 8 1 2 ...
##  $ y  : num  1925 1925 1925 1925 1925 ...
##  $ b  : num  120 112 119 124 105 120 82 111 113 134 ...
##  $ g  : num  284 267 286 287 276 289 274 278 282 297 ...
##  $ p  : num  0 1 0 0 0 1 0 0 0 0 ...
##  $ a  : num  27 22 26 27 22 31 31 29 33 27 ...
##  $ h  : num  62 62 64 62 67 59 64 65 64 67 ...
##  $ w  : num  100 138 123 105 130 102 101 145 135 170 ...
##  $ s  : num  0 0 1 1 0 0 1 1 0 1 ...
##  $ tmg: num  9.47 8.9 9.53 9.57 9.2 ...
##  $ gra: num  3402 3175 3374 3515 2977 ...

vyx$kha <- ifelse(vyx$a > 30 ,'thấp', 'cao') #thêm biến xác định khả năng mang thay trong ngoài 30 tuổi
str(vyx)

## 'data.frame':    640 obs. of  12 variables:
##  $ i  : num  1 2 3 4 5 6 7 8 1 2 ...
##  $ y  : num  1925 1925 1925 1925 1925 ...
##  $ b  : num  120 112 119 124 105 120 82 111 113 134 ...
##  $ g  : num  284 267 286 287 276 289 274 278 282 297 ...
##  $ p  : num  0 1 0 0 0 1 0 0 0 0 ...
##  $ a  : num  27 22 26 27 22 31 31 29 33 27 ...
##  $ h  : num  62 62 64 62 67 59 64 65 64 67 ...
##  $ w  : num  100 138 123 105 130 102 101 145 135 170 ...
##  $ s  : num  0 0 1 1 0 0 1 1 0 1 ...
##  $ tmg: num  9.47 8.9 9.53 9.57 9.2 ...
##  $ gra: num  3402 3175 3374 3515 2977 ...
##  $ kha: chr  "cao" "cao" "cao" "cao" ...

vyx$dukien <- case_when(vyx$g< 266 ~ 'sớm hơn dự kiến' , vyx$g < 280 ~ 'dự kiến' , vyx$g > 280 ~ ' trễ hơn dự kiến') # thêm biến dự kiến thời gian sinh
str(vyx)

## 'data.frame':    640 obs. of  13 variables:
##  $ i     : num  1 2 3 4 5 6 7 8 1 2 ...
##  $ y     : num  1925 1925 1925 1925 1925 ...
##  $ b     : num  120 112 119 124 105 120 82 111 113 134 ...
##  $ g     : num  284 267 286 287 276 289 274 278 282 297 ...
##  $ p     : num  0 1 0 0 0 1 0 0 0 0 ...
##  $ a     : num  27 22 26 27 22 31 31 29 33 27 ...
##  $ h     : num  62 62 64 62 67 59 64 65 64 67 ...
##  $ w     : num  100 138 123 105 130 102 101 145 135 170 ...
##  $ s     : num  0 0 1 1 0 0 1 1 0 1 ...
##  $ tmg   : num  9.47 8.9 9.53 9.57 9.2 ...
##  $ gra   : num  3402 3175 3374 3515 2977 ...
##  $ kha   : chr  "cao" "cao" "cao" "cao" ...
##  $ dukien: chr  " trễ hơn dự kiến" "dự kiến" " trễ hơn dự kiến" " trễ hơn dự kiến" ...

1.8 . Bảng tần số

table(vyx$dukien) # tần số của biến dự kiến thời gian sinh

## 
##  trễ hơn dự kiến          dự kiến  sớm hơn dự kiến 
##              319              217               82

stem(vyx$tmg) # biểu đồ nhánh của biến thời gian mang thai theo tháng

## 
##   The decimal point is at the |
## 
##    6 | 0
##    6 | 8
##    7 | 4
##    7 | 5677788999
##    8 | 01112222222223333344444
##    8 | 55555555666666667777777777777777788888888888889999999999999999999999
##    9 | 00000000000000000000000000000000000001111111111111111111111111111111+208
##    9 | 55555555555555555555555555555555555555555555555555555555555555566666+121
##   10 | 00000000011111111122222222334444
##   10 | 55566788
##   11 | 03
##   11 | 7

2 . NHIỆM VỤ 2.2

2.1 . Tóm tắt

Nhiệm vụ 2.2 thực hiện thao tác trên datasets Financial Sample Excel, là 1 dataset thống kê tình hình tài chính nổi bật của một số thị trường trên thế giới giai đoạn 2013-2014.

2.2 . Mô tả cơ bản

Datasets có 1006 quan sát và 16 biến như sau:

Segment: thị trường
Country: quốc gia
Product: sản phẩm tài chính
Discount Band: đánh giá mức độ rủi ro
Units Sold: số lượng sản phẩm hoặc dịch vụ đã bán
Manufacturing Price: chi phí sản xuất của 1 sản phẩm dịch vụ -
Sale Price: giá bán
Gross Sales: tổng doanh thu
Discounts: chiết khấu
Sales: doanh số bán hàng
COGS: số tiền chi trả sản xuất hoặc mua hàng hóa dịch vụ ảnh hưởng trực tiếp đến hoạt động tổ chức ( Cost of goods sold)
Profit: lợi nhuận
Date: ngày giá trị
Month Number: số thứ tự tháng trong năm
Month Name: tên tháng trong năm
Year: năm thu thập số liệu

library(openxlsx)
navy <- read.xlsx("/Users/xuyenchi/Library/Containers/com.microsoft.Excel/Data/Downloads/R Code/Financial Sample.xlsx") #Đọc dữ liệu từ file excel
table <- knitr::kable(navy,format="markdown")
table

Segment	Country	Product	Discount.Band	Units.Sold	Manufacturing.Price	Sale.Price	Gross.Sales	Discounts	Sales	COGS	Profit	Date	Month.Number	Month.Name	Year
Government	Canada	Carretera	None	1618.5	3	20	32370.0	0.000	32370.000	16185.0	16185.000	41640	1	January	2014
Government	Germany	Carretera	None	1321.0	3	20	26420.0	0.000	26420.000	13210.0	13210.000	41640	1	January	2014
Midmarket	France	Carretera	None	2178.0	3	15	32670.0	0.000	32670.000	21780.0	10890.000	41791	6	June	2014
Midmarket	Germany	Carretera	None	888.0	3	15	13320.0	0.000	13320.000	8880.0	4440.000	41791	6	June	2014
Midmarket	Mexico	Carretera	None	2470.0	3	15	37050.0	0.000	37050.000	24700.0	12350.000	41791	6	June	2014
Government	Germany	Carretera	None	1513.0	3	350	529550.0	0.000	529550.000	393380.0	136170.000	41974	12	December	2014
Midmarket	Germany	Montana	None	921.0	5	15	13815.0	0.000	13815.000	9210.0	4605.000	41699	3	March	2014
Channel Partners	Canada	Montana	None	2518.0	5	12	30216.0	0.000	30216.000	7554.0	22662.000	41791	6	June	2014
Government	France	Montana	None	1899.0	5	20	37980.0	0.000	37980.000	18990.0	18990.000	41791	6	June	2014
Channel Partners	Germany	Montana	None	1545.0	5	12	18540.0	0.000	18540.000	4635.0	13905.000	41791	6	June	2014
Midmarket	Mexico	Montana	None	2470.0	5	15	37050.0	0.000	37050.000	24700.0	12350.000	41791	6	June	2014
Enterprise	Canada	Montana	None	2665.5	5	125	333187.5	0.000	333187.500	319860.0	13327.500	41821	7	July	2014
Small Business	Mexico	Montana	None	958.0	5	300	287400.0	0.000	287400.000	239500.0	47900.000	41852	8	August	2014
Government	Germany	Montana	None	2146.0	5	7	15022.0	0.000	15022.000	10730.0	4292.000	41883	9	September	2014
Enterprise	Canada	Montana	None	345.0	5	125	43125.0	0.000	43125.000	41400.0	1725.000	41548	10	October	2013
Midmarket	United States of America	Montana	None	615.0	5	15	9225.0	0.000	9225.000	6150.0	3075.000	41974	12	December	2014
Government	Canada	Paseo	None	292.0	10	20	5840.0	0.000	5840.000	2920.0	2920.000	41671	2	February	2014
Midmarket	Mexico	Paseo	None	974.0	10	15	14610.0	0.000	14610.000	9740.0	4870.000	41671	2	February	2014
Channel Partners	Canada	Paseo	None	2518.0	10	12	30216.0	0.000	30216.000	7554.0	22662.000	41791	6	June	2014
Government	Germany	Paseo	None	1006.0	10	350	352100.0	0.000	352100.000	261560.0	90540.000	41791	6	June	2014
Channel Partners	Germany	Paseo	None	367.0	10	12	4404.0	0.000	4404.000	1101.0	3303.000	41821	7	July	2014
Government	Mexico	Paseo	None	883.0	10	7	6181.0	0.000	6181.000	4415.0	1766.000	41852	8	August	2014
Midmarket	France	Paseo	None	549.0	10	15	8235.0	0.000	8235.000	5490.0	2745.000	41518	9	September	2013
Small Business	Mexico	Paseo	None	788.0	10	300	236400.0	0.000	236400.000	197000.0	39400.000	41518	9	September	2013
Midmarket	Mexico	Paseo	None	2472.0	10	15	37080.0	0.000	37080.000	24720.0	12360.000	41883	9	September	2014
Government	United States of America	Paseo	None	1143.0	10	7	8001.0	0.000	8001.000	5715.0	2286.000	41913	10	October	2014
Government	Canada	Paseo	None	1725.0	10	350	603750.0	0.000	603750.000	448500.0	155250.000	41579	11	November	2013
Channel Partners	United States of America	Paseo	None	912.0	10	12	10944.0	0.000	10944.000	2736.0	8208.000	41579	11	November	2013
Midmarket	Canada	Paseo	None	2152.0	10	15	32280.0	0.000	32280.000	21520.0	10760.000	41609	12	December	2013
Government	Canada	Paseo	None	1817.0	10	20	36340.0	0.000	36340.000	18170.0	18170.000	41974	12	December	2014
Government	Germany	Paseo	None	1513.0	10	350	529550.0	0.000	529550.000	393380.0	136170.000	41974	12	December	2014
Government	Mexico	Velo	None	1493.0	120	7	10451.0	0.000	10451.000	7465.0	2986.000	41640	1	January	2014
Enterprise	France	Velo	None	1804.0	120	125	225500.0	0.000	225500.000	216480.0	9020.000	41671	2	February	2014
Channel Partners	Germany	Velo	None	2161.0	120	12	25932.0	0.000	25932.000	6483.0	19449.000	41699	3	March	2014
Government	Germany	Velo	None	1006.0	120	350	352100.0	0.000	352100.000	261560.0	90540.000	41791	6	June	2014
Channel Partners	Germany	Velo	None	1545.0	120	12	18540.0	0.000	18540.000	4635.0	13905.000	41791	6	June	2014
Enterprise	United States of America	Velo	None	2821.0	120	125	352625.0	0.000	352625.000	338520.0	14105.000	41852	8	August	2014
Enterprise	Canada	Velo	None	345.0	120	125	43125.0	0.000	43125.000	41400.0	1725.000	41548	10	October	2013
Small Business	Canada	VTT	None	2001.0	250	300	600300.0	0.000	600300.000	500250.0	100050.000	41671	2	February	2014
Channel Partners	Germany	VTT	None	2838.0	250	12	34056.0	0.000	34056.000	8514.0	25542.000	41730	4	April	2014
Midmarket	France	VTT	None	2178.0	250	15	32670.0	0.000	32670.000	21780.0	10890.000	41791	6	June	2014
Midmarket	Germany	VTT	None	888.0	250	15	13320.0	0.000	13320.000	8880.0	4440.000	41791	6	June	2014
Government	France	VTT	None	1527.0	250	350	534450.0	0.000	534450.000	397020.0	137430.000	41518	9	September	2013
Small Business	France	VTT	None	2151.0	250	300	645300.0	0.000	645300.000	537750.0	107550.000	41883	9	September	2014
Government	Canada	VTT	None	1817.0	250	20	36340.0	0.000	36340.000	18170.0	18170.000	41974	12	December	2014
Government	France	Amarilla	None	2750.0	260	350	962500.0	0.000	962500.000	715000.0	247500.000	41671	2	February	2014
Channel Partners	United States of America	Amarilla	None	1953.0	260	12	23436.0	0.000	23436.000	5859.0	17577.000	41730	4	April	2014
Enterprise	Germany	Amarilla	None	4219.5	260	125	527437.5	0.000	527437.500	506340.0	21097.500	41730	4	April	2014
Government	France	Amarilla	None	1899.0	260	20	37980.0	0.000	37980.000	18990.0	18990.000	41791	6	June	2014
Government	Germany	Amarilla	None	1686.0	260	7	11802.0	0.000	11802.000	8430.0	3372.000	41821	7	July	2014
Channel Partners	United States of America	Amarilla	None	2141.0	260	12	25692.0	0.000	25692.000	6423.0	19269.000	41852	8	August	2014
Government	United States of America	Amarilla	None	1143.0	260	7	8001.0	0.000	8001.000	5715.0	2286.000	41913	10	October	2014
Midmarket	United States of America	Amarilla	None	615.0	260	15	9225.0	0.000	9225.000	6150.0	3075.000	41974	12	December	2014
Government	France	Paseo	Low	3945.0	10	7	27615.0	276.150	27338.850	19725.0	7613.850	41640	1	January	2014
Midmarket	France	Paseo	Low	2296.0	10	15	34440.0	344.400	34095.600	22960.0	11135.600	41671	2	February	2014
Government	France	Paseo	Low	1030.0	10	7	7210.0	72.100	7137.900	5150.0	1987.900	41760	5	May	2014
Government	France	Velo	Low	639.0	120	7	4473.0	44.730	4428.270	3195.0	1233.270	41944	11	November	2014
Government	Canada	VTT	Low	1326.0	250	7	9282.0	92.820	9189.180	6630.0	2559.180	41699	3	March	2014
Channel Partners	United States of America	Carretera	Low	1858.0	3	12	22296.0	222.960	22073.040	5574.0	16499.040	41671	2	February	2014
Government	Mexico	Carretera	Low	1210.0	3	350	423500.0	4235.000	419265.000	314600.0	104665.000	41699	3	March	2014
Government	United States of America	Carretera	Low	2529.0	3	7	17703.0	177.030	17525.970	12645.0	4880.970	41821	7	July	2014
Channel Partners	Canada	Carretera	Low	1445.0	3	12	17340.0	173.400	17166.600	4335.0	12831.600	41883	9	September	2014
Enterprise	United States of America	Carretera	Low	330.0	3	125	41250.0	412.500	40837.500	39600.0	1237.500	41518	9	September	2013
Channel Partners	France	Carretera	Low	2671.0	3	12	32052.0	320.520	31731.480	8013.0	23718.480	41883	9	September	2014
Channel Partners	Germany	Carretera	Low	766.0	3	12	9192.0	91.920	9100.080	2298.0	6802.080	41548	10	October	2013
Small Business	Mexico	Carretera	Low	494.0	3	300	148200.0	1482.000	146718.000	123500.0	23218.000	41548	10	October	2013
Government	Mexico	Carretera	Low	1397.0	3	350	488950.0	4889.500	484060.500	363220.0	120840.500	41913	10	October	2014
Government	France	Carretera	Low	2155.0	3	350	754250.0	7542.500	746707.500	560300.0	186407.500	41974	12	December	2014
Midmarket	Mexico	Montana	Low	2214.0	5	15	33210.0	332.100	32877.900	22140.0	10737.900	41699	3	March	2014
Small Business	United States of America	Montana	Low	2301.0	5	300	690300.0	6903.000	683397.000	575250.0	108147.000	41730	4	April	2014
Government	France	Montana	Low	1375.5	5	20	27510.0	275.100	27234.900	13755.0	13479.900	41821	7	July	2014
Government	Canada	Montana	Low	1830.0	5	7	12810.0	128.100	12681.900	9150.0	3531.900	41852	8	August	2014
Small Business	United States of America	Montana	Low	2498.0	5	300	749400.0	7494.000	741906.000	624500.0	117406.000	41518	9	September	2013
Enterprise	United States of America	Montana	Low	663.0	5	125	82875.0	828.750	82046.250	79560.0	2486.250	41548	10	October	2013
Midmarket	United States of America	Paseo	Low	1514.0	10	15	22710.0	227.100	22482.900	15140.0	7342.900	41671	2	February	2014
Government	United States of America	Paseo	Low	4492.5	10	7	31447.5	314.475	31133.025	22462.5	8670.525	41730	4	April	2014
Enterprise	United States of America	Paseo	Low	727.0	10	125	90875.0	908.750	89966.250	87240.0	2726.250	41791	6	June	2014
Enterprise	France	Paseo	Low	787.0	10	125	98375.0	983.750	97391.250	94440.0	2951.250	41791	6	June	2014
Enterprise	Mexico	Paseo	Low	1823.0	10	125	227875.0	2278.750	225596.250	218760.0	6836.250	41821	7	July	2014
Midmarket	Germany	Paseo	Low	747.0	10	15	11205.0	112.050	11092.950	7470.0	3622.950	41883	9	September	2014
Channel Partners	Germany	Paseo	Low	766.0	10	12	9192.0	91.920	9100.080	2298.0	6802.080	41548	10	October	2013
Small Business	United States of America	Paseo	Low	2905.0	10	300	871500.0	8715.000	862785.000	726250.0	136535.000	41944	11	November	2014
Government	France	Paseo	Low	2155.0	10	350	754250.0	7542.500	746707.500	560300.0	186407.500	41974	12	December	2014
Government	France	Velo	Low	3864.0	120	20	77280.0	772.800	76507.200	38640.0	37867.200	41730	4	April	2014
Government	Mexico	Velo	Low	362.0	120	7	2534.0	25.340	2508.660	1810.0	698.660	41760	5	May	2014
Enterprise	Canada	Velo	Low	923.0	120	125	115375.0	1153.750	114221.250	110760.0	3461.250	41852	8	August	2014
Enterprise	United States of America	Velo	Low	663.0	120	125	82875.0	828.750	82046.250	79560.0	2486.250	41548	10	October	2013
Government	Canada	Velo	Low	2092.0	120	7	14644.0	146.440	14497.560	10460.0	4037.560	41579	11	November	2013
Government	Germany	VTT	Low	263.0	250	7	1841.0	18.410	1822.590	1315.0	507.590	41699	3	March	2014
Government	Canada	VTT	Low	943.5	250	350	330225.0	3302.250	326922.750	245310.0	81612.750	41730	4	April	2014
Enterprise	United States of America	VTT	Low	727.0	250	125	90875.0	908.750	89966.250	87240.0	2726.250	41791	6	June	2014
Enterprise	France	VTT	Low	787.0	250	125	98375.0	983.750	97391.250	94440.0	2951.250	41791	6	June	2014
Small Business	Germany	VTT	Low	986.0	250	300	295800.0	2958.000	292842.000	246500.0	46342.000	41883	9	September	2014
Small Business	Mexico	VTT	Low	494.0	250	300	148200.0	1482.000	146718.000	123500.0	23218.000	41548	10	October	2013
Government	Mexico	VTT	Low	1397.0	250	350	488950.0	4889.500	484060.500	363220.0	120840.500	41913	10	October	2014
Enterprise	France	VTT	Low	1744.0	250	125	218000.0	2180.000	215820.000	209280.0	6540.000	41944	11	November	2014
Channel Partners	United States of America	Amarilla	Low	1989.0	260	12	23868.0	238.680	23629.320	5967.0	17662.320	41518	9	September	2013
Midmarket	France	Amarilla	Low	321.0	260	15	4815.0	48.150	4766.850	3210.0	1556.850	41579	11	November	2013
Enterprise	Canada	Carretera	Low	742.5	3	125	92812.5	1856.250	90956.250	89100.0	1856.250	41730	4	April	2014
Channel Partners	Canada	Carretera	Low	1295.0	3	12	15540.0	310.800	15229.200	3885.0	11344.200	41913	10	October	2014
Small Business	Germany	Carretera	Low	214.0	3	300	64200.0	1284.000	62916.000	53500.0	9416.000	41548	10	October	2013
Government	France	Carretera	Low	2145.0	3	7	15015.0	300.300	14714.700	10725.0	3989.700	41579	11	November	2013
Government	Canada	Carretera	Low	2852.0	3	350	998200.0	19964.000	978236.000	741520.0	236716.000	41974	12	December	2014
Channel Partners	United States of America	Montana	Low	1142.0	5	12	13704.0	274.080	13429.920	3426.0	10003.920	41791	6	June	2014
Government	United States of America	Montana	Low	1566.0	5	20	31320.0	626.400	30693.600	15660.0	15033.600	41913	10	October	2014
Channel Partners	Mexico	Montana	Low	690.0	5	12	8280.0	165.600	8114.400	2070.0	6044.400	41944	11	November	2014
Enterprise	Mexico	Montana	Low	1660.0	5	125	207500.0	4150.000	203350.000	199200.0	4150.000	41579	11	November	2013
Midmarket	Canada	Paseo	Low	2363.0	10	15	35445.0	708.900	34736.100	23630.0	11106.100	41671	2	February	2014
Small Business	France	Paseo	Low	918.0	10	300	275400.0	5508.000	269892.000	229500.0	40392.000	41760	5	May	2014
Small Business	Germany	Paseo	Low	1728.0	10	300	518400.0	10368.000	508032.000	432000.0	76032.000	41760	5	May	2014
Channel Partners	United States of America	Paseo	Low	1142.0	10	12	13704.0	274.080	13429.920	3426.0	10003.920	41791	6	June	2014
Enterprise	Mexico	Paseo	Low	662.0	10	125	82750.0	1655.000	81095.000	79440.0	1655.000	41791	6	June	2014
Channel Partners	Canada	Paseo	Low	1295.0	10	12	15540.0	310.800	15229.200	3885.0	11344.200	41913	10	October	2014
Enterprise	Germany	Paseo	Low	809.0	10	125	101125.0	2022.500	99102.500	97080.0	2022.500	41548	10	October	2013
Enterprise	Mexico	Paseo	Low	2145.0	10	125	268125.0	5362.500	262762.500	257400.0	5362.500	41548	10	October	2013
Channel Partners	France	Paseo	Low	1785.0	10	12	21420.0	428.400	20991.600	5355.0	15636.600	41579	11	November	2013
Small Business	Canada	Paseo	Low	1916.0	10	300	574800.0	11496.000	563304.000	479000.0	84304.000	41974	12	December	2014
Government	Canada	Paseo	Low	2852.0	10	350	998200.0	19964.000	978236.000	741520.0	236716.000	41974	12	December	2014
Enterprise	Canada	Paseo	Low	2729.0	10	125	341125.0	6822.500	334302.500	327480.0	6822.500	41974	12	December	2014
Midmarket	United States of America	Paseo	Low	1925.0	10	15	28875.0	577.500	28297.500	19250.0	9047.500	41609	12	December	2013
Government	United States of America	Paseo	Low	2013.0	10	7	14091.0	281.820	13809.180	10065.0	3744.180	41609	12	December	2013
Channel Partners	France	Paseo	Low	1055.0	10	12	12660.0	253.200	12406.800	3165.0	9241.800	41974	12	December	2014
Channel Partners	Mexico	Paseo	Low	1084.0	10	12	13008.0	260.160	12747.840	3252.0	9495.840	41974	12	December	2014
Government	United States of America	Velo	Low	1566.0	120	20	31320.0	626.400	30693.600	15660.0	15033.600	41913	10	October	2014
Government	Germany	Velo	Low	2966.0	120	350	1038100.0	20762.000	1017338.000	771160.0	246178.000	41548	10	October	2013
Government	Germany	Velo	Low	2877.0	120	350	1006950.0	20139.000	986811.000	748020.0	238791.000	41913	10	October	2014
Enterprise	Germany	Velo	Low	809.0	120	125	101125.0	2022.500	99102.500	97080.0	2022.500	41548	10	October	2013
Enterprise	Mexico	Velo	Low	2145.0	120	125	268125.0	5362.500	262762.500	257400.0	5362.500	41548	10	October	2013
Channel Partners	France	Velo	Low	1055.0	120	12	12660.0	253.200	12406.800	3165.0	9241.800	41974	12	December	2014
Government	Mexico	Velo	Low	544.0	120	20	10880.0	217.600	10662.400	5440.0	5222.400	41609	12	December	2013
Channel Partners	Mexico	Velo	Low	1084.0	120	12	13008.0	260.160	12747.840	3252.0	9495.840	41974	12	December	2014
Enterprise	Mexico	VTT	Low	662.0	250	125	82750.0	1655.000	81095.000	79440.0	1655.000	41791	6	June	2014
Small Business	Germany	VTT	Low	214.0	250	300	64200.0	1284.000	62916.000	53500.0	9416.000	41548	10	October	2013
Government	Germany	VTT	Low	2877.0	250	350	1006950.0	20139.000	986811.000	748020.0	238791.000	41913	10	October	2014
Enterprise	Canada	VTT	Low	2729.0	250	125	341125.0	6822.500	334302.500	327480.0	6822.500	41974	12	December	2014
Government	United States of America	VTT	Low	266.0	250	350	93100.0	1862.000	91238.000	69160.0	22078.000	41609	12	December	2013
Government	Mexico	VTT	Low	1940.0	250	350	679000.0	13580.000	665420.000	504400.0	161020.000	41609	12	December	2013
Small Business	Germany	Amarilla	Low	259.0	260	300	77700.0	1554.000	76146.000	64750.0	11396.000	41699	3	March	2014
Small Business	Mexico	Amarilla	Low	1101.0	260	300	330300.0	6606.000	323694.000	275250.0	48444.000	41699	3	March	2014
Enterprise	Germany	Amarilla	Low	2276.0	260	125	284500.0	5690.000	278810.000	273120.0	5690.000	41760	5	May	2014
Government	Germany	Amarilla	Low	2966.0	260	350	1038100.0	20762.000	1017338.000	771160.0	246178.000	41548	10	October	2013
Government	United States of America	Amarilla	Low	1236.0	260	20	24720.0	494.400	24225.600	12360.0	11865.600	41944	11	November	2014
Government	France	Amarilla	Low	941.0	260	20	18820.0	376.400	18443.600	9410.0	9033.600	41944	11	November	2014
Small Business	Canada	Amarilla	Low	1916.0	260	300	574800.0	11496.000	563304.000	479000.0	84304.000	41974	12	December	2014
Enterprise	France	Carretera	Low	4243.5	3	125	530437.5	15913.125	514524.375	509220.0	5304.375	41730	4	April	2014
Government	Germany	Carretera	Low	2580.0	3	20	51600.0	1548.000	50052.000	25800.0	24252.000	41730	4	April	2014
Small Business	Germany	Carretera	Low	689.0	3	300	206700.0	6201.000	200499.000	172250.0	28249.000	41791	6	June	2014
Channel Partners	United States of America	Carretera	Low	1947.0	3	12	23364.0	700.920	22663.080	5841.0	16822.080	41883	9	September	2014
Channel Partners	Canada	Carretera	Low	908.0	3	12	10896.0	326.880	10569.120	2724.0	7845.120	41609	12	December	2013
Government	Germany	Montana	Low	1958.0	5	7	13706.0	411.180	13294.820	9790.0	3504.820	41671	2	February	2014
Channel Partners	France	Montana	Low	1901.0	5	12	22812.0	684.360	22127.640	5703.0	16424.640	41791	6	June	2014
Government	France	Montana	Low	544.0	5	7	3808.0	114.240	3693.760	2720.0	973.760	41883	9	September	2014
Government	Germany	Montana	Low	1797.0	5	350	628950.0	18868.500	610081.500	467220.0	142861.500	41518	9	September	2013
Enterprise	France	Montana	Low	1287.0	5	125	160875.0	4826.250	156048.750	154440.0	1608.750	41974	12	December	2014
Enterprise	Germany	Montana	Low	1706.0	5	125	213250.0	6397.500	206852.500	204720.0	2132.500	41974	12	December	2014
Small Business	France	Paseo	Low	2434.5	10	300	730350.0	21910.500	708439.500	608625.0	99814.500	41640	1	January	2014
Enterprise	Canada	Paseo	Low	1774.0	10	125	221750.0	6652.500	215097.500	212880.0	2217.500	41699	3	March	2014
Channel Partners	France	Paseo	Low	1901.0	10	12	22812.0	684.360	22127.640	5703.0	16424.640	41791	6	June	2014
Small Business	Germany	Paseo	Low	689.0	10	300	206700.0	6201.000	200499.000	172250.0	28249.000	41791	6	June	2014
Enterprise	Germany	Paseo	Low	1570.0	10	125	196250.0	5887.500	190362.500	188400.0	1962.500	41791	6	June	2014
Channel Partners	United States of America	Paseo	Low	1369.5	10	12	16434.0	493.020	15940.980	4108.5	11832.480	41821	7	July	2014
Enterprise	Canada	Paseo	Low	2009.0	10	125	251125.0	7533.750	243591.250	241080.0	2511.250	41913	10	October	2014
Midmarket	Germany	Paseo	Low	1945.0	10	15	29175.0	875.250	28299.750	19450.0	8849.750	41548	10	October	2013
Enterprise	France	Paseo	Low	1287.0	10	125	160875.0	4826.250	156048.750	154440.0	1608.750	41974	12	December	2014
Enterprise	Germany	Paseo	Low	1706.0	10	125	213250.0	6397.500	206852.500	204720.0	2132.500	41974	12	December	2014
Enterprise	Canada	Velo	Low	2009.0	120	125	251125.0	7533.750	243591.250	241080.0	2511.250	41913	10	October	2014
Small Business	United States of America	VTT	Low	2844.0	250	300	853200.0	25596.000	827604.000	711000.0	116604.000	41671	2	February	2014
Channel Partners	Mexico	VTT	Low	1916.0	250	12	22992.0	689.760	22302.240	5748.0	16554.240	41730	4	April	2014
Enterprise	Germany	VTT	Low	1570.0	250	125	196250.0	5887.500	190362.500	188400.0	1962.500	41791	6	June	2014
Small Business	Canada	VTT	Low	1874.0	250	300	562200.0	16866.000	545334.000	468500.0	76834.000	41852	8	August	2014
Government	Mexico	VTT	Low	1642.0	250	350	574700.0	17241.000	557459.000	426920.0	130539.000	41852	8	August	2014
Midmarket	Germany	VTT	Low	1945.0	250	15	29175.0	875.250	28299.750	19450.0	8849.750	41548	10	October	2013
Government	Canada	Carretera	Low	831.0	3	20	16620.0	498.600	16121.400	8310.0	7811.400	41760	5	May	2014
Government	Mexico	Paseo	Low	1760.0	10	7	12320.0	369.600	11950.400	8800.0	3150.400	41518	9	September	2013
Government	Canada	Velo	Low	3850.5	120	20	77010.0	2310.300	74699.700	38505.0	36194.700	41730	4	April	2014
Channel Partners	Germany	VTT	Low	2479.0	250	12	29748.0	892.440	28855.560	7437.0	21418.560	41640	1	January	2014
Midmarket	Mexico	Montana	Low	2031.0	5	15	30465.0	1218.600	29246.400	20310.0	8936.400	41913	10	October	2014
Midmarket	Mexico	Paseo	Low	2031.0	10	15	30465.0	1218.600	29246.400	20310.0	8936.400	41913	10	October	2014
Midmarket	France	Paseo	Low	2261.0	10	15	33915.0	1356.600	32558.400	22610.0	9948.400	41609	12	December	2013
Government	United States of America	Velo	Low	736.0	120	20	14720.0	588.800	14131.200	7360.0	6771.200	41518	9	September	2013
Government	Canada	Carretera	Low	2851.0	3	7	19957.0	798.280	19158.720	14255.0	4903.720	41548	10	October	2013
Small Business	Germany	Carretera	Low	2021.0	3	300	606300.0	24252.000	582048.000	505250.0	76798.000	41913	10	October	2014
Government	United States of America	Carretera	Low	274.0	3	350	95900.0	3836.000	92064.000	71240.0	20824.000	41974	12	December	2014
Midmarket	Canada	Montana	Low	1967.0	5	15	29505.0	1180.200	28324.800	19670.0	8654.800	41699	3	March	2014
Small Business	Germany	Montana	Low	1859.0	5	300	557700.0	22308.000	535392.000	464750.0	70642.000	41852	8	August	2014
Government	Canada	Montana	Low	2851.0	5	7	19957.0	798.280	19158.720	14255.0	4903.720	41548	10	October	2013
Small Business	Germany	Montana	Low	2021.0	5	300	606300.0	24252.000	582048.000	505250.0	76798.000	41913	10	October	2014
Enterprise	Mexico	Montana	Low	1138.0	5	125	142250.0	5690.000	136560.000	136560.0	0.000	41974	12	December	2014
Government	Canada	Paseo	Low	4251.0	10	7	29757.0	1190.280	28566.720	21255.0	7311.720	41640	1	January	2014
Enterprise	Germany	Paseo	Low	795.0	10	125	99375.0	3975.000	95400.000	95400.0	0.000	41699	3	March	2014
Small Business	Germany	Paseo	Low	1414.5	10	300	424350.0	16974.000	407376.000	353625.0	53751.000	41730	4	April	2014
Small Business	United States of America	Paseo	Low	2918.0	10	300	875400.0	35016.000	840384.000	729500.0	110884.000	41760	5	May	2014
Government	United States of America	Paseo	Low	3450.0	10	350	1207500.0	48300.000	1159200.000	897000.0	262200.000	41821	7	July	2014
Enterprise	France	Paseo	Low	2988.0	10	125	373500.0	14940.000	358560.000	358560.0	0.000	41821	7	July	2014
Midmarket	Canada	Paseo	Low	218.0	10	15	3270.0	130.800	3139.200	2180.0	959.200	41883	9	September	2014
Government	Canada	Paseo	Low	2074.0	10	20	41480.0	1659.200	39820.800	20740.0	19080.800	41883	9	September	2014
Government	United States of America	Paseo	Low	1056.0	10	20	21120.0	844.800	20275.200	10560.0	9715.200	41883	9	September	2014
Midmarket	United States of America	Paseo	Low	671.0	10	15	10065.0	402.600	9662.400	6710.0	2952.400	41548	10	October	2013
Midmarket	Mexico	Paseo	Low	1514.0	10	15	22710.0	908.400	21801.600	15140.0	6661.600	41548	10	October	2013
Government	United States of America	Paseo	Low	274.0	10	350	95900.0	3836.000	92064.000	71240.0	20824.000	41974	12	December	2014
Enterprise	Mexico	Paseo	Low	1138.0	10	125	142250.0	5690.000	136560.000	136560.0	0.000	41974	12	December	2014
Channel Partners	United States of America	Velo	Low	1465.0	120	12	17580.0	703.200	16876.800	4395.0	12481.800	41699	3	March	2014
Government	Canada	Velo	Low	2646.0	120	20	52920.0	2116.800	50803.200	26460.0	24343.200	41518	9	September	2013
Government	France	Velo	Low	2177.0	120	350	761950.0	30478.000	731472.000	566020.0	165452.000	41913	10	October	2014
Channel Partners	France	VTT	Low	866.0	250	12	10392.0	415.680	9976.320	2598.0	7378.320	41760	5	May	2014
Government	United States of America	VTT	Low	349.0	250	350	122150.0	4886.000	117264.000	90740.0	26524.000	41518	9	September	2013
Government	France	VTT	Low	2177.0	250	350	761950.0	30478.000	731472.000	566020.0	165452.000	41913	10	October	2014
Midmarket	Mexico	VTT	Low	1514.0	250	15	22710.0	908.400	21801.600	15140.0	6661.600	41548	10	October	2013
Government	Mexico	Amarilla	Low	1865.0	260	350	652750.0	26110.000	626640.000	484900.0	141740.000	41671	2	February	2014
Enterprise	Mexico	Amarilla	Low	1074.0	260	125	134250.0	5370.000	128880.000	128880.0	0.000	41730	4	April	2014
Government	Germany	Amarilla	Low	1907.0	260	350	667450.0	26698.000	640752.000	495820.0	144932.000	41883	9	September	2014
Midmarket	United States of America	Amarilla	Low	671.0	260	15	10065.0	402.600	9662.400	6710.0	2952.400	41548	10	October	2013
Government	Canada	Amarilla	Low	1778.0	260	350	622300.0	24892.000	597408.000	462280.0	135128.000	41609	12	December	2013
Government	Germany	Montana	Medium	1159.0	5	7	8113.0	405.650	7707.350	5795.0	1912.350	41548	10	October	2013
Government	Germany	Paseo	Medium	1372.0	10	7	9604.0	480.200	9123.800	6860.0	2263.800	41640	1	January	2014
Government	Canada	Paseo	Medium	2349.0	10	7	16443.0	822.150	15620.850	11745.0	3875.850	41518	9	September	2013
Government	Mexico	Paseo	Medium	2689.0	10	7	18823.0	941.150	17881.850	13445.0	4436.850	41913	10	October	2014
Channel Partners	Canada	Paseo	Medium	2431.0	10	12	29172.0	1458.600	27713.400	7293.0	20420.400	41974	12	December	2014
Channel Partners	Canada	Velo	Medium	2431.0	120	12	29172.0	1458.600	27713.400	7293.0	20420.400	41974	12	December	2014
Government	Mexico	VTT	Medium	2689.0	250	7	18823.0	941.150	17881.850	13445.0	4436.850	41913	10	October	2014
Government	Mexico	Amarilla	Medium	1683.0	260	7	11781.0	589.050	11191.950	8415.0	2776.950	41821	7	July	2014
Channel Partners	Mexico	Amarilla	Medium	1123.0	260	12	13476.0	673.800	12802.200	3369.0	9433.200	41852	8	August	2014
Government	Germany	Amarilla	Medium	1159.0	260	7	8113.0	405.650	7707.350	5795.0	1912.350	41548	10	October	2013
Channel Partners	France	Carretera	Medium	1865.0	3	12	22380.0	1119.000	21261.000	5595.0	15666.000	41671	2	February	2014
Channel Partners	Germany	Carretera	Medium	1116.0	3	12	13392.0	669.600	12722.400	3348.0	9374.400	41671	2	February	2014
Government	France	Carretera	Medium	1563.0	3	20	31260.0	1563.000	29697.000	15630.0	14067.000	41760	5	May	2014
Small Business	United States of America	Carretera	Medium	991.0	3	300	297300.0	14865.000	282435.000	247750.0	34685.000	41791	6	June	2014
Government	Germany	Carretera	Medium	1016.0	3	7	7112.0	355.600	6756.400	5080.0	1676.400	41579	11	November	2013
Midmarket	Mexico	Carretera	Medium	2791.0	3	15	41865.0	2093.250	39771.750	27910.0	11861.750	41944	11	November	2014
Government	United States of America	Carretera	Medium	570.0	3	7	3990.0	199.500	3790.500	2850.0	940.500	41974	12	December	2014
Government	France	Carretera	Medium	2487.0	3	7	17409.0	870.450	16538.550	12435.0	4103.550	41974	12	December	2014
Government	France	Montana	Medium	1384.5	5	350	484575.0	24228.750	460346.250	359970.0	100376.250	41640	1	January	2014
Enterprise	United States of America	Montana	Medium	3627.0	5	125	453375.0	22668.750	430706.250	435240.0	-4533.750	41821	7	July	2014
Government	Mexico	Montana	Medium	720.0	5	350	252000.0	12600.000	239400.000	187200.0	52200.000	41518	9	September	2013
Channel Partners	Germany	Montana	Medium	2342.0	5	12	28104.0	1405.200	26698.800	7026.0	19672.800	41944	11	November	2014
Small Business	Mexico	Montana	Medium	1100.0	5	300	330000.0	16500.000	313500.000	275000.0	38500.000	41609	12	December	2013
Government	France	Paseo	Medium	1303.0	10	20	26060.0	1303.000	24757.000	13030.0	11727.000	41671	2	February	2014
Enterprise	United States of America	Paseo	Medium	2992.0	10	125	374000.0	18700.000	355300.000	359040.0	-3740.000	41699	3	March	2014
Enterprise	France	Paseo	Medium	2385.0	10	125	298125.0	14906.250	283218.750	286200.0	-2981.250	41699	3	March	2014
Small Business	Mexico	Paseo	Medium	1607.0	10	300	482100.0	24105.000	457995.000	401750.0	56245.000	41730	4	April	2014
Government	United States of America	Paseo	Medium	2327.0	10	7	16289.0	814.450	15474.550	11635.0	3839.550	41760	5	May	2014
Small Business	United States of America	Paseo	Medium	991.0	10	300	297300.0	14865.000	282435.000	247750.0	34685.000	41791	6	June	2014
Government	United States of America	Paseo	Medium	602.0	10	350	210700.0	10535.000	200165.000	156520.0	43645.000	41791	6	June	2014
Midmarket	France	Paseo	Medium	2620.0	10	15	39300.0	1965.000	37335.000	26200.0	11135.000	41883	9	September	2014
Government	Canada	Paseo	Medium	1228.0	10	350	429800.0	21490.000	408310.000	319280.0	89030.000	41548	10	October	2013
Government	Canada	Paseo	Medium	1389.0	10	20	27780.0	1389.000	26391.000	13890.0	12501.000	41548	10	October	2013
Enterprise	United States of America	Paseo	Medium	861.0	10	125	107625.0	5381.250	102243.750	103320.0	-1076.250	41913	10	October	2014
Enterprise	France	Paseo	Medium	704.0	10	125	88000.0	4400.000	83600.000	84480.0	-880.000	41548	10	October	2013
Government	Canada	Paseo	Medium	1802.0	10	20	36040.0	1802.000	34238.000	18020.0	16218.000	41609	12	December	2013
Government	United States of America	Paseo	Medium	2663.0	10	20	53260.0	2663.000	50597.000	26630.0	23967.000	41974	12	December	2014
Government	France	Paseo	Medium	2136.0	10	7	14952.0	747.600	14204.400	10680.0	3524.400	41609	12	December	2013
Midmarket	Germany	Paseo	Medium	2116.0	10	15	31740.0	1587.000	30153.000	21160.0	8993.000	41609	12	December	2013
Midmarket	United States of America	Velo	Medium	555.0	120	15	8325.0	416.250	7908.750	5550.0	2358.750	41640	1	January	2014
Midmarket	Mexico	Velo	Medium	2861.0	120	15	42915.0	2145.750	40769.250	28610.0	12159.250	41640	1	January	2014
Enterprise	Germany	Velo	Medium	807.0	120	125	100875.0	5043.750	95831.250	96840.0	-1008.750	41671	2	February	2014
Government	United States of America	Velo	Medium	602.0	120	350	210700.0	10535.000	200165.000	156520.0	43645.000	41791	6	June	2014
Government	United States of America	Velo	Medium	2832.0	120	20	56640.0	2832.000	53808.000	28320.0	25488.000	41852	8	August	2014
Government	France	Velo	Medium	1579.0	120	20	31580.0	1579.000	30001.000	15790.0	14211.000	41852	8	August	2014
Enterprise	United States of America	Velo	Medium	861.0	120	125	107625.0	5381.250	102243.750	103320.0	-1076.250	41913	10	October	2014
Enterprise	France	Velo	Medium	704.0	120	125	88000.0	4400.000	83600.000	84480.0	-880.000	41548	10	October	2013
Government	France	Velo	Medium	1033.0	120	20	20660.0	1033.000	19627.000	10330.0	9297.000	41609	12	December	2013
Small Business	Germany	Velo	Medium	1250.0	120	300	375000.0	18750.000	356250.000	312500.0	43750.000	41974	12	December	2014
Government	Canada	VTT	Medium	1389.0	250	20	27780.0	1389.000	26391.000	13890.0	12501.000	41548	10	October	2013
Government	United States of America	VTT	Medium	1265.0	250	20	25300.0	1265.000	24035.000	12650.0	11385.000	41579	11	November	2013
Government	Germany	VTT	Medium	2297.0	250	20	45940.0	2297.000	43643.000	22970.0	20673.000	41579	11	November	2013
Government	United States of America	VTT	Medium	2663.0	250	20	53260.0	2663.000	50597.000	26630.0	23967.000	41974	12	December	2014
Government	United States of America	VTT	Medium	570.0	250	7	3990.0	199.500	3790.500	2850.0	940.500	41974	12	December	2014
Government	France	VTT	Medium	2487.0	250	7	17409.0	870.450	16538.550	12435.0	4103.550	41974	12	December	2014
Government	Germany	Amarilla	Medium	1350.0	260	350	472500.0	23625.000	448875.000	351000.0	97875.000	41671	2	February	2014
Government	Canada	Amarilla	Medium	552.0	260	350	193200.0	9660.000	183540.000	143520.0	40020.000	41852	8	August	2014
Government	Canada	Amarilla	Medium	1228.0	260	350	429800.0	21490.000	408310.000	319280.0	89030.000	41548	10	October	2013
Small Business	Germany	Amarilla	Medium	1250.0	260	300	375000.0	18750.000	356250.000	312500.0	43750.000	41974	12	December	2014
Midmarket	France	Paseo	Medium	3801.0	10	15	57015.0	3420.900	53594.100	38010.0	15584.100	41730	4	April	2014
Government	United States of America	Carretera	Medium	1117.5	3	20	22350.0	1341.000	21009.000	11175.0	9834.000	41640	1	January	2014
Midmarket	Canada	Carretera	Medium	2844.0	3	15	42660.0	2559.600	40100.400	28440.0	11660.400	41791	6	June	2014
Channel Partners	Mexico	Carretera	Medium	562.0	3	12	6744.0	404.640	6339.360	1686.0	4653.360	41883	9	September	2014
Channel Partners	Canada	Carretera	Medium	2299.0	3	12	27588.0	1655.280	25932.720	6897.0	19035.720	41548	10	October	2013
Midmarket	United States of America	Carretera	Medium	2030.0	3	15	30450.0	1827.000	28623.000	20300.0	8323.000	41944	11	November	2014
Government	United States of America	Carretera	Medium	263.0	3	7	1841.0	110.460	1730.540	1315.0	415.540	41579	11	November	2013
Enterprise	Germany	Carretera	Medium	887.0	3	125	110875.0	6652.500	104222.500	106440.0	-2217.500	41609	12	December	2013
Government	Mexico	Montana	Medium	980.0	5	350	343000.0	20580.000	322420.000	254800.0	67620.000	41730	4	April	2014
Government	Germany	Montana	Medium	1460.0	5	350	511000.0	30660.000	480340.000	379600.0	100740.000	41760	5	May	2014
Government	France	Montana	Medium	1403.0	5	7	9821.0	589.260	9231.740	7015.0	2216.740	41548	10	October	2013
Channel Partners	United States of America	Montana	Medium	2723.0	5	12	32676.0	1960.560	30715.440	8169.0	22546.440	41944	11	November	2014
Government	France	Paseo	Medium	1496.0	10	350	523600.0	31416.000	492184.000	388960.0	103224.000	41791	6	June	2014
Channel Partners	Canada	Paseo	Medium	2299.0	10	12	27588.0	1655.280	25932.720	6897.0	19035.720	41548	10	October	2013
Government	United States of America	Paseo	Medium	727.0	10	350	254450.0	15267.000	239183.000	189020.0	50163.000	41548	10	October	2013
Enterprise	Canada	Velo	Medium	952.0	120	125	119000.0	7140.000	111860.000	114240.0	-2380.000	41671	2	February	2014
Enterprise	United States of America	Velo	Medium	2755.0	120	125	344375.0	20662.500	323712.500	330600.0	-6887.500	41671	2	February	2014
Midmarket	Germany	Velo	Medium	1530.0	120	15	22950.0	1377.000	21573.000	15300.0	6273.000	41760	5	May	2014
Government	France	Velo	Medium	1496.0	120	350	523600.0	31416.000	492184.000	388960.0	103224.000	41791	6	June	2014
Government	Mexico	Velo	Medium	1498.0	120	7	10486.0	629.160	9856.840	7490.0	2366.840	41791	6	June	2014
Small Business	France	Velo	Medium	1221.0	120	300	366300.0	21978.000	344322.000	305250.0	39072.000	41548	10	October	2013
Government	France	Velo	Medium	2076.0	120	350	726600.0	43596.000	683004.000	539760.0	143244.000	41548	10	October	2013
Midmarket	Canada	VTT	Medium	2844.0	250	15	42660.0	2559.600	40100.400	28440.0	11660.400	41791	6	June	2014
Government	Mexico	VTT	Medium	1498.0	250	7	10486.0	629.160	9856.840	7490.0	2366.840	41791	6	June	2014
Small Business	France	VTT	Medium	1221.0	250	300	366300.0	21978.000	344322.000	305250.0	39072.000	41548	10	October	2013
Government	Mexico	VTT	Medium	1123.0	250	20	22460.0	1347.600	21112.400	11230.0	9882.400	41579	11	November	2013
Small Business	Canada	VTT	Medium	2436.0	250	300	730800.0	43848.000	686952.000	609000.0	77952.000	41609	12	December	2013
Enterprise	France	Amarilla	Medium	1987.5	260	125	248437.5	14906.250	233531.250	238500.0	-4968.750	41640	1	January	2014
Government	Mexico	Amarilla	Medium	1679.0	260	350	587650.0	35259.000	552391.000	436540.0	115851.000	41883	9	September	2014
Government	United States of America	Amarilla	Medium	727.0	260	350	254450.0	15267.000	239183.000	189020.0	50163.000	41548	10	October	2013
Government	France	Amarilla	Medium	1403.0	260	7	9821.0	589.260	9231.740	7015.0	2216.740	41548	10	October	2013
Government	France	Amarilla	Medium	2076.0	260	350	726600.0	43596.000	683004.000	539760.0	143244.000	41548	10	October	2013
Government	France	Montana	Medium	1757.0	5	20	35140.0	2108.400	33031.600	17570.0	15461.600	41548	10	October	2013
Midmarket	United States of America	Paseo	Medium	2198.0	10	15	32970.0	1978.200	30991.800	21980.0	9011.800	41852	8	August	2014
Midmarket	Germany	Paseo	Medium	1743.0	10	15	26145.0	1568.700	24576.300	17430.0	7146.300	41852	8	August	2014
Midmarket	United States of America	Paseo	Medium	1153.0	10	15	17295.0	1037.700	16257.300	11530.0	4727.300	41913	10	October	2014
Government	France	Paseo	Medium	1757.0	10	20	35140.0	2108.400	33031.600	17570.0	15461.600	41548	10	October	2013
Government	Germany	Velo	Medium	1001.0	120	20	20020.0	1201.200	18818.800	10010.0	8808.800	41852	8	August	2014
Government	Mexico	Velo	Medium	1333.0	120	7	9331.0	559.860	8771.140	6665.0	2106.140	41944	11	November	2014
Midmarket	United States of America	VTT	Medium	1153.0	250	15	17295.0	1037.700	16257.300	11530.0	4727.300	41913	10	October	2014
Channel Partners	Mexico	Carretera	Medium	727.0	3	12	8724.0	610.680	8113.320	2181.0	5932.320	41671	2	February	2014
Channel Partners	Canada	Carretera	Medium	1884.0	3	12	22608.0	1582.560	21025.440	5652.0	15373.440	41852	8	August	2014
Government	Mexico	Carretera	Medium	1834.0	3	20	36680.0	2567.600	34112.400	18340.0	15772.400	41518	9	September	2013
Channel Partners	Mexico	Montana	Medium	2340.0	5	12	28080.0	1965.600	26114.400	7020.0	19094.400	41640	1	January	2014
Channel Partners	France	Montana	Medium	2342.0	5	12	28104.0	1967.280	26136.720	7026.0	19110.720	41944	11	November	2014
Government	France	Paseo	Medium	1031.0	10	7	7217.0	505.190	6711.810	5155.0	1556.810	41518	9	September	2013
Midmarket	Canada	Velo	Medium	1262.0	120	15	18930.0	1325.100	17604.900	12620.0	4984.900	41760	5	May	2014
Government	Canada	Velo	Medium	1135.0	120	7	7945.0	556.150	7388.850	5675.0	1713.850	41791	6	June	2014
Government	United States of America	Velo	Medium	547.0	120	7	3829.0	268.030	3560.970	2735.0	825.970	41944	11	November	2014
Government	Canada	Velo	Medium	1582.0	120	7	11074.0	775.180	10298.820	7910.0	2388.820	41974	12	December	2014
Channel Partners	France	VTT	Medium	1738.5	250	12	20862.0	1460.340	19401.660	5215.5	14186.160	41730	4	April	2014
Channel Partners	Germany	VTT	Medium	2215.0	250	12	26580.0	1860.600	24719.400	6645.0	18074.400	41518	9	September	2013
Government	Canada	VTT	Medium	1582.0	250	7	11074.0	775.180	10298.820	7910.0	2388.820	41974	12	December	2014
Government	Canada	Amarilla	Medium	1135.0	260	7	7945.0	556.150	7388.850	5675.0	1713.850	41791	6	June	2014
Government	United States of America	Carretera	Medium	1761.0	3	350	616350.0	43144.500	573205.500	457860.0	115345.500	41699	3	March	2014
Small Business	France	Carretera	Medium	448.0	3	300	134400.0	9408.000	124992.000	112000.0	12992.000	41791	6	June	2014
Small Business	France	Carretera	Medium	2181.0	3	300	654300.0	45801.000	608499.000	545250.0	63249.000	41913	10	October	2014
Government	France	Montana	Medium	1976.0	5	20	39520.0	2766.400	36753.600	19760.0	16993.600	41913	10	October	2014
Small Business	France	Montana	Medium	2181.0	5	300	654300.0	45801.000	608499.000	545250.0	63249.000	41913	10	October	2014
Enterprise	Germany	Montana	Medium	2500.0	5	125	312500.0	21875.000	290625.000	300000.0	-9375.000	41579	11	November	2013
Small Business	Canada	Paseo	Medium	1702.0	10	300	510600.0	35742.000	474858.000	425500.0	49358.000	41760	5	May	2014
Small Business	France	Paseo	Medium	448.0	10	300	134400.0	9408.000	124992.000	112000.0	12992.000	41791	6	June	2014
Enterprise	Germany	Paseo	Medium	3513.0	10	125	439125.0	30738.750	408386.250	421560.0	-13173.750	41821	7	July	2014
Midmarket	France	Paseo	Medium	2101.0	10	15	31515.0	2206.050	29308.950	21010.0	8298.950	41852	8	August	2014
Midmarket	United States of America	Paseo	Medium	2931.0	10	15	43965.0	3077.550	40887.450	29310.0	11577.450	41518	9	September	2013
Government	France	Paseo	Medium	1535.0	10	20	30700.0	2149.000	28551.000	15350.0	13201.000	41883	9	September	2014
Small Business	Germany	Paseo	Medium	1123.0	10	300	336900.0	23583.000	313317.000	280750.0	32567.000	41518	9	September	2013
Small Business	Canada	Paseo	Medium	1404.0	10	300	421200.0	29484.000	391716.000	351000.0	40716.000	41579	11	November	2013
Channel Partners	Mexico	Paseo	Medium	2763.0	10	12	33156.0	2320.920	30835.080	8289.0	22546.080	41579	11	November	2013
Government	Germany	Paseo	Medium	2125.0	10	7	14875.0	1041.250	13833.750	10625.0	3208.750	41609	12	December	2013
Small Business	France	Velo	Medium	1659.0	120	300	497700.0	34839.000	462861.000	414750.0	48111.000	41821	7	July	2014
Government	Mexico	Velo	Medium	609.0	120	20	12180.0	852.600	11327.400	6090.0	5237.400	41852	8	August	2014
Enterprise	Germany	Velo	Medium	2087.0	120	125	260875.0	18261.250	242613.750	250440.0	-7826.250	41883	9	September	2014
Government	France	Velo	Medium	1976.0	120	20	39520.0	2766.400	36753.600	19760.0	16993.600	41913	10	October	2014
Government	United States of America	Velo	Medium	1421.0	120	20	28420.0	1989.400	26430.600	14210.0	12220.600	41609	12	December	2013
Small Business	United States of America	Velo	Medium	1372.0	120	300	411600.0	28812.000	382788.000	343000.0	39788.000	41974	12	December	2014
Government	Germany	Velo	Medium	588.0	120	20	11760.0	823.200	10936.800	5880.0	5056.800	41609	12	December	2013
Channel Partners	Canada	VTT	Medium	3244.5	250	12	38934.0	2725.380	36208.620	9733.5	26475.120	41640	1	January	2014
Small Business	France	VTT	Medium	959.0	250	300	287700.0	20139.000	267561.000	239750.0	27811.000	41671	2	February	2014
Small Business	Mexico	VTT	Medium	2747.0	250	300	824100.0	57687.000	766413.000	686750.0	79663.000	41671	2	February	2014
Enterprise	Canada	Amarilla	Medium	1645.0	260	125	205625.0	14393.750	191231.250	197400.0	-6168.750	41760	5	May	2014
Government	France	Amarilla	Medium	2876.0	260	350	1006600.0	70462.000	936138.000	747760.0	188378.000	41883	9	September	2014
Enterprise	Germany	Amarilla	Medium	994.0	260	125	124250.0	8697.500	115552.500	119280.0	-3727.500	41518	9	September	2013
Government	Canada	Amarilla	Medium	1118.0	260	20	22360.0	1565.200	20794.800	11180.0	9614.800	41944	11	November	2014
Small Business	United States of America	Amarilla	Medium	1372.0	260	300	411600.0	28812.000	382788.000	343000.0	39788.000	41974	12	December	2014
Government	Canada	Montana	Medium	488.0	5	7	3416.0	273.280	3142.720	2440.0	702.720	41671	2	February	2014
Government	United States of America	Montana	Medium	1282.0	5	20	25640.0	2051.200	23588.800	12820.0	10768.800	41791	6	June	2014
Government	Canada	Paseo	Medium	257.0	10	7	1799.0	143.920	1655.080	1285.0	370.080	41760	5	May	2014
Government	United States of America	Amarilla	Medium	1282.0	260	20	25640.0	2051.200	23588.800	12820.0	10768.800	41791	6	June	2014
Enterprise	Mexico	Carretera	Medium	1540.0	3	125	192500.0	15400.000	177100.000	184800.0	-7700.000	41852	8	August	2014
Midmarket	France	Carretera	Medium	490.0	3	15	7350.0	588.000	6762.000	4900.0	1862.000	41944	11	November	2014
Government	Mexico	Carretera	Medium	1362.0	3	350	476700.0	38136.000	438564.000	354120.0	84444.000	41974	12	December	2014
Midmarket	France	Montana	Medium	2501.0	5	15	37515.0	3001.200	34513.800	25010.0	9503.800	41699	3	March	2014
Government	Canada	Montana	Medium	708.0	5	20	14160.0	1132.800	13027.200	7080.0	5947.200	41791	6	June	2014
Government	Germany	Montana	Medium	645.0	5	20	12900.0	1032.000	11868.000	6450.0	5418.000	41821	7	July	2014
Small Business	France	Montana	Medium	1562.0	5	300	468600.0	37488.000	431112.000	390500.0	40612.000	41852	8	August	2014
Small Business	Canada	Montana	Medium	1283.0	5	300	384900.0	30792.000	354108.000	320750.0	33358.000	41518	9	September	2013
Midmarket	Germany	Montana	Medium	711.0	5	15	10665.0	853.200	9811.800	7110.0	2701.800	41974	12	December	2014
Enterprise	Mexico	Paseo	Medium	1114.0	10	125	139250.0	11140.000	128110.000	133680.0	-5570.000	41699	3	March	2014
Government	Germany	Paseo	Medium	1259.0	10	7	8813.0	705.040	8107.960	6295.0	1812.960	41730	4	April	2014
Government	Germany	Paseo	Medium	1095.0	10	7	7665.0	613.200	7051.800	5475.0	1576.800	41760	5	May	2014
Government	Germany	Paseo	Medium	1366.0	10	20	27320.0	2185.600	25134.400	13660.0	11474.400	41791	6	June	2014
Small Business	Mexico	Paseo	Medium	2460.0	10	300	738000.0	59040.000	678960.000	615000.0	63960.000	41791	6	June	2014
Government	United States of America	Paseo	Medium	678.0	10	7	4746.0	379.680	4366.320	3390.0	976.320	41852	8	August	2014
Government	Germany	Paseo	Medium	1598.0	10	7	11186.0	894.880	10291.120	7990.0	2301.120	41852	8	August	2014
Government	Germany	Paseo	Medium	2409.0	10	7	16863.0	1349.040	15513.960	12045.0	3468.960	41518	9	September	2013
Government	Germany	Paseo	Medium	1934.0	10	20	38680.0	3094.400	35585.600	19340.0	16245.600	41883	9	September	2014
Government	Mexico	Paseo	Medium	2993.0	10	20	59860.0	4788.800	55071.200	29930.0	25141.200	41883	9	September	2014
Government	Germany	Paseo	Medium	2146.0	10	350	751100.0	60088.000	691012.000	557960.0	133052.000	41579	11	November	2013
Government	Mexico	Paseo	Medium	1946.0	10	7	13622.0	1089.760	12532.240	9730.0	2802.240	41609	12	December	2013
Government	Mexico	Paseo	Medium	1362.0	10	350	476700.0	38136.000	438564.000	354120.0	84444.000	41974	12	December	2014
Channel Partners	Canada	Velo	Medium	598.0	120	12	7176.0	574.080	6601.920	1794.0	4807.920	41699	3	March	2014
Government	United States of America	Velo	Medium	2907.0	120	7	20349.0	1627.920	18721.080	14535.0	4186.080	41791	6	June	2014
Government	Germany	Velo	Medium	2338.0	120	7	16366.0	1309.280	15056.720	11690.0	3366.720	41791	6	June	2014
Small Business	France	Velo	Medium	386.0	120	300	115800.0	9264.000	106536.000	96500.0	10036.000	41579	11	November	2013
Small Business	Mexico	Velo	Medium	635.0	120	300	190500.0	15240.000	175260.000	158750.0	16510.000	41974	12	December	2014
Government	France	VTT	Medium	574.5	250	350	201075.0	16086.000	184989.000	149370.0	35619.000	41730	4	April	2014
Government	Germany	VTT	Medium	2338.0	250	7	16366.0	1309.280	15056.720	11690.0	3366.720	41791	6	June	2014
Government	France	VTT	Medium	381.0	250	350	133350.0	10668.000	122682.000	99060.0	23622.000	41852	8	August	2014
Government	Germany	VTT	Medium	422.0	250	350	147700.0	11816.000	135884.000	109720.0	26164.000	41852	8	August	2014
Small Business	Canada	VTT	Medium	2134.0	250	300	640200.0	51216.000	588984.000	533500.0	55484.000	41883	9	September	2014
Small Business	United States of America	VTT	Medium	808.0	250	300	242400.0	19392.000	223008.000	202000.0	21008.000	41609	12	December	2013
Government	Canada	Amarilla	Medium	708.0	260	20	14160.0	1132.800	13027.200	7080.0	5947.200	41791	6	June	2014
Government	United States of America	Amarilla	Medium	2907.0	260	7	20349.0	1627.920	18721.080	14535.0	4186.080	41791	6	June	2014
Government	Germany	Amarilla	Medium	1366.0	260	20	27320.0	2185.600	25134.400	13660.0	11474.400	41791	6	June	2014
Small Business	Mexico	Amarilla	Medium	2460.0	260	300	738000.0	59040.000	678960.000	615000.0	63960.000	41791	6	June	2014
Government	Germany	Amarilla	Medium	1520.0	260	20	30400.0	2432.000	27968.000	15200.0	12768.000	41944	11	November	2014
Midmarket	Germany	Amarilla	Medium	711.0	260	15	10665.0	853.200	9811.800	7110.0	2701.800	41974	12	December	2014
Channel Partners	Mexico	Amarilla	Medium	1375.0	260	12	16500.0	1320.000	15180.000	4125.0	11055.000	41609	12	December	2013
Small Business	Mexico	Amarilla	Medium	635.0	260	300	190500.0	15240.000	175260.000	158750.0	16510.000	41974	12	December	2014
Government	United States of America	VTT	Medium	436.5	250	20	8730.0	698.400	8031.600	4365.0	3666.600	41821	7	July	2014
Small Business	Canada	Carretera	Medium	1094.0	3	300	328200.0	29538.000	298662.000	273500.0	25162.000	41791	6	June	2014
Channel Partners	Mexico	Carretera	Medium	367.0	3	12	4404.0	396.360	4007.640	1101.0	2906.640	41548	10	October	2013
Small Business	Canada	Montana	Medium	3802.5	5	300	1140750.0	102667.500	1038082.500	950625.0	87457.500	41730	4	April	2014
Government	France	Montana	Medium	1666.0	5	350	583100.0	52479.000	530621.000	433160.0	97461.000	41760	5	May	2014
Small Business	France	Montana	Medium	322.0	5	300	96600.0	8694.000	87906.000	80500.0	7406.000	41518	9	September	2013
Channel Partners	Canada	Montana	Medium	2321.0	5	12	27852.0	2506.680	25345.320	6963.0	18382.320	41944	11	November	2014
Enterprise	France	Montana	Medium	1857.0	5	125	232125.0	20891.250	211233.750	222840.0	-11606.250	41579	11	November	2013
Government	Canada	Montana	Medium	1611.0	5	7	11277.0	1014.930	10262.070	8055.0	2207.070	41609	12	December	2013
Enterprise	United States of America	Montana	Medium	2797.0	5	125	349625.0	31466.250	318158.750	335640.0	-17481.250	41974	12	December	2014
Small Business	Germany	Montana	Medium	334.0	5	300	100200.0	9018.000	91182.000	83500.0	7682.000	41609	12	December	2013
Small Business	Mexico	Paseo	Medium	2565.0	10	300	769500.0	69255.000	700245.000	641250.0	58995.000	41640	1	January	2014
Government	Mexico	Paseo	Medium	2417.0	10	350	845950.0	76135.500	769814.500	628420.0	141394.500	41640	1	January	2014
Midmarket	United States of America	Paseo	Medium	3675.0	10	15	55125.0	4961.250	50163.750	36750.0	13413.750	41730	4	April	2014
Small Business	Canada	Paseo	Medium	1094.0	10	300	328200.0	29538.000	298662.000	273500.0	25162.000	41791	6	June	2014
Midmarket	France	Paseo	Medium	1227.0	10	15	18405.0	1656.450	16748.550	12270.0	4478.550	41913	10	October	2014
Channel Partners	Mexico	Paseo	Medium	367.0	10	12	4404.0	396.360	4007.640	1101.0	2906.640	41548	10	October	2013
Small Business	France	Paseo	Medium	1324.0	10	300	397200.0	35748.000	361452.000	331000.0	30452.000	41944	11	November	2014
Channel Partners	Germany	Paseo	Medium	1775.0	10	12	21300.0	1917.000	19383.000	5325.0	14058.000	41579	11	November	2013
Enterprise	United States of America	Paseo	Medium	2797.0	10	125	349625.0	31466.250	318158.750	335640.0	-17481.250	41974	12	December	2014
Midmarket	Mexico	Velo	Medium	245.0	120	15	3675.0	330.750	3344.250	2450.0	894.250	41760	5	May	2014
Small Business	Canada	Velo	Medium	3793.5	120	300	1138050.0	102424.500	1035625.500	948375.0	87250.500	41821	7	July	2014
Government	Germany	Velo	Medium	1307.0	120	350	457450.0	41170.500	416279.500	339820.0	76459.500	41821	7	July	2014
Enterprise	Canada	Velo	Medium	567.0	120	125	70875.0	6378.750	64496.250	68040.0	-3543.750	41883	9	September	2014
Enterprise	Mexico	Velo	Medium	2110.0	120	125	263750.0	23737.500	240012.500	253200.0	-13187.500	41883	9	September	2014
Government	Canada	Velo	Medium	1269.0	120	350	444150.0	39973.500	404176.500	329940.0	74236.500	41913	10	October	2014
Channel Partners	United States of America	VTT	Medium	1956.0	250	12	23472.0	2112.480	21359.520	5868.0	15491.520	41640	1	January	2014
Small Business	Germany	VTT	Medium	2659.0	250	300	797700.0	71793.000	725907.000	664750.0	61157.000	41671	2	February	2014
Government	United States of America	VTT	Medium	1351.5	250	350	473025.0	42572.250	430452.750	351390.0	79062.750	41730	4	April	2014
Channel Partners	Germany	VTT	Medium	880.0	250	12	10560.0	950.400	9609.600	2640.0	6969.600	41760	5	May	2014
Small Business	United States of America	VTT	Medium	1867.0	250	300	560100.0	50409.000	509691.000	466750.0	42941.000	41883	9	September	2014
Channel Partners	France	VTT	Medium	2234.0	250	12	26808.0	2412.720	24395.280	6702.0	17693.280	41518	9	September	2013
Midmarket	France	VTT	Medium	1227.0	250	15	18405.0	1656.450	16748.550	12270.0	4478.550	41913	10	October	2014
Enterprise	Mexico	VTT	Medium	877.0	250	125	109625.0	9866.250	99758.750	105240.0	-5481.250	41944	11	November	2014
Government	United States of America	Amarilla	Medium	2071.0	260	350	724850.0	65236.500	659613.500	538460.0	121153.500	41883	9	September	2014
Government	Canada	Amarilla	Medium	1269.0	260	350	444150.0	39973.500	404176.500	329940.0	74236.500	41913	10	October	2014
Midmarket	Germany	Amarilla	Medium	970.0	260	15	14550.0	1309.500	13240.500	9700.0	3540.500	41579	11	November	2013
Government	Mexico	Amarilla	Medium	1694.0	260	20	33880.0	3049.200	30830.800	16940.0	13890.800	41944	11	November	2014
Government	Germany	Carretera	Medium	663.0	3	20	13260.0	1193.400	12066.600	6630.0	5436.600	41760	5	May	2014
Government	Canada	Carretera	Medium	819.0	3	7	5733.0	515.970	5217.030	4095.0	1122.030	41821	7	July	2014
Channel Partners	Germany	Carretera	Medium	1580.0	3	12	18960.0	1706.400	17253.600	4740.0	12513.600	41883	9	September	2014
Government	Mexico	Carretera	Medium	521.0	3	7	3647.0	328.230	3318.770	2605.0	713.770	41974	12	December	2014
Government	United States of America	Paseo	Medium	973.0	10	20	19460.0	1751.400	17708.600	9730.0	7978.600	41699	3	March	2014
Government	Mexico	Paseo	Medium	1038.0	10	20	20760.0	1868.400	18891.600	10380.0	8511.600	41791	6	June	2014
Government	Germany	Paseo	Medium	360.0	10	7	2520.0	226.800	2293.200	1800.0	493.200	41913	10	October	2014
Channel Partners	France	Velo	Medium	1967.0	120	12	23604.0	2124.360	21479.640	5901.0	15578.640	41699	3	March	2014
Midmarket	Mexico	Velo	Medium	2628.0	120	15	39420.0	3547.800	35872.200	26280.0	9592.200	41730	4	April	2014
Government	Germany	VTT	Medium	360.0	250	7	2520.0	226.800	2293.200	1800.0	493.200	41913	10	October	2014
Government	France	VTT	Medium	2682.0	250	20	53640.0	4827.600	48812.400	26820.0	21992.400	41579	11	November	2013
Government	Mexico	VTT	Medium	521.0	250	7	3647.0	328.230	3318.770	2605.0	713.770	41974	12	December	2014
Government	Mexico	Amarilla	Medium	1038.0	260	20	20760.0	1868.400	18891.600	10380.0	8511.600	41791	6	June	2014
Midmarket	Canada	Amarilla	Medium	1630.5	260	15	24457.5	2201.175	22256.325	16305.0	5951.325	41821	7	July	2014
Channel Partners	France	Amarilla	Medium	306.0	260	12	3672.0	330.480	3341.520	918.0	2423.520	41609	12	December	2013
Channel Partners	United States of America	Carretera	High	386.0	3	12	4632.0	463.200	4168.800	1158.0	3010.800	41548	10	October	2013
Government	United States of America	Montana	High	2328.0	5	7	16296.0	1629.600	14666.400	11640.0	3026.400	41883	9	September	2014
Channel Partners	United States of America	Paseo	High	386.0	10	12	4632.0	463.200	4168.800	1158.0	3010.800	41548	10	October	2013
Enterprise	United States of America	Carretera	High	3445.5	3	125	430687.5	43068.750	387618.750	413460.0	-25841.250	41730	4	April	2014
Enterprise	France	Carretera	High	1482.0	3	125	185250.0	18525.000	166725.000	177840.0	-11115.000	41609	12	December	2013
Government	United States of America	Montana	High	2313.0	5	350	809550.0	80955.000	728595.000	601380.0	127215.000	41760	5	May	2014
Enterprise	United States of America	Montana	High	1804.0	5	125	225500.0	22550.000	202950.000	216480.0	-13530.000	41579	11	November	2013
Midmarket	France	Montana	High	2072.0	5	15	31080.0	3108.000	27972.000	20720.0	7252.000	41974	12	December	2014
Government	France	Paseo	High	1954.0	10	20	39080.0	3908.000	35172.000	19540.0	15632.000	41699	3	March	2014
Small Business	Mexico	Paseo	High	591.0	10	300	177300.0	17730.000	159570.000	147750.0	11820.000	41760	5	May	2014
Midmarket	France	Paseo	High	2167.0	10	15	32505.0	3250.500	29254.500	21670.0	7584.500	41548	10	October	2013
Government	Germany	Paseo	High	241.0	10	20	4820.0	482.000	4338.000	2410.0	1928.000	41913	10	October	2014
Midmarket	Germany	Velo	High	681.0	120	15	10215.0	1021.500	9193.500	6810.0	2383.500	41640	1	January	2014
Midmarket	Germany	Velo	High	510.0	120	15	7650.0	765.000	6885.000	5100.0	1785.000	41730	4	April	2014
Midmarket	United States of America	Velo	High	790.0	120	15	11850.0	1185.000	10665.000	7900.0	2765.000	41760	5	May	2014
Government	France	Velo	High	639.0	120	350	223650.0	22365.000	201285.000	166140.0	35145.000	41821	7	July	2014
Enterprise	United States of America	Velo	High	1596.0	120	125	199500.0	19950.000	179550.000	191520.0	-11970.000	41883	9	September	2014
Small Business	United States of America	Velo	High	2294.0	120	300	688200.0	68820.000	619380.000	573500.0	45880.000	41548	10	October	2013
Government	Germany	Velo	High	241.0	120	20	4820.0	482.000	4338.000	2410.0	1928.000	41913	10	October	2014
Government	Germany	Velo	High	2665.0	120	7	18655.0	1865.500	16789.500	13325.0	3464.500	41944	11	November	2014
Enterprise	Canada	Velo	High	1916.0	120	125	239500.0	23950.000	215550.000	229920.0	-14370.000	41609	12	December	2013
Small Business	France	Velo	High	853.0	120	300	255900.0	25590.000	230310.000	213250.0	17060.000	41974	12	December	2014
Enterprise	Mexico	VTT	High	341.0	250	125	42625.0	4262.500	38362.500	40920.0	-2557.500	41760	5	May	2014
Midmarket	Mexico	VTT	High	641.0	250	15	9615.0	961.500	8653.500	6410.0	2243.500	41821	7	July	2014
Government	United States of America	VTT	High	2807.0	250	350	982450.0	98245.000	884205.000	729820.0	154385.000	41852	8	August	2014
Small Business	Mexico	VTT	High	432.0	250	300	129600.0	12960.000	116640.000	108000.0	8640.000	41883	9	September	2014
Small Business	United States of America	VTT	High	2294.0	250	300	688200.0	68820.000	619380.000	573500.0	45880.000	41548	10	October	2013
Midmarket	France	VTT	High	2167.0	250	15	32505.0	3250.500	29254.500	21670.0	7584.500	41548	10	October	2013
Enterprise	Canada	VTT	High	2529.0	250	125	316125.0	31612.500	284512.500	303480.0	-18967.500	41944	11	November	2014
Government	Germany	VTT	High	1870.0	250	350	654500.0	65450.000	589050.000	486200.0	102850.000	41609	12	December	2013
Enterprise	United States of America	Amarilla	High	579.0	260	125	72375.0	7237.500	65137.500	69480.0	-4342.500	41640	1	January	2014
Government	Canada	Amarilla	High	2240.0	260	350	784000.0	78400.000	705600.000	582400.0	123200.000	41671	2	February	2014
Small Business	United States of America	Amarilla	High	2993.0	260	300	897900.0	89790.000	808110.000	748250.0	59860.000	41699	3	March	2014
Channel Partners	Canada	Amarilla	High	3520.5	260	12	42246.0	4224.600	38021.400	10561.5	27459.900	41730	4	April	2014
Government	Mexico	Amarilla	High	2039.0	260	20	40780.0	4078.000	36702.000	20390.0	16312.000	41760	5	May	2014
Channel Partners	Germany	Amarilla	High	2574.0	260	12	30888.0	3088.800	27799.200	7722.0	20077.200	41852	8	August	2014
Government	Canada	Amarilla	High	707.0	260	350	247450.0	24745.000	222705.000	183820.0	38885.000	41883	9	September	2014
Midmarket	France	Amarilla	High	2072.0	260	15	31080.0	3108.000	27972.000	20720.0	7252.000	41974	12	December	2014
Small Business	France	Amarilla	High	853.0	260	300	255900.0	25590.000	230310.000	213250.0	17060.000	41974	12	December	2014
Channel Partners	France	Carretera	High	1198.0	3	12	14376.0	1581.360	12794.640	3594.0	9200.640	41548	10	October	2013
Government	France	Paseo	High	2532.0	10	7	17724.0	1949.640	15774.360	12660.0	3114.360	41730	4	April	2014
Channel Partners	France	Paseo	High	1198.0	10	12	14376.0	1581.360	12794.640	3594.0	9200.640	41548	10	October	2013
Midmarket	Canada	Velo	High	384.0	120	15	5760.0	633.600	5126.400	3840.0	1286.400	41640	1	January	2014
Channel Partners	Germany	Velo	High	472.0	120	12	5664.0	623.040	5040.960	1416.0	3624.960	41913	10	October	2014
Government	United States of America	VTT	High	1579.0	250	7	11053.0	1215.830	9837.170	7895.0	1942.170	41699	3	March	2014
Channel Partners	Mexico	VTT	High	1005.0	250	12	12060.0	1326.600	10733.400	3015.0	7718.400	41518	9	September	2013
Midmarket	United States of America	Amarilla	High	3199.5	260	15	47992.5	5279.175	42713.325	31995.0	10718.325	41821	7	July	2014
Channel Partners	Germany	Amarilla	High	472.0	260	12	5664.0	623.040	5040.960	1416.0	3624.960	41913	10	October	2014
Channel Partners	Canada	Carretera	High	1937.0	3	12	23244.0	2556.840	20687.160	5811.0	14876.160	41671	2	February	2014
Government	Germany	Carretera	High	792.0	3	350	277200.0	30492.000	246708.000	205920.0	40788.000	41699	3	March	2014
Small Business	Germany	Carretera	High	2811.0	3	300	843300.0	92763.000	750537.000	702750.0	47787.000	41821	7	July	2014
Enterprise	France	Carretera	High	2441.0	3	125	305125.0	33563.750	271561.250	292920.0	-21358.750	41913	10	October	2014
Midmarket	Canada	Carretera	High	1560.0	3	15	23400.0	2574.000	20826.000	15600.0	5226.000	41579	11	November	2013
Government	Mexico	Carretera	High	2706.0	3	7	18942.0	2083.620	16858.380	13530.0	3328.380	41579	11	November	2013
Government	Germany	Montana	High	766.0	5	350	268100.0	29491.000	238609.000	199160.0	39449.000	41640	1	January	2014
Government	Germany	Montana	High	2992.0	5	20	59840.0	6582.400	53257.600	29920.0	23337.600	41548	10	October	2013
Midmarket	Mexico	Montana	High	2157.0	5	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Small Business	Canada	Paseo	High	873.0	10	300	261900.0	28809.000	233091.000	218250.0	14841.000	41640	1	January	2014
Government	Mexico	Paseo	High	1122.0	10	20	22440.0	2468.400	19971.600	11220.0	8751.600	41699	3	March	2014
Government	Canada	Paseo	High	2104.5	10	350	736575.0	81023.250	655551.750	547170.0	108381.750	41821	7	July	2014
Channel Partners	Canada	Paseo	High	4026.0	10	12	48312.0	5314.320	42997.680	12078.0	30919.680	41821	7	July	2014
Channel Partners	France	Paseo	High	2425.5	10	12	29106.0	3201.660	25904.340	7276.5	18627.840	41821	7	July	2014
Government	Canada	Paseo	High	2394.0	10	20	47880.0	5266.800	42613.200	23940.0	18673.200	41852	8	August	2014
Midmarket	Mexico	Paseo	High	1984.0	10	15	29760.0	3273.600	26486.400	19840.0	6646.400	41852	8	August	2014
Enterprise	France	Paseo	High	2441.0	10	125	305125.0	33563.750	271561.250	292920.0	-21358.750	41913	10	October	2014
Government	Germany	Paseo	High	2992.0	10	20	59840.0	6582.400	53257.600	29920.0	23337.600	41548	10	October	2013
Small Business	Canada	Paseo	High	1366.0	10	300	409800.0	45078.000	364722.000	341500.0	23222.000	41944	11	November	2014
Government	France	Velo	High	2805.0	120	20	56100.0	6171.000	49929.000	28050.0	21879.000	41518	9	September	2013
Midmarket	Mexico	Velo	High	655.0	120	15	9825.0	1080.750	8744.250	6550.0	2194.250	41518	9	September	2013
Government	Mexico	Velo	High	344.0	120	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Government	Canada	Velo	High	1808.0	120	7	12656.0	1392.160	11263.840	9040.0	2223.840	41944	11	November	2014
Channel Partners	France	VTT	High	1734.0	250	12	20808.0	2288.880	18519.120	5202.0	13317.120	41640	1	January	2014
Enterprise	Mexico	VTT	High	554.0	250	125	69250.0	7617.500	61632.500	66480.0	-4847.500	41640	1	January	2014
Government	Canada	VTT	High	2935.0	250	20	58700.0	6457.000	52243.000	29350.0	22893.000	41579	11	November	2013
Enterprise	Germany	Amarilla	High	3165.0	260	125	395625.0	43518.750	352106.250	379800.0	-27693.750	41640	1	January	2014
Government	Mexico	Amarilla	High	2629.0	260	20	52580.0	5783.800	46796.200	26290.0	20506.200	41640	1	January	2014
Enterprise	France	Amarilla	High	1433.0	260	125	179125.0	19703.750	159421.250	171960.0	-12538.750	41760	5	May	2014
Enterprise	Mexico	Amarilla	High	947.0	260	125	118375.0	13021.250	105353.750	113640.0	-8286.250	41518	9	September	2013
Government	Mexico	Amarilla	High	344.0	260	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Midmarket	Mexico	Amarilla	High	2157.0	260	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Government	United States of America	Paseo	High	380.0	10	7	2660.0	292.600	2367.400	1900.0	467.400	41518	9	September	2013
Government	Mexico	Carretera	High	886.0	3	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Canada	Carretera	High	2416.0	3	125	302000.0	36240.000	265760.000	289920.0	-24160.000	41518	9	September	2013
Enterprise	Mexico	Carretera	High	2156.0	3	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Midmarket	Canada	Carretera	High	2689.0	3	15	40335.0	4840.200	35494.800	26890.0	8604.800	41944	11	November	2014
Midmarket	United States of America	Montana	High	677.0	5	15	10155.0	1218.600	8936.400	6770.0	2166.400	41699	3	March	2014
Small Business	France	Montana	High	1773.0	5	300	531900.0	63828.000	468072.000	443250.0	24822.000	41730	4	April	2014
Government	Mexico	Montana	High	2420.0	5	7	16940.0	2032.800	14907.200	12100.0	2807.200	41883	9	September	2014
Government	Canada	Montana	High	2734.0	5	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Government	Mexico	Montana	High	1715.0	5	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Small Business	France	Montana	High	1186.0	5	300	355800.0	42696.000	313104.000	296500.0	16604.000	41609	12	December	2013
Small Business	United States of America	Paseo	High	3495.0	10	300	1048500.0	125820.000	922680.000	873750.0	48930.000	41640	1	January	2014
Government	Mexico	Paseo	High	886.0	10	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Mexico	Paseo	High	2156.0	10	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Government	Mexico	Paseo	High	905.0	10	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Government	Mexico	Paseo	High	1715.0	10	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Government	France	Paseo	High	1594.0	10	350	557900.0	66948.000	490952.000	414440.0	76512.000	41944	11	November	2014
Small Business	Germany	Paseo	High	1359.0	10	300	407700.0	48924.000	358776.000	339750.0	19026.000	41944	11	November	2014
Small Business	Mexico	Paseo	High	2150.0	10	300	645000.0	77400.000	567600.000	537500.0	30100.000	41944	11	November	2014
Government	Mexico	Paseo	High	1197.0	10	350	418950.0	50274.000	368676.000	311220.0	57456.000	41944	11	November	2014
Midmarket	Mexico	Paseo	High	380.0	10	15	5700.0	684.000	5016.000	3800.0	1216.000	41609	12	December	2013
Government	Mexico	Paseo	High	1233.0	10	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	Mexico	Velo	High	1395.0	120	350	488250.0	58590.000	429660.000	362700.0	66960.000	41821	7	July	2014
Government	United States of America	Velo	High	986.0	120	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Government	Mexico	Velo	High	905.0	120	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Channel Partners	Canada	VTT	High	2109.0	250	12	25308.0	3036.960	22271.040	6327.0	15944.040	41760	5	May	2014
Midmarket	France	VTT	High	3874.5	250	15	58117.5	6974.100	51143.400	38745.0	12398.400	41821	7	July	2014
Government	Canada	VTT	High	623.0	250	350	218050.0	26166.000	191884.000	161980.0	29904.000	41518	9	September	2013
Government	United States of America	VTT	High	986.0	250	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Enterprise	United States of America	VTT	High	2387.0	250	125	298375.0	35805.000	262570.000	286440.0	-23870.000	41944	11	November	2014
Government	Mexico	VTT	High	1233.0	250	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	United States of America	Amarilla	High	270.0	260	350	94500.0	11340.000	83160.000	70200.0	12960.000	41671	2	February	2014
Government	France	Amarilla	High	3421.5	260	7	23950.5	2874.060	21076.440	17107.5	3968.940	41821	7	July	2014
Government	Canada	Amarilla	High	2734.0	260	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Midmarket	United States of America	Amarilla	High	2548.0	260	15	38220.0	4586.400	33633.600	25480.0	8153.600	41579	11	November	2013
Government	France	Carretera	High	2521.5	3	20	50430.0	6051.600	44378.400	25215.0	19163.400	41640	1	January	2014
Channel Partners	Mexico	Montana	High	2661.0	5	12	31932.0	3831.840	28100.160	7983.0	20117.160	41760	5	May	2014
Government	Germany	Paseo	High	1531.0	10	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Government	France	VTT	High	1491.0	250	7	10437.0	1252.440	9184.560	7455.0	1729.560	41699	3	March	2014
Government	Germany	VTT	High	1531.0	250	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Channel Partners	Canada	Amarilla	High	2761.0	260	12	33132.0	3975.840	29156.160	8283.0	20873.160	41518	9	September	2013
Midmarket	United States of America	Carretera	High	2567.0	3	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Midmarket	United States of America	VTT	High	2567.0	250	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Government	Canada	Carretera	High	923.0	3	350	323050.0	41996.500	281053.500	239980.0	41073.500	41699	3	March	2014
Government	France	Carretera	High	1790.0	3	350	626500.0	81445.000	545055.000	465400.0	79655.000	41699	3	March	2014
Government	Germany	Carretera	High	442.0	3	20	8840.0	1149.200	7690.800	4420.0	3270.800	41518	9	September	2013
Government	United States of America	Montana	High	982.5	5	350	343875.0	44703.750	299171.250	255450.0	43721.250	41640	1	January	2014
Government	United States of America	Montana	High	1298.0	5	7	9086.0	1181.180	7904.820	6490.0	1414.820	41671	2	February	2014
Channel Partners	Mexico	Montana	High	604.0	5	12	7248.0	942.240	6305.760	1812.0	4493.760	41791	6	June	2014
Government	Mexico	Montana	High	2255.0	5	20	45100.0	5863.000	39237.000	22550.0	16687.000	41821	7	July	2014
Government	Canada	Montana	High	1249.0	5	20	24980.0	3247.400	21732.600	12490.0	9242.600	41913	10	October	2014
Government	United States of America	Paseo	High	1438.5	10	7	10069.5	1309.035	8760.465	7192.5	1567.965	41640	1	January	2014
Small Business	Germany	Paseo	High	807.0	10	300	242100.0	31473.000	210627.000	201750.0	8877.000	41640	1	January	2014
Government	United States of America	Paseo	High	2641.0	10	20	52820.0	6866.600	45953.400	26410.0	19543.400	41671	2	February	2014
Government	Germany	Paseo	High	2708.0	10	20	54160.0	7040.800	47119.200	27080.0	20039.200	41671	2	February	2014
Government	Canada	Paseo	High	2632.0	10	350	921200.0	119756.000	801444.000	684320.0	117124.000	41791	6	June	2014
Enterprise	Canada	Paseo	High	1583.0	10	125	197875.0	25723.750	172151.250	189960.0	-17808.750	41791	6	June	2014
Channel Partners	Mexico	Paseo	High	571.0	10	12	6852.0	890.760	5961.240	1713.0	4248.240	41821	7	July	2014
Government	France	Paseo	High	2696.0	10	7	18872.0	2453.360	16418.640	13480.0	2938.640	41852	8	August	2014
Midmarket	Canada	Paseo	High	1565.0	10	15	23475.0	3051.750	20423.250	15650.0	4773.250	41913	10	October	2014
Government	Canada	Paseo	High	1249.0	10	20	24980.0	3247.400	21732.600	12490.0	9242.600	41913	10	October	2014
Government	Germany	Paseo	High	357.0	10	350	124950.0	16243.500	108706.500	92820.0	15886.500	41944	11	November	2014
Channel Partners	Germany	Paseo	High	1013.0	10	12	12156.0	1580.280	10575.720	3039.0	7536.720	41974	12	December	2014
Midmarket	France	Velo	High	3997.5	120	15	59962.5	7795.125	52167.375	39975.0	12192.375	41640	1	January	2014
Government	Canada	Velo	High	2632.0	120	350	921200.0	119756.000	801444.000	684320.0	117124.000	41791	6	June	2014
Government	France	Velo	High	1190.0	120	7	8330.0	1082.900	7247.100	5950.0	1297.100	41791	6	June	2014
Channel Partners	Mexico	Velo	High	604.0	120	12	7248.0	942.240	6305.760	1812.0	4493.760	41791	6	June	2014
Midmarket	Germany	Velo	High	660.0	120	15	9900.0	1287.000	8613.000	6600.0	2013.000	41518	9	September	2013
Channel Partners	Mexico	Velo	High	410.0	120	12	4920.0	639.600	4280.400	1230.0	3050.400	41913	10	October	2014
Small Business	Mexico	Velo	High	2605.0	120	300	781500.0	101595.000	679905.000	651250.0	28655.000	41579	11	November	2013
Channel Partners	Germany	Velo	High	1013.0	120	12	12156.0	1580.280	10575.720	3039.0	7536.720	41974	12	December	2014
Enterprise	Canada	VTT	High	1583.0	250	125	197875.0	25723.750	172151.250	189960.0	-17808.750	41791	6	June	2014
Midmarket	Canada	VTT	High	1565.0	250	15	23475.0	3051.750	20423.250	15650.0	4773.250	41913	10	October	2014
Enterprise	Canada	Amarilla	High	1659.0	260	125	207375.0	26958.750	180416.250	199080.0	-18663.750	41640	1	January	2014
Government	France	Amarilla	High	1190.0	260	7	8330.0	1082.900	7247.100	5950.0	1297.100	41791	6	June	2014
Channel Partners	Mexico	Amarilla	High	410.0	260	12	4920.0	639.600	4280.400	1230.0	3050.400	41913	10	October	2014
Channel Partners	Germany	Amarilla	High	1770.0	260	12	21240.0	2761.200	18478.800	5310.0	13168.800	41609	12	December	2013
Government	Mexico	Carretera	High	2579.0	3	20	51580.0	7221.200	44358.800	25790.0	18568.800	41730	4	April	2014
Government	United States of America	Carretera	High	1743.0	3	20	34860.0	4880.400	29979.600	17430.0	12549.600	41760	5	May	2014
Government	United States of America	Carretera	High	2996.0	3	7	20972.0	2936.080	18035.920	14980.0	3055.920	41548	10	October	2013
Government	Germany	Carretera	High	280.0	3	7	1960.0	274.400	1685.600	1400.0	285.600	41974	12	December	2014
Government	France	Montana	High	293.0	5	7	2051.0	287.140	1763.860	1465.0	298.860	41671	2	February	2014
Government	United States of America	Montana	High	2996.0	5	7	20972.0	2936.080	18035.920	14980.0	3055.920	41548	10	October	2013
Midmarket	Germany	Paseo	High	278.0	10	15	4170.0	583.800	3586.200	2780.0	806.200	41671	2	February	2014
Government	Canada	Paseo	High	2428.0	10	20	48560.0	6798.400	41761.600	24280.0	17481.600	41699	3	March	2014
Midmarket	United States of America	Paseo	High	1767.0	10	15	26505.0	3710.700	22794.300	17670.0	5124.300	41883	9	September	2014
Channel Partners	France	Paseo	High	1393.0	10	12	16716.0	2340.240	14375.760	4179.0	10196.760	41913	10	October	2014
Government	Germany	VTT	High	280.0	250	7	1960.0	274.400	1685.600	1400.0	285.600	41974	12	December	2014
Channel Partners	France	Amarilla	High	1393.0	260	12	16716.0	2340.240	14375.760	4179.0	10196.760	41913	10	October	2014
Channel Partners	United States of America	Amarilla	High	2015.0	260	12	24180.0	3385.200	20794.800	6045.0	14749.800	41609	12	December	2013
Small Business	Mexico	Carretera	High	801.0	3	300	240300.0	33642.000	206658.000	200250.0	6408.000	41821	7	July	2014
Enterprise	France	Carretera	High	1023.0	3	125	127875.0	17902.500	109972.500	122760.0	-12787.500	41518	9	September	2013
Small Business	Canada	Carretera	High	1496.0	3	300	448800.0	62832.000	385968.000	374000.0	11968.000	41913	10	October	2014
Small Business	United States of America	Carretera	High	1010.0	3	300	303000.0	42420.000	260580.000	252500.0	8080.000	41913	10	October	2014
Midmarket	Germany	Carretera	High	1513.0	3	15	22695.0	3177.300	19517.700	15130.0	4387.700	41944	11	November	2014
Midmarket	Canada	Carretera	High	2300.0	3	15	34500.0	4830.000	29670.000	23000.0	6670.000	41974	12	December	2014
Enterprise	Mexico	Carretera	High	2821.0	3	125	352625.0	49367.500	303257.500	338520.0	-35262.500	41609	12	December	2013
Government	Canada	Montana	High	2227.5	5	350	779625.0	109147.500	670477.500	579150.0	91327.500	41640	1	January	2014
Government	Germany	Montana	High	1199.0	5	350	419650.0	58751.000	360899.000	311740.0	49159.000	41730	4	April	2014
Government	Canada	Montana	High	200.0	5	350	70000.0	9800.000	60200.000	52000.0	8200.000	41760	5	May	2014
Government	Canada	Montana	High	388.0	5	7	2716.0	380.240	2335.760	1940.0	395.760	41883	9	September	2014
Government	Mexico	Montana	High	1727.0	5	7	12089.0	1692.460	10396.540	8635.0	1761.540	41548	10	October	2013
Midmarket	Canada	Montana	High	2300.0	5	15	34500.0	4830.000	29670.000	23000.0	6670.000	41974	12	December	2014
Government	Mexico	Paseo	High	260.0	10	20	5200.0	728.000	4472.000	2600.0	1872.000	41671	2	February	2014
Midmarket	Canada	Paseo	High	2470.0	10	15	37050.0	5187.000	31863.000	24700.0	7163.000	41518	9	September	2013
Midmarket	Canada	Paseo	High	1743.0	10	15	26145.0	3660.300	22484.700	17430.0	5054.700	41548	10	October	2013
Channel Partners	United States of America	Paseo	High	2914.0	10	12	34968.0	4895.520	30072.480	8742.0	21330.480	41913	10	October	2014
Government	France	Paseo	High	1731.0	10	7	12117.0	1696.380	10420.620	8655.0	1765.620	41913	10	October	2014
Government	Canada	Paseo	High	700.0	10	350	245000.0	34300.000	210700.000	182000.0	28700.000	41944	11	November	2014
Channel Partners	Canada	Paseo	High	2222.0	10	12	26664.0	3732.960	22931.040	6666.0	16265.040	41579	11	November	2013
Government	United States of America	Paseo	High	1177.0	10	350	411950.0	57673.000	354277.000	306020.0	48257.000	41944	11	November	2014
Government	France	Paseo	High	1922.0	10	350	672700.0	94178.000	578522.000	499720.0	78802.000	41579	11	November	2013
Enterprise	Mexico	Velo	High	1575.0	120	125	196875.0	27562.500	169312.500	189000.0	-19687.500	41671	2	February	2014
Government	United States of America	Velo	High	606.0	120	20	12120.0	1696.800	10423.200	6060.0	4363.200	41730	4	April	2014
Small Business	United States of America	Velo	High	2460.0	120	300	738000.0	103320.000	634680.000	615000.0	19680.000	41821	7	July	2014
Small Business	Canada	Velo	High	269.0	120	300	80700.0	11298.000	69402.000	67250.0	2152.000	41548	10	October	2013
Small Business	Germany	Velo	High	2536.0	120	300	760800.0	106512.000	654288.000	634000.0	20288.000	41579	11	November	2013
Government	Mexico	VTT	High	2903.0	250	7	20321.0	2844.940	17476.060	14515.0	2961.060	41699	3	March	2014
Small Business	United States of America	VTT	High	2541.0	250	300	762300.0	106722.000	655578.000	635250.0	20328.000	41852	8	August	2014
Small Business	Canada	VTT	High	269.0	250	300	80700.0	11298.000	69402.000	67250.0	2152.000	41548	10	October	2013
Small Business	Canada	VTT	High	1496.0	250	300	448800.0	62832.000	385968.000	374000.0	11968.000	41913	10	October	2014
Small Business	United States of America	VTT	High	1010.0	250	300	303000.0	42420.000	260580.000	252500.0	8080.000	41913	10	October	2014
Government	France	VTT	High	1281.0	250	350	448350.0	62769.000	385581.000	333060.0	52521.000	41609	12	December	2013
Small Business	Canada	Amarilla	High	888.0	260	300	266400.0	37296.000	229104.000	222000.0	7104.000	41699	3	March	2014
Enterprise	United States of America	Amarilla	High	2844.0	260	125	355500.0	49770.000	305730.000	341280.0	-35550.000	41760	5	May	2014
Channel Partners	France	Amarilla	High	2475.0	260	12	29700.0	4158.000	25542.000	7425.0	18117.000	41852	8	August	2014
Midmarket	Canada	Amarilla	High	1743.0	260	15	26145.0	3660.300	22484.700	17430.0	5054.700	41548	10	October	2013
Channel Partners	United States of America	Amarilla	High	2914.0	260	12	34968.0	4895.520	30072.480	8742.0	21330.480	41913	10	October	2014
Government	France	Amarilla	High	1731.0	260	7	12117.0	1696.380	10420.620	8655.0	1765.620	41913	10	October	2014
Government	Mexico	Amarilla	High	1727.0	260	7	12089.0	1692.460	10396.540	8635.0	1761.540	41548	10	October	2013
Midmarket	Mexico	Amarilla	High	1870.0	260	15	28050.0	3927.000	24123.000	18700.0	5423.000	41579	11	November	2013
Enterprise	France	Carretera	High	1174.0	3	125	146750.0	22012.500	124737.500	140880.0	-16142.500	41852	8	August	2014
Enterprise	Germany	Carretera	High	2767.0	3	125	345875.0	51881.250	293993.750	332040.0	-38046.250	41852	8	August	2014
Enterprise	Germany	Carretera	High	1085.0	3	125	135625.0	20343.750	115281.250	130200.0	-14918.750	41913	10	October	2014
Small Business	Mexico	Montana	High	546.0	5	300	163800.0	24570.000	139230.000	136500.0	2730.000	41913	10	October	2014
Government	Germany	Paseo	High	1158.0	10	20	23160.0	3474.000	19686.000	11580.0	8106.000	41699	3	March	2014
Midmarket	Canada	Paseo	High	1614.0	10	15	24210.0	3631.500	20578.500	16140.0	4438.500	41730	4	April	2014
Government	Mexico	Paseo	High	2535.0	10	7	17745.0	2661.750	15083.250	12675.0	2408.250	41730	4	April	2014
Government	Mexico	Paseo	High	2851.0	10	350	997850.0	149677.500	848172.500	741260.0	106912.500	41760	5	May	2014
Midmarket	Canada	Paseo	High	2559.0	10	15	38385.0	5757.750	32627.250	25590.0	7037.250	41852	8	August	2014
Government	United States of America	Paseo	High	267.0	10	20	5340.0	801.000	4539.000	2670.0	1869.000	41548	10	October	2013
Enterprise	Germany	Paseo	High	1085.0	10	125	135625.0	20343.750	115281.250	130200.0	-14918.750	41913	10	October	2014
Midmarket	Germany	Paseo	High	1175.0	10	15	17625.0	2643.750	14981.250	11750.0	3231.250	41913	10	October	2014
Government	United States of America	Paseo	High	2007.0	10	350	702450.0	105367.500	597082.500	521820.0	75262.500	41579	11	November	2013
Government	Mexico	Paseo	High	2151.0	10	350	752850.0	112927.500	639922.500	559260.0	80662.500	41579	11	November	2013
Channel Partners	United States of America	Paseo	High	914.0	10	12	10968.0	1645.200	9322.800	2742.0	6580.800	41974	12	December	2014
Government	France	Paseo	High	293.0	10	20	5860.0	879.000	4981.000	2930.0	2051.000	41974	12	December	2014
Channel Partners	Mexico	Velo	High	500.0	120	12	6000.0	900.000	5100.000	1500.0	3600.000	41699	3	March	2014
Midmarket	France	Velo	High	2826.0	120	15	42390.0	6358.500	36031.500	28260.0	7771.500	41760	5	May	2014
Enterprise	France	Velo	High	663.0	120	125	82875.0	12431.250	70443.750	79560.0	-9116.250	41883	9	September	2014
Small Business	United States of America	Velo	High	2574.0	120	300	772200.0	115830.000	656370.000	643500.0	12870.000	41579	11	November	2013
Enterprise	United States of America	Velo	High	2438.0	120	125	304750.0	45712.500	259037.500	292560.0	-33522.500	41609	12	December	2013
Channel Partners	United States of America	Velo	High	914.0	120	12	10968.0	1645.200	9322.800	2742.0	6580.800	41974	12	December	2014
Government	Canada	VTT	High	865.5	250	20	17310.0	2596.500	14713.500	8655.0	6058.500	41821	7	July	2014
Midmarket	Germany	VTT	High	492.0	250	15	7380.0	1107.000	6273.000	4920.0	1353.000	41821	7	July	2014
Government	United States of America	VTT	High	267.0	250	20	5340.0	801.000	4539.000	2670.0	1869.000	41548	10	October	2013
Midmarket	Germany	VTT	High	1175.0	250	15	17625.0	2643.750	14981.250	11750.0	3231.250	41913	10	October	2014
Enterprise	Canada	VTT	High	2954.0	250	125	369250.0	55387.500	313862.500	354480.0	-40617.500	41579	11	November	2013
Enterprise	Germany	VTT	High	552.0	250	125	69000.0	10350.000	58650.000	66240.0	-7590.000	41944	11	November	2014
Government	France	VTT	High	293.0	250	20	5860.0	879.000	4981.000	2930.0	2051.000	41974	12	December	2014
Small Business	France	Amarilla	High	2475.0	260	300	742500.0	111375.000	631125.000	618750.0	12375.000	41699	3	March	2014
Small Business	Mexico	Amarilla	High	546.0	260	300	163800.0	24570.000	139230.000	136500.0	2730.000	41913	10	October	2014
Government	Mexico	Montana	High	1368.0	5	7	9576.0	1436.400	8139.600	6840.0	1299.600	41671	2	February	2014
Government	Canada	Paseo	High	723.0	10	7	5061.0	759.150	4301.850	3615.0	686.850	41730	4	April	2014
Channel Partners	United States of America	VTT	High	1806.0	250	12	21672.0	3250.800	18421.200	5418.0	13003.200	41760	5	May	2014
Government	France	Paseo	High	1954.0	10	20	39080.0	3908.000	35172.000	19540.0	15632.000	41699	3	March	2014
Small Business	Mexico	Paseo	High	591.0	10	300	177300.0	17730.000	159570.000	147750.0	11820.000	41760	5	May	2014
Midmarket	France	Paseo	High	2167.0	10	15	32505.0	3250.500	29254.500	21670.0	7584.500	41548	10	October	2013
Government	Germany	Paseo	High	241.0	10	20	4820.0	482.000	4338.000	2410.0	1928.000	41913	10	October	2014
Midmarket	Germany	Velo	High	681.0	120	15	10215.0	1021.500	9193.500	6810.0	2383.500	41640	1	January	2014
Midmarket	Germany	Velo	High	510.0	120	15	7650.0	765.000	6885.000	5100.0	1785.000	41730	4	April	2014
Midmarket	United States of America	Velo	High	790.0	120	15	11850.0	1185.000	10665.000	7900.0	2765.000	41760	5	May	2014
Government	France	Velo	High	639.0	120	350	223650.0	22365.000	201285.000	166140.0	35145.000	41821	7	July	2014
Enterprise	United States of America	Velo	High	1596.0	120	125	199500.0	19950.000	179550.000	191520.0	-11970.000	41883	9	September	2014
Small Business	United States of America	Velo	High	2294.0	120	300	688200.0	68820.000	619380.000	573500.0	45880.000	41548	10	October	2013
Government	Germany	Velo	High	241.0	120	20	4820.0	482.000	4338.000	2410.0	1928.000	41913	10	October	2014
Government	Germany	Velo	High	2665.0	120	7	18655.0	1865.500	16789.500	13325.0	3464.500	41944	11	November	2014
Enterprise	Canada	Velo	High	1916.0	120	125	239500.0	23950.000	215550.000	229920.0	-14370.000	41609	12	December	2013
Small Business	France	Velo	High	853.0	120	300	255900.0	25590.000	230310.000	213250.0	17060.000	41974	12	December	2014
Enterprise	Mexico	VTT	High	341.0	250	125	42625.0	4262.500	38362.500	40920.0	-2557.500	41760	5	May	2014
Midmarket	Mexico	VTT	High	641.0	250	15	9615.0	961.500	8653.500	6410.0	2243.500	41821	7	July	2014
Government	United States of America	VTT	High	2807.0	250	350	982450.0	98245.000	884205.000	729820.0	154385.000	41852	8	August	2014
Small Business	Mexico	VTT	High	432.0	250	300	129600.0	12960.000	116640.000	108000.0	8640.000	41883	9	September	2014
Small Business	United States of America	VTT	High	2294.0	250	300	688200.0	68820.000	619380.000	573500.0	45880.000	41548	10	October	2013
Midmarket	France	VTT	High	2167.0	250	15	32505.0	3250.500	29254.500	21670.0	7584.500	41548	10	October	2013
Enterprise	Canada	VTT	High	2529.0	250	125	316125.0	31612.500	284512.500	303480.0	-18967.500	41944	11	November	2014
Government	Germany	VTT	High	1870.0	250	350	654500.0	65450.000	589050.000	486200.0	102850.000	41609	12	December	2013
Enterprise	United States of America	Amarilla	High	579.0	260	125	72375.0	7237.500	65137.500	69480.0	-4342.500	41640	1	January	2014
Government	Canada	Amarilla	High	2240.0	260	350	784000.0	78400.000	705600.000	582400.0	123200.000	41671	2	February	2014
Small Business	United States of America	Amarilla	High	2993.0	260	300	897900.0	89790.000	808110.000	748250.0	59860.000	41699	3	March	2014
Channel Partners	Canada	Amarilla	High	3520.5	260	12	42246.0	4224.600	38021.400	10561.5	27459.900	41730	4	April	2014
Government	Mexico	Amarilla	High	2039.0	260	20	40780.0	4078.000	36702.000	20390.0	16312.000	41760	5	May	2014
Channel Partners	Germany	Amarilla	High	2574.0	260	12	30888.0	3088.800	27799.200	7722.0	20077.200	41852	8	August	2014
Government	Canada	Amarilla	High	707.0	260	350	247450.0	24745.000	222705.000	183820.0	38885.000	41883	9	September	2014
Midmarket	France	Amarilla	High	2072.0	260	15	31080.0	3108.000	27972.000	20720.0	7252.000	41974	12	December	2014
Small Business	France	Amarilla	High	853.0	260	300	255900.0	25590.000	230310.000	213250.0	17060.000	41974	12	December	2014
Channel Partners	France	Carretera	High	1198.0	3	12	14376.0	1581.360	12794.640	3594.0	9200.640	41548	10	October	2013
Government	France	Paseo	High	2532.0	10	7	17724.0	1949.640	15774.360	12660.0	3114.360	41730	4	April	2014
Channel Partners	France	Paseo	High	1198.0	10	12	14376.0	1581.360	12794.640	3594.0	9200.640	41548	10	October	2013
Midmarket	Canada	Velo	High	384.0	120	15	5760.0	633.600	5126.400	3840.0	1286.400	41640	1	January	2014
Channel Partners	Germany	Velo	High	472.0	120	12	5664.0	623.040	5040.960	1416.0	3624.960	41913	10	October	2014
Government	United States of America	VTT	High	1579.0	250	7	11053.0	1215.830	9837.170	7895.0	1942.170	41699	3	March	2014
Channel Partners	Mexico	VTT	High	1005.0	250	12	12060.0	1326.600	10733.400	3015.0	7718.400	41518	9	September	2013
Midmarket	United States of America	Amarilla	High	3199.5	260	15	47992.5	5279.175	42713.325	31995.0	10718.325	41821	7	July	2014
Channel Partners	Germany	Amarilla	High	472.0	260	12	5664.0	623.040	5040.960	1416.0	3624.960	41913	10	October	2014
Channel Partners	Canada	Carretera	High	1937.0	3	12	23244.0	2556.840	20687.160	5811.0	14876.160	41671	2	February	2014
Government	Germany	Carretera	High	792.0	3	350	277200.0	30492.000	246708.000	205920.0	40788.000	41699	3	March	2014
Small Business	Germany	Carretera	High	2811.0	3	300	843300.0	92763.000	750537.000	702750.0	47787.000	41821	7	July	2014
Enterprise	France	Carretera	High	2441.0	3	125	305125.0	33563.750	271561.250	292920.0	-21358.750	41913	10	October	2014
Midmarket	Canada	Carretera	High	1560.0	3	15	23400.0	2574.000	20826.000	15600.0	5226.000	41579	11	November	2013
Government	Mexico	Carretera	High	2706.0	3	7	18942.0	2083.620	16858.380	13530.0	3328.380	41579	11	November	2013
Government	Germany	Montana	High	766.0	5	350	268100.0	29491.000	238609.000	199160.0	39449.000	41640	1	January	2014
Government	Germany	Montana	High	2992.0	5	20	59840.0	6582.400	53257.600	29920.0	23337.600	41548	10	October	2013
Midmarket	Mexico	Montana	High	2157.0	5	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Small Business	Canada	Paseo	High	873.0	10	300	261900.0	28809.000	233091.000	218250.0	14841.000	41640	1	January	2014
Government	Mexico	Paseo	High	1122.0	10	20	22440.0	2468.400	19971.600	11220.0	8751.600	41699	3	March	2014
Government	Canada	Paseo	High	2104.5	10	350	736575.0	81023.250	655551.750	547170.0	108381.750	41821	7	July	2014
Channel Partners	Canada	Paseo	High	4026.0	10	12	48312.0	5314.320	42997.680	12078.0	30919.680	41821	7	July	2014
Channel Partners	France	Paseo	High	2425.5	10	12	29106.0	3201.660	25904.340	7276.5	18627.840	41821	7	July	2014
Government	Canada	Paseo	High	2394.0	10	20	47880.0	5266.800	42613.200	23940.0	18673.200	41852	8	August	2014
Midmarket	Mexico	Paseo	High	1984.0	10	15	29760.0	3273.600	26486.400	19840.0	6646.400	41852	8	August	2014
Enterprise	France	Paseo	High	2441.0	10	125	305125.0	33563.750	271561.250	292920.0	-21358.750	41913	10	October	2014
Government	Germany	Paseo	High	2992.0	10	20	59840.0	6582.400	53257.600	29920.0	23337.600	41548	10	October	2013
Small Business	Canada	Paseo	High	1366.0	10	300	409800.0	45078.000	364722.000	341500.0	23222.000	41944	11	November	2014
Government	France	Velo	High	2805.0	120	20	56100.0	6171.000	49929.000	28050.0	21879.000	41518	9	September	2013
Midmarket	Mexico	Velo	High	655.0	120	15	9825.0	1080.750	8744.250	6550.0	2194.250	41518	9	September	2013
Government	Mexico	Velo	High	344.0	120	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Government	Canada	Velo	High	1808.0	120	7	12656.0	1392.160	11263.840	9040.0	2223.840	41944	11	November	2014
Channel Partners	France	VTT	High	1734.0	250	12	20808.0	2288.880	18519.120	5202.0	13317.120	41640	1	January	2014
Enterprise	Mexico	VTT	High	554.0	250	125	69250.0	7617.500	61632.500	66480.0	-4847.500	41640	1	January	2014
Government	Canada	VTT	High	2935.0	250	20	58700.0	6457.000	52243.000	29350.0	22893.000	41579	11	November	2013
Enterprise	Germany	Amarilla	High	3165.0	260	125	395625.0	43518.750	352106.250	379800.0	-27693.750	41640	1	January	2014
Government	Mexico	Amarilla	High	2629.0	260	20	52580.0	5783.800	46796.200	26290.0	20506.200	41640	1	January	2014
Enterprise	France	Amarilla	High	1433.0	260	125	179125.0	19703.750	159421.250	171960.0	-12538.750	41760	5	May	2014
Enterprise	Mexico	Amarilla	High	947.0	260	125	118375.0	13021.250	105353.750	113640.0	-8286.250	41518	9	September	2013
Government	Mexico	Amarilla	High	344.0	260	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Midmarket	Mexico	Amarilla	High	2157.0	260	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Government	United States of America	Paseo	High	380.0	10	7	2660.0	292.600	2367.400	1900.0	467.400	41518	9	September	2013
Government	Mexico	Carretera	High	886.0	3	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Canada	Carretera	High	2416.0	3	125	302000.0	36240.000	265760.000	289920.0	-24160.000	41518	9	September	2013
Enterprise	Mexico	Carretera	High	2156.0	3	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Midmarket	Canada	Carretera	High	2689.0	3	15	40335.0	4840.200	35494.800	26890.0	8604.800	41944	11	November	2014
Midmarket	United States of America	Montana	High	677.0	5	15	10155.0	1218.600	8936.400	6770.0	2166.400	41699	3	March	2014
Small Business	France	Montana	High	1773.0	5	300	531900.0	63828.000	468072.000	443250.0	24822.000	41730	4	April	2014
Government	Mexico	Montana	High	2420.0	5	7	16940.0	2032.800	14907.200	12100.0	2807.200	41883	9	September	2014
Government	Canada	Montana	High	2734.0	5	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Government	Mexico	Montana	High	1715.0	5	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Small Business	France	Montana	High	1186.0	5	300	355800.0	42696.000	313104.000	296500.0	16604.000	41609	12	December	2013
Small Business	United States of America	Paseo	High	3495.0	10	300	1048500.0	125820.000	922680.000	873750.0	48930.000	41640	1	January	2014
Government	Mexico	Paseo	High	886.0	10	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Mexico	Paseo	High	2156.0	10	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Government	Mexico	Paseo	High	905.0	10	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Government	France	VTT	High	1491.0	250	7	10437.0	1252.440	9184.560	7455.0	1729.560	41699	3	March	2014
Government	Germany	VTT	High	1531.0	250	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Channel Partners	Canada	Amarilla	High	2761.0	260	12	33132.0	3975.840	29156.160	8283.0	20873.160	41518	9	September	2013
Midmarket	United States of America	Carretera	High	2567.0	3	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Midmarket	United States of America	VTT	High	2567.0	250	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Government	Canada	Carretera	High	923.0	3	350	323050.0	41996.500	281053.500	239980.0	41073.500	41699	3	March	2014
Government	France	Carretera	High	1790.0	3	350	626500.0	81445.000	545055.000	465400.0	79655.000	41699	3	March	2014
Government	Germany	Carretera	High	442.0	3	20	8840.0	1149.200	7690.800	4420.0	3270.800	41518	9	September	2013
Government	United States of America	Montana	High	982.5	5	350	343875.0	44703.750	299171.250	255450.0	43721.250	41640	1	January	2014
Government	United States of America	Montana	High	1298.0	5	7	9086.0	1181.180	7904.820	6490.0	1414.820	41671	2	February	2014
Channel Partners	Mexico	Montana	High	604.0	5	12	7248.0	942.240	6305.760	1812.0	4493.760	41791	6	June	2014
Government	Mexico	Montana	High	2255.0	5	20	45100.0	5863.000	39237.000	22550.0	16687.000	41821	7	July	2014
Government	Canada	Montana	High	1249.0	5	20	24980.0	3247.400	21732.600	12490.0	9242.600	41913	10	October	2014
Government	United States of America	Paseo	High	1438.5	10	7	10069.5	1309.035	8760.465	7192.5	1567.965	41640	1	January	2014
Small Business	Germany	Paseo	High	807.0	10	300	242100.0	31473.000	210627.000	201750.0	8877.000	41640	1	January	2014
Government	United States of America	Paseo	High	2641.0	10	20	52820.0	6866.600	45953.400	26410.0	19543.400	41671	2	February	2014
Government	Germany	Paseo	High	2708.0	10	20	54160.0	7040.800	47119.200	27080.0	20039.200	41671	2	February	2014
Government	Canada	Paseo	High	2632.0	10	350	921200.0	119756.000	801444.000	684320.0	117124.000	41791	6	June	2014
Enterprise	Canada	Paseo	High	1583.0	10	125	197875.0	25723.750	172151.250	189960.0	-17808.750	41791	6	June	2014
Channel Partners	Mexico	Paseo	High	571.0	10	12	6852.0	890.760	5961.240	1713.0	4248.240	41821	7	July	2014
Government	France	Paseo	High	2696.0	10	7	18872.0	2453.360	16418.640	13480.0	2938.640	41852	8	August	2014
Midmarket	Canada	Paseo	High	1565.0	10	15	23475.0	3051.750	20423.250	15650.0	4773.250	41913	10	October	2014
Government	Canada	Paseo	High	1249.0	10	20	24980.0	3247.400	21732.600	12490.0	9242.600	41913	10	October	2014
Government	Germany	Paseo	High	357.0	10	350	124950.0	16243.500	108706.500	92820.0	15886.500	41944	11	November	2014
Channel Partners	Germany	Paseo	High	1013.0	10	12	12156.0	1580.280	10575.720	3039.0	7536.720	41974	12	December	2014
Midmarket	France	Velo	High	3997.5	120	15	59962.5	7795.125	52167.375	39975.0	12192.375	41640	1	January	2014
Government	Canada	Velo	High	2632.0	120	350	921200.0	119756.000	801444.000	684320.0	117124.000	41791	6	June	2014
Government	France	Velo	High	1190.0	120	7	8330.0	1082.900	7247.100	5950.0	1297.100	41791	6	June	2014
Channel Partners	Mexico	Velo	High	604.0	120	12	7248.0	942.240	6305.760	1812.0	4493.760	41791	6	June	2014
Midmarket	Germany	Velo	High	660.0	120	15	9900.0	1287.000	8613.000	6600.0	2013.000	41518	9	September	2013
Channel Partners	Mexico	Velo	High	410.0	120	12	4920.0	639.600	4280.400	1230.0	3050.400	41913	10	October	2014
Small Business	Mexico	Velo	High	2605.0	120	300	781500.0	101595.000	679905.000	651250.0	28655.000	41579	11	November	2013
Channel Partners	Germany	Velo	High	1013.0	120	12	12156.0	1580.280	10575.720	3039.0	7536.720	41974	12	December	2014
Enterprise	Canada	VTT	High	1583.0	250	125	197875.0	25723.750	172151.250	189960.0	-17808.750	41791	6	June	2014
Midmarket	Canada	VTT	High	1565.0	250	15	23475.0	3051.750	20423.250	15650.0	4773.250	41913	10	October	2014
Enterprise	Canada	Amarilla	High	1659.0	260	125	207375.0	26958.750	180416.250	199080.0	-18663.750	41640	1	January	2014
Government	France	Amarilla	High	1190.0	260	7	8330.0	1082.900	7247.100	5950.0	1297.100	41791	6	June	2014
Channel Partners	Mexico	Amarilla	High	410.0	260	12	4920.0	639.600	4280.400	1230.0	3050.400	41913	10	October	2014
Channel Partners	Germany	Amarilla	High	1770.0	260	12	21240.0	2761.200	18478.800	5310.0	13168.800	41609	12	December	2013
Government	Mexico	Carretera	High	2579.0	3	20	51580.0	7221.200	44358.800	25790.0	18568.800	41730	4	April	2014
Government	United States of America	Carretera	High	1743.0	3	20	34860.0	4880.400	29979.600	17430.0	12549.600	41760	5	May	2014
Government	United States of America	Carretera	High	2996.0	3	7	20972.0	2936.080	18035.920	14980.0	3055.920	41548	10	October	2013
Government	Germany	Carretera	High	280.0	3	7	1960.0	274.400	1685.600	1400.0	285.600	41974	12	December	2014
Government	France	Montana	High	293.0	5	7	2051.0	287.140	1763.860	1465.0	298.860	41671	2	February	2014
Government	United States of America	Montana	High	2996.0	5	7	20972.0	2936.080	18035.920	14980.0	3055.920	41548	10	October	2013
Midmarket	Germany	Paseo	High	278.0	10	15	4170.0	583.800	3586.200	2780.0	806.200	41671	2	February	2014
Government	Canada	Paseo	High	2428.0	10	20	48560.0	6798.400	41761.600	24280.0	17481.600	41699	3	March	2014
Midmarket	United States of America	Paseo	High	1767.0	10	15	26505.0	3710.700	22794.300	17670.0	5124.300	41883	9	September	2014
Channel Partners	France	Paseo	High	1393.0	10	12	16716.0	2340.240	14375.760	4179.0	10196.760	41913	10	October	2014
Government	Germany	VTT	High	280.0	250	7	1960.0	274.400	1685.600	1400.0	285.600	41974	12	December	2014
Channel Partners	France	Amarilla	High	1393.0	260	12	16716.0	2340.240	14375.760	4179.0	10196.760	41913	10	October	2014
Government	France	Velo	High	2805.0	120	20	56100.0	6171.000	49929.000	28050.0	21879.000	41518	9	September	2013
Midmarket	Mexico	Velo	High	655.0	120	15	9825.0	1080.750	8744.250	6550.0	2194.250	41518	9	September	2013
Government	Mexico	Velo	High	344.0	120	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Government	Canada	Velo	High	1808.0	120	7	12656.0	1392.160	11263.840	9040.0	2223.840	41944	11	November	2014
Channel Partners	France	VTT	High	1734.0	250	12	20808.0	2288.880	18519.120	5202.0	13317.120	41640	1	January	2014
Enterprise	Mexico	VTT	High	554.0	250	125	69250.0	7617.500	61632.500	66480.0	-4847.500	41640	1	January	2014
Government	Canada	VTT	High	2935.0	250	20	58700.0	6457.000	52243.000	29350.0	22893.000	41579	11	November	2013
Enterprise	Germany	Amarilla	High	3165.0	260	125	395625.0	43518.750	352106.250	379800.0	-27693.750	41640	1	January	2014
Government	Mexico	Amarilla	High	2629.0	260	20	52580.0	5783.800	46796.200	26290.0	20506.200	41640	1	January	2014
Enterprise	France	Amarilla	High	1433.0	260	125	179125.0	19703.750	159421.250	171960.0	-12538.750	41760	5	May	2014
Enterprise	Mexico	Amarilla	High	947.0	260	125	118375.0	13021.250	105353.750	113640.0	-8286.250	41518	9	September	2013
Government	Mexico	Amarilla	High	344.0	260	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Midmarket	Mexico	Amarilla	High	2157.0	260	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Government	United States of America	Paseo	High	380.0	10	7	2660.0	292.600	2367.400	1900.0	467.400	41518	9	September	2013
Government	Mexico	Carretera	High	886.0	3	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Canada	Carretera	High	2416.0	3	125	302000.0	36240.000	265760.000	289920.0	-24160.000	41518	9	September	2013
Enterprise	Mexico	Carretera	High	2156.0	3	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Midmarket	Canada	Carretera	High	2689.0	3	15	40335.0	4840.200	35494.800	26890.0	8604.800	41944	11	November	2014
Midmarket	United States of America	Montana	High	677.0	5	15	10155.0	1218.600	8936.400	6770.0	2166.400	41699	3	March	2014
Small Business	France	Montana	High	1773.0	5	300	531900.0	63828.000	468072.000	443250.0	24822.000	41730	4	April	2014
Government	Mexico	Montana	High	2420.0	5	7	16940.0	2032.800	14907.200	12100.0	2807.200	41883	9	September	2014
Government	Canada	Montana	High	2734.0	5	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Government	Mexico	Montana	High	1715.0	5	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Small Business	France	Montana	High	1186.0	5	300	355800.0	42696.000	313104.000	296500.0	16604.000	41609	12	December	2013
Small Business	United States of America	Paseo	High	3495.0	10	300	1048500.0	125820.000	922680.000	873750.0	48930.000	41640	1	January	2014
Government	Mexico	Paseo	High	886.0	10	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Mexico	Paseo	High	2156.0	10	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Government	Mexico	Paseo	High	905.0	10	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Government	Mexico	Paseo	High	1715.0	10	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Government	France	Paseo	High	1594.0	10	350	557900.0	66948.000	490952.000	414440.0	76512.000	41944	11	November	2014
Small Business	Germany	Paseo	High	1359.0	10	300	407700.0	48924.000	358776.000	339750.0	19026.000	41944	11	November	2014
Small Business	Mexico	Paseo	High	2150.0	10	300	645000.0	77400.000	567600.000	537500.0	30100.000	41944	11	November	2014
Government	Mexico	Paseo	High	1197.0	10	350	418950.0	50274.000	368676.000	311220.0	57456.000	41944	11	November	2014
Midmarket	Mexico	Paseo	High	380.0	10	15	5700.0	684.000	5016.000	3800.0	1216.000	41609	12	December	2013
Government	Mexico	Paseo	High	1233.0	10	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	Mexico	Velo	High	1395.0	120	350	488250.0	58590.000	429660.000	362700.0	66960.000	41821	7	July	2014
Government	United States of America	Velo	High	986.0	120	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Government	Mexico	Velo	High	905.0	120	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Channel Partners	Canada	VTT	High	2109.0	250	12	25308.0	3036.960	22271.040	6327.0	15944.040	41760	5	May	2014
Midmarket	France	VTT	High	3874.5	250	15	58117.5	6974.100	51143.400	38745.0	12398.400	41821	7	July	2014
Government	Canada	VTT	High	623.0	250	350	218050.0	26166.000	191884.000	161980.0	29904.000	41518	9	September	2013
Government	United States of America	VTT	High	986.0	250	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Enterprise	United States of America	VTT	High	2387.0	250	125	298375.0	35805.000	262570.000	286440.0	-23870.000	41944	11	November	2014
Government	Mexico	VTT	High	1233.0	250	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	United States of America	Amarilla	High	270.0	260	350	94500.0	11340.000	83160.000	70200.0	12960.000	41671	2	February	2014
Government	France	Amarilla	High	3421.5	260	7	23950.5	2874.060	21076.440	17107.5	3968.940	41821	7	July	2014
Government	Canada	Amarilla	High	2734.0	260	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Midmarket	United States of America	Amarilla	High	2548.0	260	15	38220.0	4586.400	33633.600	25480.0	8153.600	41579	11	November	2013
Government	France	Carretera	High	2521.5	3	20	50430.0	6051.600	44378.400	25215.0	19163.400	41640	1	January	2014
Channel Partners	Mexico	Montana	High	2661.0	5	12	31932.0	3831.840	28100.160	7983.0	20117.160	41760	5	May	2014
Government	Germany	Paseo	High	1531.0	10	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Government	France	VTT	High	1491.0	250	7	10437.0	1252.440	9184.560	7455.0	1729.560	41699	3	March	2014
Government	Germany	VTT	High	1531.0	250	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Channel Partners	Canada	Amarilla	High	2761.0	260	12	33132.0	3975.840	29156.160	8283.0	20873.160	41518	9	September	2013
Midmarket	United States of America	Carretera	High	2567.0	3	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Midmarket	United States of America	VTT	High	2567.0	250	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Government	France	Velo	High	2805.0	120	20	56100.0	6171.000	49929.000	28050.0	21879.000	41518	9	September	2013
Midmarket	Mexico	Velo	High	655.0	120	15	9825.0	1080.750	8744.250	6550.0	2194.250	41518	9	September	2013
Government	Mexico	Velo	High	344.0	120	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Government	Canada	Velo	High	1808.0	120	7	12656.0	1392.160	11263.840	9040.0	2223.840	41944	11	November	2014
Channel Partners	France	VTT	High	1734.0	250	12	20808.0	2288.880	18519.120	5202.0	13317.120	41640	1	January	2014
Enterprise	Mexico	VTT	High	554.0	250	125	69250.0	7617.500	61632.500	66480.0	-4847.500	41640	1	January	2014
Government	Canada	VTT	High	2935.0	250	20	58700.0	6457.000	52243.000	29350.0	22893.000	41579	11	November	2013
Enterprise	Germany	Amarilla	High	3165.0	260	125	395625.0	43518.750	352106.250	379800.0	-27693.750	41640	1	January	2014
Government	Mexico	Amarilla	High	2629.0	260	20	52580.0	5783.800	46796.200	26290.0	20506.200	41640	1	January	2014
Enterprise	France	Amarilla	High	1433.0	260	125	179125.0	19703.750	159421.250	171960.0	-12538.750	41760	5	May	2014
Enterprise	Mexico	Amarilla	High	947.0	260	125	118375.0	13021.250	105353.750	113640.0	-8286.250	41518	9	September	2013
Government	Mexico	Amarilla	High	344.0	260	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Midmarket	Mexico	Amarilla	High	2157.0	260	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Government	United States of America	Paseo	High	380.0	10	7	2660.0	292.600	2367.400	1900.0	467.400	41518	9	September	2013
Government	Mexico	Carretera	High	886.0	3	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Canada	Carretera	High	2416.0	3	125	302000.0	36240.000	265760.000	289920.0	-24160.000	41518	9	September	2013
Enterprise	Mexico	Carretera	High	2156.0	3	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Midmarket	Canada	Carretera	High	2689.0	3	15	40335.0	4840.200	35494.800	26890.0	8604.800	41944	11	November	2014
Midmarket	United States of America	Montana	High	677.0	5	15	10155.0	1218.600	8936.400	6770.0	2166.400	41699	3	March	2014
Small Business	France	Montana	High	1773.0	5	300	531900.0	63828.000	468072.000	443250.0	24822.000	41730	4	April	2014
Government	Mexico	Montana	High	2420.0	5	7	16940.0	2032.800	14907.200	12100.0	2807.200	41883	9	September	2014
Government	Canada	Montana	High	2734.0	5	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Government	Mexico	Montana	High	1715.0	5	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Small Business	France	Montana	High	1186.0	5	300	355800.0	42696.000	313104.000	296500.0	16604.000	41609	12	December	2013
Small Business	United States of America	Paseo	High	3495.0	10	300	1048500.0	125820.000	922680.000	873750.0	48930.000	41640	1	January	2014
Government	Mexico	Paseo	High	886.0	10	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Mexico	Paseo	High	2156.0	10	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Government	Mexico	Paseo	High	905.0	10	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Government	Mexico	Paseo	High	1715.0	10	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Government	France	Paseo	High	1594.0	10	350	557900.0	66948.000	490952.000	414440.0	76512.000	41944	11	November	2014
Small Business	Germany	Paseo	High	1359.0	10	300	407700.0	48924.000	358776.000	339750.0	19026.000	41944	11	November	2014
Small Business	Mexico	Paseo	High	2150.0	10	300	645000.0	77400.000	567600.000	537500.0	30100.000	41944	11	November	2014
Government	Mexico	Paseo	High	1197.0	10	350	418950.0	50274.000	368676.000	311220.0	57456.000	41944	11	November	2014
Midmarket	Mexico	Paseo	High	380.0	10	15	5700.0	684.000	5016.000	3800.0	1216.000	41609	12	December	2013
Government	Mexico	Paseo	High	1233.0	10	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	Mexico	Velo	High	1395.0	120	350	488250.0	58590.000	429660.000	362700.0	66960.000	41821	7	July	2014
Government	United States of America	Velo	High	986.0	120	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Government	Mexico	Velo	High	905.0	120	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Channel Partners	Canada	VTT	High	2109.0	250	12	25308.0	3036.960	22271.040	6327.0	15944.040	41760	5	May	2014
Midmarket	France	VTT	High	3874.5	250	15	58117.5	6974.100	51143.400	38745.0	12398.400	41821	7	July	2014
Government	Canada	VTT	High	623.0	250	350	218050.0	26166.000	191884.000	161980.0	29904.000	41518	9	September	2013
Government	United States of America	VTT	High	986.0	250	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Enterprise	United States of America	VTT	High	2387.0	250	125	298375.0	35805.000	262570.000	286440.0	-23870.000	41944	11	November	2014
Government	Mexico	VTT	High	1233.0	250	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	United States of America	Amarilla	High	270.0	260	350	94500.0	11340.000	83160.000	70200.0	12960.000	41671	2	February	2014
Government	France	Amarilla	High	3421.5	260	7	23950.5	2874.060	21076.440	17107.5	3968.940	41821	7	July	2014
Government	Canada	Amarilla	High	2734.0	260	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Midmarket	United States of America	Amarilla	High	2548.0	260	15	38220.0	4586.400	33633.600	25480.0	8153.600	41579	11	November	2013
Government	France	Carretera	High	2521.5	3	20	50430.0	6051.600	44378.400	25215.0	19163.400	41640	1	January	2014
Channel Partners	Mexico	Montana	High	2661.0	5	12	31932.0	3831.840	28100.160	7983.0	20117.160	41760	5	May	2014
Government	Germany	Paseo	High	1531.0	10	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Government	France	VTT	High	1491.0	250	7	10437.0	1252.440	9184.560	7455.0	1729.560	41699	3	March	2014
Government	Germany	VTT	High	1531.0	250	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Channel Partners	Canada	Amarilla	High	2761.0	260	12	33132.0	3975.840	29156.160	8283.0	20873.160	41518	9	September	2013
Midmarket	United States of America	Carretera	High	2567.0	3	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Midmarket	United States of America	VTT	High	2567.0	250	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Government	France	Velo	High	2805.0	120	20	56100.0	6171.000	49929.000	28050.0	21879.000	41518	9	September	2013
Midmarket	Mexico	Velo	High	655.0	120	15	9825.0	1080.750	8744.250	6550.0	2194.250	41518	9	September	2013
Government	Mexico	Velo	High	344.0	120	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Government	Canada	Velo	High	1808.0	120	7	12656.0	1392.160	11263.840	9040.0	2223.840	41944	11	November	2014
Channel Partners	France	VTT	High	1734.0	250	12	20808.0	2288.880	18519.120	5202.0	13317.120	41640	1	January	2014
Enterprise	Mexico	VTT	High	554.0	250	125	69250.0	7617.500	61632.500	66480.0	-4847.500	41640	1	January	2014
Government	Canada	VTT	High	2935.0	250	20	58700.0	6457.000	52243.000	29350.0	22893.000	41579	11	November	2013
Enterprise	Germany	Amarilla	High	3165.0	260	125	395625.0	43518.750	352106.250	379800.0	-27693.750	41640	1	January	2014
Government	Mexico	Amarilla	High	2629.0	260	20	52580.0	5783.800	46796.200	26290.0	20506.200	41640	1	January	2014
Enterprise	France	Amarilla	High	1433.0	260	125	179125.0	19703.750	159421.250	171960.0	-12538.750	41760	5	May	2014
Enterprise	Mexico	Amarilla	High	947.0	260	125	118375.0	13021.250	105353.750	113640.0	-8286.250	41518	9	September	2013
Government	Mexico	Amarilla	High	344.0	260	350	120400.0	13244.000	107156.000	89440.0	17716.000	41548	10	October	2013
Midmarket	Mexico	Amarilla	High	2157.0	260	15	32355.0	3559.050	28795.950	21570.0	7225.950	41974	12	December	2014
Government	United States of America	Paseo	High	380.0	10	7	2660.0	292.600	2367.400	1900.0	467.400	41518	9	September	2013
Government	Mexico	Carretera	High	886.0	3	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Canada	Carretera	High	2416.0	3	125	302000.0	36240.000	265760.000	289920.0	-24160.000	41518	9	September	2013
Enterprise	Mexico	Carretera	High	2156.0	3	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Midmarket	Canada	Carretera	High	2689.0	3	15	40335.0	4840.200	35494.800	26890.0	8604.800	41944	11	November	2014
Midmarket	United States of America	Montana	High	677.0	5	15	10155.0	1218.600	8936.400	6770.0	2166.400	41699	3	March	2014
Small Business	France	Montana	High	1773.0	5	300	531900.0	63828.000	468072.000	443250.0	24822.000	41730	4	April	2014
Government	Mexico	Montana	High	2420.0	5	7	16940.0	2032.800	14907.200	12100.0	2807.200	41883	9	September	2014
Government	Canada	Montana	High	2734.0	5	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Government	Mexico	Montana	High	1715.0	5	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Small Business	France	Montana	High	1186.0	5	300	355800.0	42696.000	313104.000	296500.0	16604.000	41609	12	December	2013
Small Business	United States of America	Paseo	High	3495.0	10	300	1048500.0	125820.000	922680.000	873750.0	48930.000	41640	1	January	2014
Government	Mexico	Paseo	High	886.0	10	350	310100.0	37212.000	272888.000	230360.0	42528.000	41791	6	June	2014
Enterprise	Mexico	Paseo	High	2156.0	10	125	269500.0	32340.000	237160.000	258720.0	-21560.000	41913	10	October	2014
Government	Mexico	Paseo	High	905.0	10	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Government	Mexico	Paseo	High	1715.0	10	20	34300.0	4116.000	30184.000	17150.0	13034.000	41548	10	October	2013
Government	France	Paseo	High	1594.0	10	350	557900.0	66948.000	490952.000	414440.0	76512.000	41944	11	November	2014
Small Business	Germany	Paseo	High	1359.0	10	300	407700.0	48924.000	358776.000	339750.0	19026.000	41944	11	November	2014
Small Business	Mexico	Paseo	High	2150.0	10	300	645000.0	77400.000	567600.000	537500.0	30100.000	41944	11	November	2014
Government	Mexico	Paseo	High	1197.0	10	350	418950.0	50274.000	368676.000	311220.0	57456.000	41944	11	November	2014
Midmarket	Mexico	Paseo	High	380.0	10	15	5700.0	684.000	5016.000	3800.0	1216.000	41609	12	December	2013
Government	Mexico	Paseo	High	1233.0	10	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	Mexico	Velo	High	1395.0	120	350	488250.0	58590.000	429660.000	362700.0	66960.000	41821	7	July	2014
Government	United States of America	Velo	High	986.0	120	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Government	Mexico	Velo	High	905.0	120	20	18100.0	2172.000	15928.000	9050.0	6878.000	41913	10	October	2014
Channel Partners	Canada	VTT	High	2109.0	250	12	25308.0	3036.960	22271.040	6327.0	15944.040	41760	5	May	2014
Midmarket	France	VTT	High	3874.5	250	15	58117.5	6974.100	51143.400	38745.0	12398.400	41821	7	July	2014
Government	Canada	VTT	High	623.0	250	350	218050.0	26166.000	191884.000	161980.0	29904.000	41518	9	September	2013
Government	United States of America	VTT	High	986.0	250	350	345100.0	41412.000	303688.000	256360.0	47328.000	41913	10	October	2014
Enterprise	United States of America	VTT	High	2387.0	250	125	298375.0	35805.000	262570.000	286440.0	-23870.000	41944	11	November	2014
Government	Mexico	VTT	High	1233.0	250	20	24660.0	2959.200	21700.800	12330.0	9370.800	41974	12	December	2014
Government	United States of America	Amarilla	High	270.0	260	350	94500.0	11340.000	83160.000	70200.0	12960.000	41671	2	February	2014
Government	France	Amarilla	High	3421.5	260	7	23950.5	2874.060	21076.440	17107.5	3968.940	41821	7	July	2014
Government	Canada	Amarilla	High	2734.0	260	7	19138.0	2296.560	16841.440	13670.0	3171.440	41913	10	October	2014
Midmarket	United States of America	Amarilla	High	2548.0	260	15	38220.0	4586.400	33633.600	25480.0	8153.600	41579	11	November	2013
Government	France	Carretera	High	2521.5	3	20	50430.0	6051.600	44378.400	25215.0	19163.400	41640	1	January	2014
Channel Partners	Mexico	Montana	High	2661.0	5	12	31932.0	3831.840	28100.160	7983.0	20117.160	41760	5	May	2014
Government	Germany	Paseo	High	1531.0	10	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Government	France	VTT	High	1491.0	250	7	10437.0	1252.440	9184.560	7455.0	1729.560	41699	3	March	2014
Government	Germany	VTT	High	1531.0	250	20	30620.0	3674.400	26945.600	15310.0	11635.600	41974	12	December	2014
Channel Partners	Canada	Amarilla	High	2761.0	260	12	33132.0	3975.840	29156.160	8283.0	20873.160	41518	9	September	2013
Midmarket	United States of America	Carretera	High	2567.0	3	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014
Midmarket	United States of America	VTT	High	2567.0	250	15	38505.0	5005.650	33499.350	25670.0	7829.350	41791	6	June	2014

library(skimr)
skim(navy)

Data summary
Name	navy
Number of rows	1006
Number of columns	16
_______________________
Column type frequency:
character	6
numeric	10
________________________
Group variables	None

Variable type: character

skim_variable	complete_rate	min	max	n_unique
Segment	1	9	16	5
Country	1	6	24	5
Product	1	3	9	6
Discount.Band	1	3	6	4
Month.Name	1	3	9	12
Year	1	4	4	2

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Units.Sold	1	1639.26	885.62	200.00	905.00	1566.00	2339.50	4492.5	▇▇▇▂▁
Manufacturing.Price	1	101.69	110.35	3.00	5.00	10.00	250.00	260.0	▇▁▂▁▅
Sale.Price	1	116.81	136.77	7.00	12.00	20.00	300.00	350.0	▇▂▁▁▃
Gross.Sales	1	175936.31	245508.65	1799.00	18176.25	38592.50	269500.00	1207500.0	▇▂▁▁▁
Discounts	1	14832.22	24110.38	0.00	1132.80	3559.05	19950.00	149677.5	▇▁▁▁▁
Sales	1	161104.09	225860.91	1655.08	16748.55	35540.20	243346.88	1159200.0	▇▂▁▁▁
COGS	1	139965.38	198115.49	918.00	8083.50	24490.00	236465.00	950625.0	▇▂▁▁▁
Profit	1	21138.70	38428.09	-40617.50	2750.00	9242.60	21272.24	262200.0	▇▂▁▁▁
Date	1	41756.63	149.55	41518.00	41640.00	41760.00	41913.00	41974.0	▆▅▅▂▇
Month.Number	1	7.84	3.44	1.00	5.00	9.00	10.00	12.0	▃▂▂▂▇

2.3 . Thống kê mô tả

Thực hiện gán object navy là datasets Financial Sample Excel, thực hiện các lệnh trên objec navy, ta có được những thông tin sau:

navy có 1006 quan sát và 16 biến
Không có dữ liệu trống
n_missing: số ô dữ liệu trống
complete_rate: tỷ lệ ô có dữ liệu
mean: trung bình
sd: độ lệch chuẩn
p0: giá trị min
p25: phân vị thứ nhất
p50: phân vị thứ hai(trung vị)
p75: phân vị thứ ba
p100: giá trị max
hist: biểu đồ Histogram

2.4 . Xử lý dữ liệu bị trùng lắp

library(tidyverse)
navy1 <- unique(navy) #lấy lượng biến trong "navy"
str(navy1)

## 'data.frame':    700 obs. of  16 variables:
##  $ Segment            : chr  "Government" "Government" "Midmarket" "Midmarket" ...
##  $ Country            : chr  "Canada" "Germany" "France" "Germany" ...
##  $ Product            : chr  "Carretera" "Carretera" "Carretera" "Carretera" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  1618 1321 2178 888 2470 ...
##  $ Manufacturing.Price: num  3 3 3 3 3 3 5 5 5 5 ...
##  $ Sale.Price         : num  20 20 15 15 15 350 15 12 20 12 ...
##  $ Gross.Sales        : num  32370 26420 32670 13320 37050 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  32370 26420 32670 13320 37050 ...
##  $ COGS               : num  16185 13210 21780 8880 24700 ...
##  $ Profit             : num  16185 13210 10890 4440 12350 ...
##  $ Date               : num  41640 41640 41791 41791 41791 ...
##  $ Month.Number       : num  1 1 6 6 6 12 3 6 6 6 ...
##  $ Month.Name         : chr  "January" "January" "June" "June" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...

navy2 <- distinct(navy) #Loại bỏ trung lắp trong "navy"
str(navy2)

## 'data.frame':    700 obs. of  16 variables:
##  $ Segment            : chr  "Government" "Government" "Midmarket" "Midmarket" ...
##  $ Country            : chr  "Canada" "Germany" "France" "Germany" ...
##  $ Product            : chr  "Carretera" "Carretera" "Carretera" "Carretera" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  1618 1321 2178 888 2470 ...
##  $ Manufacturing.Price: num  3 3 3 3 3 3 5 5 5 5 ...
##  $ Sale.Price         : num  20 20 15 15 15 350 15 12 20 12 ...
##  $ Gross.Sales        : num  32370 26420 32670 13320 37050 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  32370 26420 32670 13320 37050 ...
##  $ COGS               : num  16185 13210 21780 8880 24700 ...
##  $ Profit             : num  16185 13210 10890 4440 12350 ...
##  $ Date               : num  41640 41640 41791 41791 41791 ...
##  $ Month.Number       : num  1 1 6 6 6 12 3 6 6 6 ...
##  $ Month.Name         : chr  "January" "January" "June" "June" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...

2.5 . Rút trích dữ liệu

Giả sử yêu cầu lấy những thông tin trong datasets đã loại bỏ trùng lặp “navy2” như sau: - lấy 100 quan sát đầu tiên trong datasets - lấy 50 quan sát cuối trong datastest - chọn những quan sát quốc gia Germany - chọn những sản phẩm Paseo hoặc Velo - chọn những sản phẩm Paseo có rủi ro trung bình - chọn làm việc với biến Country,Date mà Product là Paseo

navy100 <- head(navy,100)
str(navy100)

## 'data.frame':    100 obs. of  16 variables:
##  $ Segment            : chr  "Government" "Government" "Midmarket" "Midmarket" ...
##  $ Country            : chr  "Canada" "Germany" "France" "Germany" ...
##  $ Product            : chr  "Carretera" "Carretera" "Carretera" "Carretera" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  1618 1321 2178 888 2470 ...
##  $ Manufacturing.Price: num  3 3 3 3 3 3 5 5 5 5 ...
##  $ Sale.Price         : num  20 20 15 15 15 350 15 12 20 12 ...
##  $ Gross.Sales        : num  32370 26420 32670 13320 37050 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  32370 26420 32670 13320 37050 ...
##  $ COGS               : num  16185 13210 21780 8880 24700 ...
##  $ Profit             : num  16185 13210 10890 4440 12350 ...
##  $ Date               : num  41640 41640 41791 41791 41791 ...
##  $ Month.Number       : num  1 1 6 6 6 12 3 6 6 6 ...
##  $ Month.Name         : chr  "January" "January" "June" "June" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...

navy50 <- tail(navy,50)
str(navy50)

## 'data.frame':    50 obs. of  16 variables:
##  $ Segment            : chr  "Government" "Enterprise" "Government" "Enterprise" ...
##  $ Country            : chr  "Canada" "Germany" "Mexico" "France" ...
##  $ Product            : chr  "VTT" "Amarilla" "Amarilla" "Amarilla" ...
##  $ Discount.Band      : chr  "High" "High" "High" "High" ...
##  $ Units.Sold         : num  2935 3165 2629 1433 947 ...
##  $ Manufacturing.Price: num  250 260 260 260 260 260 260 10 3 3 ...
##  $ Sale.Price         : num  20 125 20 125 125 350 15 7 350 125 ...
##  $ Gross.Sales        : num  58700 395625 52580 179125 118375 ...
##  $ Discounts          : num  6457 43519 5784 19704 13021 ...
##  $ Sales              : num  52243 352106 46796 159421 105354 ...
##  $ COGS               : num  29350 379800 26290 171960 113640 ...
##  $ Profit             : num  22893 -27694 20506 -12539 -8286 ...
##  $ Date               : num  41579 41640 41640 41760 41518 ...
##  $ Month.Number       : num  11 1 1 5 9 10 12 9 6 9 ...
##  $ Month.Name         : chr  "November" "January" "January" "May" ...
##  $ Year               : chr  "2013" "2014" "2014" "2014" ...

navy150 <- navy[navy$Product == 'Paseo' & navy$DiscountBand == 'Medium', ]
str(navy150)

## 'data.frame':    0 obs. of  16 variables:
##  $ Segment            : chr 
##  $ Country            : chr 
##  $ Product            : chr 
##  $ Discount.Band      : chr 
##  $ Units.Sold         : num 
##  $ Manufacturing.Price: num 
##  $ Sale.Price         : num 
##  $ Gross.Sales        : num 
##  $ Discounts          : num 
##  $ Sales              : num 
##  $ COGS               : num 
##  $ Profit             : num 
##  $ Date               : num 
##  $ Month.Number       : num 
##  $ Month.Name         : chr 
##  $ Year               : chr

navy200 <- navy[navy$Country == 'Germany', ]
str(navy200)

## 'data.frame':    179 obs. of  16 variables:
##  $ Segment            : chr  "Government" "Midmarket" "Government" "Midmarket" ...
##  $ Country            : chr  "Germany" "Germany" "Germany" "Germany" ...
##  $ Product            : chr  "Carretera" "Carretera" "Carretera" "Montana" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  1321 888 1513 921 1545 ...
##  $ Manufacturing.Price: num  3 3 3 5 5 5 10 10 10 120 ...
##  $ Sale.Price         : num  20 15 350 15 12 7 350 12 350 12 ...
##  $ Gross.Sales        : num  26420 13320 529550 13815 18540 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  26420 13320 529550 13815 18540 ...
##  $ COGS               : num  13210 8880 393380 9210 4635 ...
##  $ Profit             : num  13210 4440 136170 4605 13905 ...
##  $ Date               : num  41640 41791 41974 41699 41791 ...
##  $ Month.Number       : num  1 6 12 3 6 9 6 7 12 3 ...
##  $ Month.Name         : chr  "January" "June" "December" "March" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...

navy200 <- navy[navy$Product == 'Paseo' | navy$Product == 'Velo',]
str(navy200)

## 'data.frame':    432 obs. of  16 variables:
##  $ Segment            : chr  "Government" "Midmarket" "Channel Partners" "Government" ...
##  $ Country            : chr  "Canada" "Mexico" "Canada" "Germany" ...
##  $ Product            : chr  "Paseo" "Paseo" "Paseo" "Paseo" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  292 974 2518 1006 367 ...
##  $ Manufacturing.Price: num  10 10 10 10 10 10 10 10 10 10 ...
##  $ Sale.Price         : num  20 15 12 350 12 7 15 300 15 7 ...
##  $ Gross.Sales        : num  5840 14610 30216 352100 4404 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  5840 14610 30216 352100 4404 ...
##  $ COGS               : num  2920 9740 7554 261560 1101 ...
##  $ Profit             : num  2920 4870 22662 90540 3303 ...
##  $ Date               : num  41671 41671 41791 41791 41821 ...
##  $ Month.Number       : num  2 2 6 6 7 8 9 9 9 10 ...
##  $ Month.Name         : chr  "February" "February" "June" "June" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...

library(dplyr)

navy300 <- filter(navy, Product=='Paseo') %>% select(Country,Date,)
str(navy300)

## 'data.frame':    278 obs. of  2 variables:
##  $ Country: chr  "Canada" "Mexico" "Canada" "Germany" ...
##  $ Date   : num  41671 41671 41791 41791 41821 ...

2.6 . Tạo dữ liệu mới

Từ object cũ navy ta tạo thành object mới **navyx*, với các biến mới như sau:

pVND: lợi nhuận tính bằng VND
tPro: đánh giá số lượng sản phẩm bán ra

navyx <- mutate(navy, pVND= Profit*24.550)
str(navyx)

## 'data.frame':    1006 obs. of  17 variables:
##  $ Segment            : chr  "Government" "Government" "Midmarket" "Midmarket" ...
##  $ Country            : chr  "Canada" "Germany" "France" "Germany" ...
##  $ Product            : chr  "Carretera" "Carretera" "Carretera" "Carretera" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  1618 1321 2178 888 2470 ...
##  $ Manufacturing.Price: num  3 3 3 3 3 3 5 5 5 5 ...
##  $ Sale.Price         : num  20 20 15 15 15 350 15 12 20 12 ...
##  $ Gross.Sales        : num  32370 26420 32670 13320 37050 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  32370 26420 32670 13320 37050 ...
##  $ COGS               : num  16185 13210 21780 8880 24700 ...
##  $ Profit             : num  16185 13210 10890 4440 12350 ...
##  $ Date               : num  41640 41640 41791 41791 41791 ...
##  $ Month.Number       : num  1 1 6 6 6 12 3 6 6 6 ...
##  $ Month.Name         : chr  "January" "January" "June" "June" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...
##  $ pVND               : num  397342 324306 267350 109002 303192 ...

navyx$tPro <- case_when(navy$Product< 1000 ~ 'bán ra thấp' , navy$Product == 1000 ~ 'bán ra trung bình' , navy$Product > 1000 ~ ' bán ra cao') 
str(navyx)

## 'data.frame':    1006 obs. of  18 variables:
##  $ Segment            : chr  "Government" "Government" "Midmarket" "Midmarket" ...
##  $ Country            : chr  "Canada" "Germany" "France" "Germany" ...
##  $ Product            : chr  "Carretera" "Carretera" "Carretera" "Carretera" ...
##  $ Discount.Band      : chr  "None" "None" "None" "None" ...
##  $ Units.Sold         : num  1618 1321 2178 888 2470 ...
##  $ Manufacturing.Price: num  3 3 3 3 3 3 5 5 5 5 ...
##  $ Sale.Price         : num  20 20 15 15 15 350 15 12 20 12 ...
##  $ Gross.Sales        : num  32370 26420 32670 13320 37050 ...
##  $ Discounts          : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sales              : num  32370 26420 32670 13320 37050 ...
##  $ COGS               : num  16185 13210 21780 8880 24700 ...
##  $ Profit             : num  16185 13210 10890 4440 12350 ...
##  $ Date               : num  41640 41640 41791 41791 41791 ...
##  $ Month.Number       : num  1 1 6 6 6 12 3 6 6 6 ...
##  $ Month.Name         : chr  "January" "January" "June" "June" ...
##  $ Year               : chr  "2014" "2014" "2014" "2014" ...
##  $ pVND               : num  397342 324306 267350 109002 303192 ...
##  $ tPro               : chr  " bán ra cao" " bán ra cao" " bán ra cao" " bán ra cao" ...

```

---
title: "NHIỆM VỤ 2"
author: "Lê Ngọc Tường Vy"
date: "`r format(Sys.time(), '%H:%M:%S, %d - %m - %Y')`"
output:
  html_document:
    code_download: true
    code_folding: hide
    number_sections: yes
    theme: "default"
    toc_depth: 2
    toc_float: true
    toc: true
  word_document:
    toc: true
    toc_depth: '2'
  pdf_document: 
    latex_engine: xelatex
---
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# **. NHIỆM VỤ 2.1**
***
## **. Tóm Tắt**
Nhiệm vụ 2.1 thao tác trên datasets "**bwt_co_dieu_chinh.xlsx**" là datasets thống kê những thuộc tính trong quá trình mang thai của phụ nữ giai đoạn 1925-2004.

## **. Mô tả cơ bản** 
Các thông số từ datasets có 640 quan sát và 9 biến như sau:

- **id:** Khu vực (có 8 khu vực).
- **year:** Năm lấy số liệu.
- **bwt:** Trọng lượng lúc sinh tính bằng ounces, 1 ounces=28.3495 gram).
- **gestation:** Thời gian mang thai(tính bằng ngày).
- **parity:** Số lần sinh (có hai giá trị, 1=sinh lần đầu, 0=không phải lần đầu).
- **age:** Tuổi của mẹ.
- **height:** Chiều cao của mẹ (tính bằng inches, 1 inch=2.54cm).
- **weight:** Cân nặng của bà mẹ khi mang thai (tính bằng pounds, 1 pound=0.453592kg).
- **smoke:** Hút thuốc lúc mang thai (1=có, 0=không).

Không có dữ liệu trống

***
## **. Đọc dữ liệu từ file Excel**
***

```{r}
library(openxlsx)
vy1 <- read.xlsx("/Users/xuyenchi/Library/Containers/com.microsoft.Excel/Data/Downloads/R Code/bwt_co_dieu_chinh.xlsx") #đọc dữ liệu từ excel và gán vào object vy1
table <- knitr::kable(vy1,format="markdown")
table 
is.data.frame(vy1) #kiểm tra "vy1" có phải là data frame không, nếu đúng thì true và ngược lại
```

## **. Thông tin tổng quan**
***

```{r}
length(vy1) #cho ra số biến của "vy1"

```

```{r}
names(vy1) #cho ra tên các biến của "vy1"
```



```{r}
dim(vy1) #cho ra số quan sát và số biến của "vy1"
```

```{r}
sum(is.na(vy1)) #cho ra tổng số object của "vy1"
```

```{r}
library(skimr) 
skim(vy1)


```


**Mô tả**

- n_missing: số ô dữ liệu trống
- complete_rate: tỷ lệ ô có dữ liệu
- mean: trung bình
- sd:	độ lệch chuẩn
- p0:	giá trị min
- p25: phân vị thứ nhất
- p50: phân vị thứ hai(trung vị)	
- p75: phân vị thứ ba
- p100:	giá trị max
- hist: biểu đồ Histogram














```{r}
head(vy1,28) #lấy 28 dòng đầu từ "vy1"
```

```
```

```{r}
tail(vy1,28) #lấy 28 dòng cuối từ "vy1"
```




```{r}
is.na(vy1) # tìm ô không có dữ liệu trong "vy1", nếu "False" là có dữ liệu và ngược lại
```


```{r}
sum(is.na(vy1)) # cho biết tổng số ô trống trong "vy1'
```


```{r}
which(is.na(vy1)) # cho biết vị trí ô trống trong "vy1"
```


## **. Xử lý dữ liệu bị trùng lắp**
***

```{r}
library(tidyverse)
vy <- unique(vy1) #lấy lượng biến của "vy1"
str(vy)
```


```{r}
vyy <- distinct(vy1) #Loại bỏ trung lắp trong "vy1"
str(vyy)
```

## **. Rút trích dữ liệu**
***

Mục đích của việc rút trích dữ liệu là để thu được những trường thông tin cần thiết nhằm phục vụ cho các mục tác vụ phân tích hoặc lưu trữ.

***




```{r}
names(vy1) <- c("i", "y","b","g","p","a","h","w","s")
names(vy1)
```


```{r}
vy2 <- vy1[5,3] #gán "vy2" là giá trị quan sát 5, biến 3
str(vy2)

```


```{r}
vy3 <- vy1[1:5,4] # lấy giá trị 5 hàng đầu tiên biến "g"
str(vy3)
```

```{r}
vy4 <- vy1[c(1,2,3,4), c(3,4)] # lấy giá trị các quan sát 1,2,3,4 của biến "b" và "g"
str(vy4)
```
  
  
```{r}
vy5 <- vy1[vy1$w >=100 & vy1$w <=108,] #Lấy giá trị những quan sát có giá trị ở biến "w" lớn hơn bằng 100 và bé hơn bằng 108
str(vy1)
```
  
  
```{r}
vy6 <- vy1[vy1$w >130,] # lấy giá trị quan sát có giá trị ở biến "w" lớn hơn 130
str(vy6)
```
  
  
```{r}
vy7 <- vy1[vy1$a == 30 | vy1$a == 40,] #lấy giá trị những quan sát ở biến "a" bằng 30 hoặc bằng 40
str(vy1)
```


```{r}
vy8 <- filter(vy1,vy1$a >= 27 & vy1$g > 290) # lấy những quan sát có tuổi của mẹ lớn hơn hoặc bằng 27 và thời gian mang thai lớn hơn 290 ngày
str(vy8)
```


```{r}
library(dplyr)


```


```{r}
vy9 <- select(vy1,a,y,s) #chỉ lấy những biến tuổi của mẹ, năm lấy số liệu và hút thuốc lúc mang thai trong object "vy1"
str(vy9)
```


```{r}

vy10 <- filter(vy1,a < 27 & w > 170) %>% select (i,a,h) # lấy những biến khu vực, tuổi, chiều cao với điều kiện quan sát có tuổi bé hơn 27 và cân nặng lớn hơn 170 pound
str(vy10)
```


## **. Tạo dữ liệu mới từ dữ liệu có sẵn**
***

 Tạo ra object mới là "**vyx**" từ object cũ là "**vy1**". Có thêm các biến mới là:
 - **tmg:** thời gian mang thai tính bằng tháng
 - **gra:** trọng lượng lúc sinh tính bằng gram
 - **kha:** khả năng mang thai ở mức 30 tuổi ( trên 30 tuổi và dưới 30 tuổi)
 - **dukien:** dự kiến thời gian sinh em bé
 
```{r}

vyx <- mutate(vy1, tmg= g/30) %>% mutate(vy1, gra= b*28.3495) #thêm biến thời gian mang thai tính bằng tháng và trọng lượng lúc sinh tính bằng gram
str(vyx)


```


```{r}

vyx$kha <- ifelse(vyx$a > 30 ,'thấp', 'cao') #thêm biến xác định khả năng mang thay trong ngoài 30 tuổi
str(vyx)
```


```{r}

vyx$dukien <- case_when(vyx$g< 266 ~ 'sớm hơn dự kiến' , vyx$g < 280 ~ 'dự kiến' , vyx$g > 280 ~ ' trễ hơn dự kiến') # thêm biến dự kiến thời gian sinh
str(vyx)


```
  
  
## **. Bảng tần số**
***


```{r}
table(vyx$dukien) # tần số của biến dự kiến thời gian sinh
```


```{r}
stem(vyx$tmg) # biểu đồ nhánh của biến thời gian mang thai theo tháng
```


# **. NHIỆM VỤ 2.2**

## **. Tóm tắt**
***


Nhiệm vụ 2.2 thực hiện thao tác trên datasets **Financial Sample Excel**, là 1 dataset thống kê tình hình tài chính nổi bật của một số thị trường trên thế giới
giai đoạn 2013-2014.

## **. Mô tả cơ bản**
***

Datasets có 1006 quan sát và 16 biến như sau:


- **Segment:** thị trường
- **Country:** quốc gia
- **Product:** sản phẩm tài chính
- **Discount Band:** đánh giá mức độ rủi ro
- **Units Sold:** số lượng sản phẩm hoặc dịch vụ đã bán 
- **Manufacturing Price:** chi phí sản xuất của 1 sản phẩm dịch vụ	 -
- **Sale Price:** giá bán
- **Gross Sales:** tổng doanh thu 
- **Discounts:** chiết khấu	 
- **Sales:** doanh số bán hàng	
- **COGS:** số tiền chi trả sản xuất hoặc mua hàng hóa dịch vụ ảnh hưởng trực tiếp đến hoạt động tổ chức ( Cost of goods sold)
- **Profit:** lợi nhuận	
- **Date:** ngày giá trị 
- **Month Number:** số thứ tự tháng trong năm
- **Month Name:** tên tháng trong năm	
- **Year:** năm thu thập số liệu





```{r}


library(openxlsx)
navy <- read.xlsx("/Users/xuyenchi/Library/Containers/com.microsoft.Excel/Data/Downloads/R Code/Financial Sample.xlsx") #Đọc dữ liệu từ file excel
table <- knitr::kable(navy,format="markdown")
table 

```



```{r}
library(skimr)
skim(navy)
```


## **. Thống kê mô tả**
***

Thực hiện gán object **navy** là datasets **Financial Sample Excel**, thực hiện các lệnh trên objec **navy**, ta có được những thông tin sau:

- **navy** có 1006 quan sát và 16 biến
- Không có dữ liệu trống
- n_missing: số ô dữ liệu trống
- complete_rate: tỷ lệ ô có dữ liệu
- mean: trung bình
- sd:	độ lệch chuẩn
- p0:	giá trị min
- p25: phân vị thứ nhất
- p50: phân vị thứ hai(trung vị)	
- p75: phân vị thứ ba
- p100:	giá trị max
- hist: biểu đồ Histogram



## **. Xử lý dữ liệu bị trùng lắp**
***



```{r}
library(tidyverse)
navy1 <- unique(navy) #lấy lượng biến trong "navy"
str(navy1)
```



```{r}
navy2 <- distinct(navy) #Loại bỏ trung lắp trong "navy"
str(navy2)
```





## **. Rút trích dữ liệu**
***


Giả sử yêu cầu lấy những thông tin trong datasets đã loại bỏ trùng lặp "**navy2**" như sau:
- lấy 100 quan sát đầu tiên trong datasets 
- lấy 50 quan sát cuối trong datastest
- chọn những quan sát quốc gia **Germany**
- chọn những sản phẩm **Paseo** hoặc **Velo**
- chọn những sản phẩm **Paseo** có rủi ro trung bình
- chọn làm việc với biến **Country**,**Date** mà **Product** là **Paseo**


```{r}
navy100 <- head(navy,100)
str(navy100)
```


```{r}
navy50 <- tail(navy,50)
str(navy50)
```


```{r}
navy150 <- navy[navy$Product == 'Paseo' & navy$DiscountBand == 'Medium', ]
str(navy150)
  
  
  
```



```{r}
navy200 <- navy[navy$Country == 'Germany', ]
str(navy200)
```



```{r}
navy200 <- navy[navy$Product == 'Paseo' | navy$Product == 'Velo',]
str(navy200)
```



```{r}
library(dplyr)

navy300 <- filter(navy, Product=='Paseo') %>% select(Country,Date,)
str(navy300)

```


## **. Tạo dữ liệu mới**
***

Từ object cũ **navy** ta tạo thành object mới **navyx*, với các biến mới như sau:

- **pVND:** lợi nhuận tính bằng VND
- **tPro:** đánh giá số lượng sản phẩm bán ra


```{r}
navyx <- mutate(navy, pVND= Profit*24.550)
str(navyx)
```


```{r}
navyx$tPro <- case_when(navy$Product< 1000 ~ 'bán ra thấp' , navy$Product == 1000 ~ 'bán ra trung bình' , navy$Product > 1000 ~ ' bán ra cao') 
str(navyx)

```




```



























NHIỆM VỤ 2

Lê Ngọc Tường Vy

19:59:41, 20 - 01 - 2024