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<- read.csv ("Milk_Production.csv" , colClasses = c (NA , "numeric" ))head (data1)
EweType Diet Week MilkProd
1 2 1 0 1260
2 2 1 0 1900
3 2 1 0 1380
4 2 1 0 3910
5 2 1 0 2900
6 2 2 0 2210
'data.frame': 240 obs. of 4 variables:
$ EweType : int 2 2 2 2 2 2 2 2 2 2 ...
$ Diet : num 1 1 1 1 1 2 2 2 2 2 ...
$ Week : int 0 0 0 0 0 0 0 0 0 0 ...
$ MilkProd: num 1260 1900 1380 3910 2900 2210 1850 1750 1900 1950 ...
Rows: 240
Columns: 4
$ EweType <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1~
$ Diet <dbl> 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 2~
$ Week <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0~
$ MilkProd <dbl> 1260, 1900, 1380, 3910, 2900, 2210, 1850, 1750, 1900, 1950, 1~
$ EweType<- as.factor (data1$ EweType)$ Diet<- as.factor (data1$ Diet)$ Week <- as.integer (data1$ Week)$ MilkProd<- as.numeric (data1$ MilkProd)tail (data1)
EweType Diet Week MilkProd
235 1 2 7 1000
236 1 3 7 550
237 1 3 7 820
238 1 3 7 520
239 1 3 7 630
240 1 3 7 500
###Question 1#### %>% arrange (Week)
EweType Diet Week MilkProd
1 2 1 0 1260
2 2 1 0 1900
3 2 1 0 1380
4 2 1 0 3910
5 2 1 0 2900
6 2 2 0 2210
7 2 2 0 1850
8 2 2 0 1750
9 2 2 0 1900
10 2 2 0 1950
11 2 3 0 1190
12 2 3 0 1190
13 2 3 0 590
14 2 3 0 1410
15 2 3 0 1320
16 1 1 0 4120
17 1 1 0 3530
18 1 1 0 1940
19 1 1 0 3130
20 1 1 0 3230
21 1 2 0 1480
22 1 2 0 2180
23 1 2 0 2610
24 1 2 0 2320
25 1 2 0 1740
26 1 3 0 1740
27 1 3 0 1680
28 1 3 0 1890
29 1 3 0 1970
30 1 3 0 2770
31 2 1 1 1640
32 2 1 1 2570
33 2 1 1 2760
34 2 1 1 3190
35 2 1 1 2440
36 2 2 1 2330
37 2 2 1 930
38 2 2 1 1810
39 2 2 1 1500
40 2 2 1 1800
41 2 3 1 760
42 2 3 1 1030
43 2 3 1 910
44 2 3 1 990
45 2 3 1 950
46 1 1 1 4810
47 1 1 1 3040
48 1 1 1 2000
49 1 1 1 2440
50 1 1 1 4040
51 1 2 1 1870
52 1 2 1 1700
53 1 2 1 1850
54 1 2 1 1420
55 1 2 1 1260
56 1 3 1 1190
57 1 3 1 1240
58 1 3 1 1380
59 1 3 1 1170
60 1 3 1 1790
61 2 1 2 1080
62 2 1 2 1100
63 2 1 2 1550
64 2 1 2 1050
65 2 1 2 1280
66 2 2 2 1700
67 2 2 2 850
68 2 2 2 1540
69 2 2 2 950
70 2 2 2 1350
71 2 3 2 540
72 2 3 2 700
73 2 3 2 600
74 2 3 2 750
75 2 3 2 700
76 1 1 2 1850
77 1 1 2 1380
78 1 1 2 1650
79 1 1 2 1230
80 1 1 2 1580
81 1 2 2 1500
82 1 2 2 1380
83 1 2 2 1120
84 1 2 2 1130
85 1 2 2 860
86 1 3 2 960
87 1 3 2 1080
88 1 3 2 1120
89 1 3 2 960
90 1 3 2 1020
91 2 1 3 1000
92 2 1 3 1520
93 2 1 3 980
94 2 1 3 1180
95 2 1 3 1540
96 2 2 3 1180
97 2 2 3 780
98 2 2 3 1210
99 2 2 3 500
100 2 2 3 1000
101 2 3 3 500
102 2 3 3 500
103 2 3 3 320
104 2 3 3 240
105 2 3 3 460
106 1 1 3 1600
107 1 1 3 1250
108 1 1 3 1420
109 1 1 3 1020
110 1 1 3 1450
111 1 2 3 1300
112 1 2 3 1100
113 1 2 3 750
114 1 2 3 900
115 1 2 3 640
116 1 3 3 600
117 1 3 3 980
118 1 3 3 940
119 1 3 3 750
120 1 3 3 570
121 2 1 4 950
122 2 1 4 1200
123 2 1 4 1380
124 2 1 4 980
125 2 1 4 740
126 2 2 4 890
127 2 2 4 380
128 2 2 4 810
129 2 2 4 260
130 2 2 4 800
131 2 3 4 370
132 2 3 4 350
133 2 3 4 250
134 2 3 4 170
135 2 3 4 380
136 1 1 4 1680
137 1 1 4 1200
138 1 1 4 960
139 1 1 4 1100
140 1 1 4 620
141 1 2 4 900
142 1 2 4 720
143 1 2 4 680
144 1 2 4 480
145 1 2 4 800
146 1 3 4 700
147 1 3 4 800
148 1 3 4 680
149 1 3 4 400
150 1 3 4 420
151 2 1 5 1000
152 2 1 5 1300
153 2 1 5 1000
154 2 1 5 850
155 2 1 5 800
156 2 2 5 850
157 2 2 5 300
158 2 2 5 600
159 2 2 5 300
160 2 2 5 650
161 2 3 5 250
162 2 3 5 250
163 2 3 5 200
164 2 3 5 100
165 2 3 5 270
166 1 1 5 1380
167 1 1 5 920
168 1 1 5 1280
169 1 1 5 1120
170 1 1 5 800
171 1 2 5 640
172 1 2 5 800
173 1 2 5 420
174 1 2 5 380
175 1 2 5 900
176 1 3 5 660
177 1 3 5 760
178 1 3 5 640
179 1 3 5 480
180 1 3 5 460
181 2 1 6 900
182 2 1 6 1350
183 2 1 6 1300
184 2 1 6 1100
185 2 1 6 600
186 2 2 6 750
187 2 2 6 560
188 2 2 6 750
189 2 2 6 250
190 2 2 6 600
191 2 3 6 360
192 2 3 6 300
193 2 3 6 150
194 2 3 6 200
195 2 3 6 200
196 1 1 6 1100
197 1 1 6 850
198 1 1 6 1100
199 1 1 6 1200
200 1 1 6 750
201 1 2 6 400
202 1 2 6 520
203 1 2 6 500
204 1 2 6 400
205 1 2 6 950
206 1 3 6 650
207 1 3 6 900
208 1 3 6 850
209 1 3 6 500
210 1 3 6 400
211 2 1 7 800
212 2 1 7 1250
213 2 1 7 1050
214 2 1 7 950
215 2 1 7 500
216 2 2 7 600
217 2 2 7 350
218 2 2 7 500
219 2 2 7 200
220 2 2 7 500
221 2 3 7 300
222 2 3 7 100
223 2 3 7 100
224 2 3 7 200
225 2 3 7 100
226 1 1 7 1000
227 1 1 7 1150
228 1 1 7 1120
229 1 1 7 1450
230 1 1 7 660
231 1 2 7 780
232 1 2 7 620
233 1 2 7 550
234 1 2 7 450
235 1 2 7 1000
236 1 3 7 550
237 1 3 7 820
238 1 3 7 520
239 1 3 7 630
240 1 3 7 500
%>% arrange (EweType)
EweType Diet Week MilkProd
1 1 1 0 4120
2 1 1 0 3530
3 1 1 0 1940
4 1 1 0 3130
5 1 1 0 3230
6 1 2 0 1480
7 1 2 0 2180
8 1 2 0 2610
9 1 2 0 2320
10 1 2 0 1740
11 1 3 0 1740
12 1 3 0 1680
13 1 3 0 1890
14 1 3 0 1970
15 1 3 0 2770
16 1 1 1 4810
17 1 1 1 3040
18 1 1 1 2000
19 1 1 1 2440
20 1 1 1 4040
21 1 2 1 1870
22 1 2 1 1700
23 1 2 1 1850
24 1 2 1 1420
25 1 2 1 1260
26 1 3 1 1190
27 1 3 1 1240
28 1 3 1 1380
29 1 3 1 1170
30 1 3 1 1790
31 1 1 2 1850
32 1 1 2 1380
33 1 1 2 1650
34 1 1 2 1230
35 1 1 2 1580
36 1 2 2 1500
37 1 2 2 1380
38 1 2 2 1120
39 1 2 2 1130
40 1 2 2 860
41 1 3 2 960
42 1 3 2 1080
43 1 3 2 1120
44 1 3 2 960
45 1 3 2 1020
46 1 1 3 1600
47 1 1 3 1250
48 1 1 3 1420
49 1 1 3 1020
50 1 1 3 1450
51 1 2 3 1300
52 1 2 3 1100
53 1 2 3 750
54 1 2 3 900
55 1 2 3 640
56 1 3 3 600
57 1 3 3 980
58 1 3 3 940
59 1 3 3 750
60 1 3 3 570
61 1 1 4 1680
62 1 1 4 1200
63 1 1 4 960
64 1 1 4 1100
65 1 1 4 620
66 1 2 4 900
67 1 2 4 720
68 1 2 4 680
69 1 2 4 480
70 1 2 4 800
71 1 3 4 700
72 1 3 4 800
73 1 3 4 680
74 1 3 4 400
75 1 3 4 420
76 1 1 5 1380
77 1 1 5 920
78 1 1 5 1280
79 1 1 5 1120
80 1 1 5 800
81 1 2 5 640
82 1 2 5 800
83 1 2 5 420
84 1 2 5 380
85 1 2 5 900
86 1 3 5 660
87 1 3 5 760
88 1 3 5 640
89 1 3 5 480
90 1 3 5 460
91 1 1 6 1100
92 1 1 6 850
93 1 1 6 1100
94 1 1 6 1200
95 1 1 6 750
96 1 2 6 400
97 1 2 6 520
98 1 2 6 500
99 1 2 6 400
100 1 2 6 950
101 1 3 6 650
102 1 3 6 900
103 1 3 6 850
104 1 3 6 500
105 1 3 6 400
106 1 1 7 1000
107 1 1 7 1150
108 1 1 7 1120
109 1 1 7 1450
110 1 1 7 660
111 1 2 7 780
112 1 2 7 620
113 1 2 7 550
114 1 2 7 450
115 1 2 7 1000
116 1 3 7 550
117 1 3 7 820
118 1 3 7 520
119 1 3 7 630
120 1 3 7 500
121 2 1 0 1260
122 2 1 0 1900
123 2 1 0 1380
124 2 1 0 3910
125 2 1 0 2900
126 2 2 0 2210
127 2 2 0 1850
128 2 2 0 1750
129 2 2 0 1900
130 2 2 0 1950
131 2 3 0 1190
132 2 3 0 1190
133 2 3 0 590
134 2 3 0 1410
135 2 3 0 1320
136 2 1 1 1640
137 2 1 1 2570
138 2 1 1 2760
139 2 1 1 3190
140 2 1 1 2440
141 2 2 1 2330
142 2 2 1 930
143 2 2 1 1810
144 2 2 1 1500
145 2 2 1 1800
146 2 3 1 760
147 2 3 1 1030
148 2 3 1 910
149 2 3 1 990
150 2 3 1 950
151 2 1 2 1080
152 2 1 2 1100
153 2 1 2 1550
154 2 1 2 1050
155 2 1 2 1280
156 2 2 2 1700
157 2 2 2 850
158 2 2 2 1540
159 2 2 2 950
160 2 2 2 1350
161 2 3 2 540
162 2 3 2 700
163 2 3 2 600
164 2 3 2 750
165 2 3 2 700
166 2 1 3 1000
167 2 1 3 1520
168 2 1 3 980
169 2 1 3 1180
170 2 1 3 1540
171 2 2 3 1180
172 2 2 3 780
173 2 2 3 1210
174 2 2 3 500
175 2 2 3 1000
176 2 3 3 500
177 2 3 3 500
178 2 3 3 320
179 2 3 3 240
180 2 3 3 460
181 2 1 4 950
182 2 1 4 1200
183 2 1 4 1380
184 2 1 4 980
185 2 1 4 740
186 2 2 4 890
187 2 2 4 380
188 2 2 4 810
189 2 2 4 260
190 2 2 4 800
191 2 3 4 370
192 2 3 4 350
193 2 3 4 250
194 2 3 4 170
195 2 3 4 380
196 2 1 5 1000
197 2 1 5 1300
198 2 1 5 1000
199 2 1 5 850
200 2 1 5 800
201 2 2 5 850
202 2 2 5 300
203 2 2 5 600
204 2 2 5 300
205 2 2 5 650
206 2 3 5 250
207 2 3 5 250
208 2 3 5 200
209 2 3 5 100
210 2 3 5 270
211 2 1 6 900
212 2 1 6 1350
213 2 1 6 1300
214 2 1 6 1100
215 2 1 6 600
216 2 2 6 750
217 2 2 6 560
218 2 2 6 750
219 2 2 6 250
220 2 2 6 600
221 2 3 6 360
222 2 3 6 300
223 2 3 6 150
224 2 3 6 200
225 2 3 6 200
226 2 1 7 800
227 2 1 7 1250
228 2 1 7 1050
229 2 1 7 950
230 2 1 7 500
231 2 2 7 600
232 2 2 7 350
233 2 2 7 500
234 2 2 7 200
235 2 2 7 500
236 2 3 7 300
237 2 3 7 100
238 2 3 7 100
239 2 3 7 200
240 2 3 7 100
%>% arrange (desc (Week))
EweType Diet Week MilkProd
1 2 1 7 800
2 2 1 7 1250
3 2 1 7 1050
4 2 1 7 950
5 2 1 7 500
6 2 2 7 600
7 2 2 7 350
8 2 2 7 500
9 2 2 7 200
10 2 2 7 500
11 2 3 7 300
12 2 3 7 100
13 2 3 7 100
14 2 3 7 200
15 2 3 7 100
16 1 1 7 1000
17 1 1 7 1150
18 1 1 7 1120
19 1 1 7 1450
20 1 1 7 660
21 1 2 7 780
22 1 2 7 620
23 1 2 7 550
24 1 2 7 450
25 1 2 7 1000
26 1 3 7 550
27 1 3 7 820
28 1 3 7 520
29 1 3 7 630
30 1 3 7 500
31 2 1 6 900
32 2 1 6 1350
33 2 1 6 1300
34 2 1 6 1100
35 2 1 6 600
36 2 2 6 750
37 2 2 6 560
38 2 2 6 750
39 2 2 6 250
40 2 2 6 600
41 2 3 6 360
42 2 3 6 300
43 2 3 6 150
44 2 3 6 200
45 2 3 6 200
46 1 1 6 1100
47 1 1 6 850
48 1 1 6 1100
49 1 1 6 1200
50 1 1 6 750
51 1 2 6 400
52 1 2 6 520
53 1 2 6 500
54 1 2 6 400
55 1 2 6 950
56 1 3 6 650
57 1 3 6 900
58 1 3 6 850
59 1 3 6 500
60 1 3 6 400
61 2 1 5 1000
62 2 1 5 1300
63 2 1 5 1000
64 2 1 5 850
65 2 1 5 800
66 2 2 5 850
67 2 2 5 300
68 2 2 5 600
69 2 2 5 300
70 2 2 5 650
71 2 3 5 250
72 2 3 5 250
73 2 3 5 200
74 2 3 5 100
75 2 3 5 270
76 1 1 5 1380
77 1 1 5 920
78 1 1 5 1280
79 1 1 5 1120
80 1 1 5 800
81 1 2 5 640
82 1 2 5 800
83 1 2 5 420
84 1 2 5 380
85 1 2 5 900
86 1 3 5 660
87 1 3 5 760
88 1 3 5 640
89 1 3 5 480
90 1 3 5 460
91 2 1 4 950
92 2 1 4 1200
93 2 1 4 1380
94 2 1 4 980
95 2 1 4 740
96 2 2 4 890
97 2 2 4 380
98 2 2 4 810
99 2 2 4 260
100 2 2 4 800
101 2 3 4 370
102 2 3 4 350
103 2 3 4 250
104 2 3 4 170
105 2 3 4 380
106 1 1 4 1680
107 1 1 4 1200
108 1 1 4 960
109 1 1 4 1100
110 1 1 4 620
111 1 2 4 900
112 1 2 4 720
113 1 2 4 680
114 1 2 4 480
115 1 2 4 800
116 1 3 4 700
117 1 3 4 800
118 1 3 4 680
119 1 3 4 400
120 1 3 4 420
121 2 1 3 1000
122 2 1 3 1520
123 2 1 3 980
124 2 1 3 1180
125 2 1 3 1540
126 2 2 3 1180
127 2 2 3 780
128 2 2 3 1210
129 2 2 3 500
130 2 2 3 1000
131 2 3 3 500
132 2 3 3 500
133 2 3 3 320
134 2 3 3 240
135 2 3 3 460
136 1 1 3 1600
137 1 1 3 1250
138 1 1 3 1420
139 1 1 3 1020
140 1 1 3 1450
141 1 2 3 1300
142 1 2 3 1100
143 1 2 3 750
144 1 2 3 900
145 1 2 3 640
146 1 3 3 600
147 1 3 3 980
148 1 3 3 940
149 1 3 3 750
150 1 3 3 570
151 2 1 2 1080
152 2 1 2 1100
153 2 1 2 1550
154 2 1 2 1050
155 2 1 2 1280
156 2 2 2 1700
157 2 2 2 850
158 2 2 2 1540
159 2 2 2 950
160 2 2 2 1350
161 2 3 2 540
162 2 3 2 700
163 2 3 2 600
164 2 3 2 750
165 2 3 2 700
166 1 1 2 1850
167 1 1 2 1380
168 1 1 2 1650
169 1 1 2 1230
170 1 1 2 1580
171 1 2 2 1500
172 1 2 2 1380
173 1 2 2 1120
174 1 2 2 1130
175 1 2 2 860
176 1 3 2 960
177 1 3 2 1080
178 1 3 2 1120
179 1 3 2 960
180 1 3 2 1020
181 2 1 1 1640
182 2 1 1 2570
183 2 1 1 2760
184 2 1 1 3190
185 2 1 1 2440
186 2 2 1 2330
187 2 2 1 930
188 2 2 1 1810
189 2 2 1 1500
190 2 2 1 1800
191 2 3 1 760
192 2 3 1 1030
193 2 3 1 910
194 2 3 1 990
195 2 3 1 950
196 1 1 1 4810
197 1 1 1 3040
198 1 1 1 2000
199 1 1 1 2440
200 1 1 1 4040
201 1 2 1 1870
202 1 2 1 1700
203 1 2 1 1850
204 1 2 1 1420
205 1 2 1 1260
206 1 3 1 1190
207 1 3 1 1240
208 1 3 1 1380
209 1 3 1 1170
210 1 3 1 1790
211 2 1 0 1260
212 2 1 0 1900
213 2 1 0 1380
214 2 1 0 3910
215 2 1 0 2900
216 2 2 0 2210
217 2 2 0 1850
218 2 2 0 1750
219 2 2 0 1900
220 2 2 0 1950
221 2 3 0 1190
222 2 3 0 1190
223 2 3 0 590
224 2 3 0 1410
225 2 3 0 1320
226 1 1 0 4120
227 1 1 0 3530
228 1 1 0 1940
229 1 1 0 3130
230 1 1 0 3230
231 1 2 0 1480
232 1 2 0 2180
233 1 2 0 2610
234 1 2 0 2320
235 1 2 0 1740
236 1 3 0 1740
237 1 3 0 1680
238 1 3 0 1890
239 1 3 0 1970
240 1 3 0 2770
%>% arrange (desc (MilkProd))
EweType Diet Week MilkProd
1 1 1 1 4810
2 1 1 0 4120
3 1 1 1 4040
4 2 1 0 3910
5 1 1 0 3530
6 1 1 0 3230
7 2 1 1 3190
8 1 1 0 3130
9 1 1 1 3040
10 2 1 0 2900
11 1 3 0 2770
12 2 1 1 2760
13 1 2 0 2610
14 2 1 1 2570
15 2 1 1 2440
16 1 1 1 2440
17 2 2 1 2330
18 1 2 0 2320
19 2 2 0 2210
20 1 2 0 2180
21 1 1 1 2000
22 1 3 0 1970
23 2 2 0 1950
24 1 1 0 1940
25 2 1 0 1900
26 2 2 0 1900
27 1 3 0 1890
28 1 2 1 1870
29 2 2 0 1850
30 1 2 1 1850
31 1 1 2 1850
32 2 2 1 1810
33 2 2 1 1800
34 1 3 1 1790
35 2 2 0 1750
36 1 2 0 1740
37 1 3 0 1740
38 1 2 1 1700
39 2 2 2 1700
40 1 3 0 1680
41 1 1 4 1680
42 1 1 2 1650
43 2 1 1 1640
44 1 1 3 1600
45 1 1 2 1580
46 2 1 2 1550
47 2 2 2 1540
48 2 1 3 1540
49 2 1 3 1520
50 2 2 1 1500
51 1 2 2 1500
52 1 2 0 1480
53 1 1 3 1450
54 1 1 7 1450
55 1 2 1 1420
56 1 1 3 1420
57 2 3 0 1410
58 2 1 0 1380
59 1 3 1 1380
60 1 1 2 1380
61 1 2 2 1380
62 2 1 4 1380
63 1 1 5 1380
64 2 2 2 1350
65 2 1 6 1350
66 2 3 0 1320
67 1 2 3 1300
68 2 1 5 1300
69 2 1 6 1300
70 2 1 2 1280
71 1 1 5 1280
72 2 1 0 1260
73 1 2 1 1260
74 1 1 3 1250
75 2 1 7 1250
76 1 3 1 1240
77 1 1 2 1230
78 2 2 3 1210
79 2 1 4 1200
80 1 1 4 1200
81 1 1 6 1200
82 2 3 0 1190
83 2 3 0 1190
84 1 3 1 1190
85 2 1 3 1180
86 2 2 3 1180
87 1 3 1 1170
88 1 1 7 1150
89 1 2 2 1130
90 1 2 2 1120
91 1 3 2 1120
92 1 1 5 1120
93 1 1 7 1120
94 2 1 2 1100
95 1 2 3 1100
96 1 1 4 1100
97 2 1 6 1100
98 1 1 6 1100
99 1 1 6 1100
100 2 1 2 1080
101 1 3 2 1080
102 2 1 2 1050
103 2 1 7 1050
104 2 3 1 1030
105 1 3 2 1020
106 1 1 3 1020
107 2 1 3 1000
108 2 2 3 1000
109 2 1 5 1000
110 2 1 5 1000
111 1 1 7 1000
112 1 2 7 1000
113 2 3 1 990
114 2 1 3 980
115 1 3 3 980
116 2 1 4 980
117 1 3 2 960
118 1 3 2 960
119 1 1 4 960
120 2 3 1 950
121 2 2 2 950
122 2 1 4 950
123 1 2 6 950
124 2 1 7 950
125 1 3 3 940
126 2 2 1 930
127 1 1 5 920
128 2 3 1 910
129 1 2 3 900
130 1 2 4 900
131 1 2 5 900
132 2 1 6 900
133 1 3 6 900
134 2 2 4 890
135 1 2 2 860
136 2 2 2 850
137 2 1 5 850
138 2 2 5 850
139 1 1 6 850
140 1 3 6 850
141 1 3 7 820
142 2 2 4 810
143 2 2 4 800
144 1 2 4 800
145 1 3 4 800
146 2 1 5 800
147 1 1 5 800
148 1 2 5 800
149 2 1 7 800
150 2 2 3 780
151 1 2 7 780
152 2 3 1 760
153 1 3 5 760
154 2 3 2 750
155 1 2 3 750
156 1 3 3 750
157 2 2 6 750
158 2 2 6 750
159 1 1 6 750
160 2 1 4 740
161 1 2 4 720
162 2 3 2 700
163 2 3 2 700
164 1 3 4 700
165 1 2 4 680
166 1 3 4 680
167 1 3 5 660
168 1 1 7 660
169 2 2 5 650
170 1 3 6 650
171 1 2 3 640
172 1 2 5 640
173 1 3 5 640
174 1 3 7 630
175 1 1 4 620
176 1 2 7 620
177 2 3 2 600
178 1 3 3 600
179 2 2 5 600
180 2 1 6 600
181 2 2 6 600
182 2 2 7 600
183 2 3 0 590
184 1 3 3 570
185 2 2 6 560
186 1 2 7 550
187 1 3 7 550
188 2 3 2 540
189 1 2 6 520
190 1 3 7 520
191 2 2 3 500
192 2 3 3 500
193 2 3 3 500
194 1 2 6 500
195 1 3 6 500
196 2 1 7 500
197 2 2 7 500
198 2 2 7 500
199 1 3 7 500
200 1 2 4 480
201 1 3 5 480
202 2 3 3 460
203 1 3 5 460
204 1 2 7 450
205 1 3 4 420
206 1 2 5 420
207 1 3 4 400
208 1 2 6 400
209 1 2 6 400
210 1 3 6 400
211 2 2 4 380
212 2 3 4 380
213 1 2 5 380
214 2 3 4 370
215 2 3 6 360
216 2 3 4 350
217 2 2 7 350
218 2 3 3 320
219 2 2 5 300
220 2 2 5 300
221 2 3 6 300
222 2 3 7 300
223 2 3 5 270
224 2 2 4 260
225 2 3 4 250
226 2 3 5 250
227 2 3 5 250
228 2 2 6 250
229 2 3 3 240
230 2 3 5 200
231 2 3 6 200
232 2 3 6 200
233 2 2 7 200
234 2 3 7 200
235 2 3 4 170
236 2 3 6 150
237 2 3 5 100
238 2 3 7 100
239 2 3 7 100
240 2 3 7 100
%>% filter (Week == "7" )
EweType Diet Week MilkProd
1 2 1 7 800
2 2 1 7 1250
3 2 1 7 1050
4 2 1 7 950
5 2 1 7 500
6 2 2 7 600
7 2 2 7 350
8 2 2 7 500
9 2 2 7 200
10 2 2 7 500
11 2 3 7 300
12 2 3 7 100
13 2 3 7 100
14 2 3 7 200
15 2 3 7 100
16 1 1 7 1000
17 1 1 7 1150
18 1 1 7 1120
19 1 1 7 1450
20 1 1 7 660
21 1 2 7 780
22 1 2 7 620
23 1 2 7 550
24 1 2 7 450
25 1 2 7 1000
26 1 3 7 550
27 1 3 7 820
28 1 3 7 520
29 1 3 7 630
30 1 3 7 500
[1] FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE
[13] FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE
[25] FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE
[49] TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[157] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[169] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[181] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[193] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[205] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[217] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[229] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
%>% filter (Week != 0 )
EweType Diet Week MilkProd
1 2 1 1 1640
2 2 1 1 2570
3 2 1 1 2760
4 2 1 1 3190
5 2 1 1 2440
6 2 2 1 2330
7 2 2 1 930
8 2 2 1 1810
9 2 2 1 1500
10 2 2 1 1800
11 2 3 1 760
12 2 3 1 1030
13 2 3 1 910
14 2 3 1 990
15 2 3 1 950
16 1 1 1 4810
17 1 1 1 3040
18 1 1 1 2000
19 1 1 1 2440
20 1 1 1 4040
21 1 2 1 1870
22 1 2 1 1700
23 1 2 1 1850
24 1 2 1 1420
25 1 2 1 1260
26 1 3 1 1190
27 1 3 1 1240
28 1 3 1 1380
29 1 3 1 1170
30 1 3 1 1790
31 2 1 2 1080
32 2 1 2 1100
33 2 1 2 1550
34 2 1 2 1050
35 2 1 2 1280
36 2 2 2 1700
37 2 2 2 850
38 2 2 2 1540
39 2 2 2 950
40 2 2 2 1350
41 2 3 2 540
42 2 3 2 700
43 2 3 2 600
44 2 3 2 750
45 2 3 2 700
46 1 1 2 1850
47 1 1 2 1380
48 1 1 2 1650
49 1 1 2 1230
50 1 1 2 1580
51 1 2 2 1500
52 1 2 2 1380
53 1 2 2 1120
54 1 2 2 1130
55 1 2 2 860
56 1 3 2 960
57 1 3 2 1080
58 1 3 2 1120
59 1 3 2 960
60 1 3 2 1020
61 2 1 3 1000
62 2 1 3 1520
63 2 1 3 980
64 2 1 3 1180
65 2 1 3 1540
66 2 2 3 1180
67 2 2 3 780
68 2 2 3 1210
69 2 2 3 500
70 2 2 3 1000
71 2 3 3 500
72 2 3 3 500
73 2 3 3 320
74 2 3 3 240
75 2 3 3 460
76 1 1 3 1600
77 1 1 3 1250
78 1 1 3 1420
79 1 1 3 1020
80 1 1 3 1450
81 1 2 3 1300
82 1 2 3 1100
83 1 2 3 750
84 1 2 3 900
85 1 2 3 640
86 1 3 3 600
87 1 3 3 980
88 1 3 3 940
89 1 3 3 750
90 1 3 3 570
91 2 1 4 950
92 2 1 4 1200
93 2 1 4 1380
94 2 1 4 980
95 2 1 4 740
96 2 2 4 890
97 2 2 4 380
98 2 2 4 810
99 2 2 4 260
100 2 2 4 800
101 2 3 4 370
102 2 3 4 350
103 2 3 4 250
104 2 3 4 170
105 2 3 4 380
106 1 1 4 1680
107 1 1 4 1200
108 1 1 4 960
109 1 1 4 1100
110 1 1 4 620
111 1 2 4 900
112 1 2 4 720
113 1 2 4 680
114 1 2 4 480
115 1 2 4 800
116 1 3 4 700
117 1 3 4 800
118 1 3 4 680
119 1 3 4 400
120 1 3 4 420
121 2 1 5 1000
122 2 1 5 1300
123 2 1 5 1000
124 2 1 5 850
125 2 1 5 800
126 2 2 5 850
127 2 2 5 300
128 2 2 5 600
129 2 2 5 300
130 2 2 5 650
131 2 3 5 250
132 2 3 5 250
133 2 3 5 200
134 2 3 5 100
135 2 3 5 270
136 1 1 5 1380
137 1 1 5 920
138 1 1 5 1280
139 1 1 5 1120
140 1 1 5 800
141 1 2 5 640
142 1 2 5 800
143 1 2 5 420
144 1 2 5 380
145 1 2 5 900
146 1 3 5 660
147 1 3 5 760
148 1 3 5 640
149 1 3 5 480
150 1 3 5 460
151 2 1 6 900
152 2 1 6 1350
153 2 1 6 1300
154 2 1 6 1100
155 2 1 6 600
156 2 2 6 750
157 2 2 6 560
158 2 2 6 750
159 2 2 6 250
160 2 2 6 600
161 2 3 6 360
162 2 3 6 300
163 2 3 6 150
164 2 3 6 200
165 2 3 6 200
166 1 1 6 1100
167 1 1 6 850
168 1 1 6 1100
169 1 1 6 1200
170 1 1 6 750
171 1 2 6 400
172 1 2 6 520
173 1 2 6 500
174 1 2 6 400
175 1 2 6 950
176 1 3 6 650
177 1 3 6 900
178 1 3 6 850
179 1 3 6 500
180 1 3 6 400
181 2 1 7 800
182 2 1 7 1250
183 2 1 7 1050
184 2 1 7 950
185 2 1 7 500
186 2 2 7 600
187 2 2 7 350
188 2 2 7 500
189 2 2 7 200
190 2 2 7 500
191 2 3 7 300
192 2 3 7 100
193 2 3 7 100
194 2 3 7 200
195 2 3 7 100
196 1 1 7 1000
197 1 1 7 1150
198 1 1 7 1120
199 1 1 7 1450
200 1 1 7 660
201 1 2 7 780
202 1 2 7 620
203 1 2 7 550
204 1 2 7 450
205 1 2 7 1000
206 1 3 7 550
207 1 3 7 820
208 1 3 7 520
209 1 3 7 630
210 1 3 7 500
%>% filter (EweType == "1" , Week == "0" )
EweType Diet Week MilkProd
1 1 1 0 4120
2 1 1 0 3530
3 1 1 0 1940
4 1 1 0 3130
5 1 1 0 3230
6 1 2 0 1480
7 1 2 0 2180
8 1 2 0 2610
9 1 2 0 2320
10 1 2 0 1740
11 1 3 0 1740
12 1 3 0 1680
13 1 3 0 1890
14 1 3 0 1970
15 1 3 0 2770
%>% filter (EweType == "1" , Week == "1" )
EweType Diet Week MilkProd
1 1 1 1 4810
2 1 1 1 3040
3 1 1 1 2000
4 1 1 1 2440
5 1 1 1 4040
6 1 2 1 1870
7 1 2 1 1700
8 1 2 1 1850
9 1 2 1 1420
10 1 2 1 1260
11 1 3 1 1190
12 1 3 1 1240
13 1 3 1 1380
14 1 3 1 1170
15 1 3 1 1790
%>% slice_head (n= 5 )
EweType Diet Week MilkProd
1 2 1 0 1260
2 2 1 0 1900
3 2 1 0 1380
4 2 1 0 3910
5 2 1 0 2900
%>% slice_sample (prop = 0.20 )
EweType Diet Week MilkProd
1 1 1 0 3230
2 1 3 0 1970
3 1 3 3 600
4 1 1 5 1380
5 1 3 1 1170
6 1 3 6 650
7 2 1 6 1100
8 1 1 7 1120
9 2 1 1 2760
10 1 1 1 4810
11 2 2 5 600
12 1 1 7 1150
13 1 3 4 420
14 1 1 1 3040
15 2 2 4 810
16 2 3 0 1320
17 2 1 7 1050
18 2 3 5 250
19 2 2 1 1500
20 1 1 4 1680
21 1 2 4 480
22 2 2 6 750
23 1 2 5 640
24 1 2 3 900
25 2 1 3 980
26 2 2 4 380
27 1 3 5 640
28 1 2 6 520
29 1 3 5 480
30 1 3 6 400
31 2 2 6 750
32 2 1 2 1050
33 2 3 5 270
34 2 3 3 500
35 1 2 2 1500
36 2 2 1 930
37 1 2 7 620
38 1 2 0 1740
39 1 2 4 720
40 1 3 3 750
41 1 3 2 1080
42 1 3 6 900
43 1 1 0 4120
44 2 3 6 360
45 2 2 6 560
46 1 1 4 620
47 1 3 0 1890
48 2 2 7 500
%>% slice_min (MilkProd, n= 5 )
EweType Diet Week MilkProd
1 2 3 5 100
2 2 3 7 100
3 2 3 7 100
4 2 3 7 100
5 2 3 6 150
%>% select (Week, MilkProd)
Week MilkProd
1 0 1260
2 0 1900
3 0 1380
4 0 3910
5 0 2900
6 0 2210
7 0 1850
8 0 1750
9 0 1900
10 0 1950
11 0 1190
12 0 1190
13 0 590
14 0 1410
15 0 1320
16 0 4120
17 0 3530
18 0 1940
19 0 3130
20 0 3230
21 0 1480
22 0 2180
23 0 2610
24 0 2320
25 0 1740
26 0 1740
27 0 1680
28 0 1890
29 0 1970
30 0 2770
31 1 1640
32 1 2570
33 1 2760
34 1 3190
35 1 2440
36 1 2330
37 1 930
38 1 1810
39 1 1500
40 1 1800
41 1 760
42 1 1030
43 1 910
44 1 990
45 1 950
46 1 4810
47 1 3040
48 1 2000
49 1 2440
50 1 4040
51 1 1870
52 1 1700
53 1 1850
54 1 1420
55 1 1260
56 1 1190
57 1 1240
58 1 1380
59 1 1170
60 1 1790
61 2 1080
62 2 1100
63 2 1550
64 2 1050
65 2 1280
66 2 1700
67 2 850
68 2 1540
69 2 950
70 2 1350
71 2 540
72 2 700
73 2 600
74 2 750
75 2 700
76 2 1850
77 2 1380
78 2 1650
79 2 1230
80 2 1580
81 2 1500
82 2 1380
83 2 1120
84 2 1130
85 2 860
86 2 960
87 2 1080
88 2 1120
89 2 960
90 2 1020
91 3 1000
92 3 1520
93 3 980
94 3 1180
95 3 1540
96 3 1180
97 3 780
98 3 1210
99 3 500
100 3 1000
101 3 500
102 3 500
103 3 320
104 3 240
105 3 460
106 3 1600
107 3 1250
108 3 1420
109 3 1020
110 3 1450
111 3 1300
112 3 1100
113 3 750
114 3 900
115 3 640
116 3 600
117 3 980
118 3 940
119 3 750
120 3 570
121 4 950
122 4 1200
123 4 1380
124 4 980
125 4 740
126 4 890
127 4 380
128 4 810
129 4 260
130 4 800
131 4 370
132 4 350
133 4 250
134 4 170
135 4 380
136 4 1680
137 4 1200
138 4 960
139 4 1100
140 4 620
141 4 900
142 4 720
143 4 680
144 4 480
145 4 800
146 4 700
147 4 800
148 4 680
149 4 400
150 4 420
151 5 1000
152 5 1300
153 5 1000
154 5 850
155 5 800
156 5 850
157 5 300
158 5 600
159 5 300
160 5 650
161 5 250
162 5 250
163 5 200
164 5 100
165 5 270
166 5 1380
167 5 920
168 5 1280
169 5 1120
170 5 800
171 5 640
172 5 800
173 5 420
174 5 380
175 5 900
176 5 660
177 5 760
178 5 640
179 5 480
180 5 460
181 6 900
182 6 1350
183 6 1300
184 6 1100
185 6 600
186 6 750
187 6 560
188 6 750
189 6 250
190 6 600
191 6 360
192 6 300
193 6 150
194 6 200
195 6 200
196 6 1100
197 6 850
198 6 1100
199 6 1200
200 6 750
201 6 400
202 6 520
203 6 500
204 6 400
205 6 950
206 6 650
207 6 900
208 6 850
209 6 500
210 6 400
211 7 800
212 7 1250
213 7 1050
214 7 950
215 7 500
216 7 600
217 7 350
218 7 500
219 7 200
220 7 500
221 7 300
222 7 100
223 7 100
224 7 200
225 7 100
226 7 1000
227 7 1150
228 7 1120
229 7 1450
230 7 660
231 7 780
232 7 620
233 7 550
234 7 450
235 7 1000
236 7 550
237 7 820
238 7 520
239 7 630
240 7 500
%>% select (- EweType)
Diet Week MilkProd
1 1 0 1260
2 1 0 1900
3 1 0 1380
4 1 0 3910
5 1 0 2900
6 2 0 2210
7 2 0 1850
8 2 0 1750
9 2 0 1900
10 2 0 1950
11 3 0 1190
12 3 0 1190
13 3 0 590
14 3 0 1410
15 3 0 1320
16 1 0 4120
17 1 0 3530
18 1 0 1940
19 1 0 3130
20 1 0 3230
21 2 0 1480
22 2 0 2180
23 2 0 2610
24 2 0 2320
25 2 0 1740
26 3 0 1740
27 3 0 1680
28 3 0 1890
29 3 0 1970
30 3 0 2770
31 1 1 1640
32 1 1 2570
33 1 1 2760
34 1 1 3190
35 1 1 2440
36 2 1 2330
37 2 1 930
38 2 1 1810
39 2 1 1500
40 2 1 1800
41 3 1 760
42 3 1 1030
43 3 1 910
44 3 1 990
45 3 1 950
46 1 1 4810
47 1 1 3040
48 1 1 2000
49 1 1 2440
50 1 1 4040
51 2 1 1870
52 2 1 1700
53 2 1 1850
54 2 1 1420
55 2 1 1260
56 3 1 1190
57 3 1 1240
58 3 1 1380
59 3 1 1170
60 3 1 1790
61 1 2 1080
62 1 2 1100
63 1 2 1550
64 1 2 1050
65 1 2 1280
66 2 2 1700
67 2 2 850
68 2 2 1540
69 2 2 950
70 2 2 1350
71 3 2 540
72 3 2 700
73 3 2 600
74 3 2 750
75 3 2 700
76 1 2 1850
77 1 2 1380
78 1 2 1650
79 1 2 1230
80 1 2 1580
81 2 2 1500
82 2 2 1380
83 2 2 1120
84 2 2 1130
85 2 2 860
86 3 2 960
87 3 2 1080
88 3 2 1120
89 3 2 960
90 3 2 1020
91 1 3 1000
92 1 3 1520
93 1 3 980
94 1 3 1180
95 1 3 1540
96 2 3 1180
97 2 3 780
98 2 3 1210
99 2 3 500
100 2 3 1000
101 3 3 500
102 3 3 500
103 3 3 320
104 3 3 240
105 3 3 460
106 1 3 1600
107 1 3 1250
108 1 3 1420
109 1 3 1020
110 1 3 1450
111 2 3 1300
112 2 3 1100
113 2 3 750
114 2 3 900
115 2 3 640
116 3 3 600
117 3 3 980
118 3 3 940
119 3 3 750
120 3 3 570
121 1 4 950
122 1 4 1200
123 1 4 1380
124 1 4 980
125 1 4 740
126 2 4 890
127 2 4 380
128 2 4 810
129 2 4 260
130 2 4 800
131 3 4 370
132 3 4 350
133 3 4 250
134 3 4 170
135 3 4 380
136 1 4 1680
137 1 4 1200
138 1 4 960
139 1 4 1100
140 1 4 620
141 2 4 900
142 2 4 720
143 2 4 680
144 2 4 480
145 2 4 800
146 3 4 700
147 3 4 800
148 3 4 680
149 3 4 400
150 3 4 420
151 1 5 1000
152 1 5 1300
153 1 5 1000
154 1 5 850
155 1 5 800
156 2 5 850
157 2 5 300
158 2 5 600
159 2 5 300
160 2 5 650
161 3 5 250
162 3 5 250
163 3 5 200
164 3 5 100
165 3 5 270
166 1 5 1380
167 1 5 920
168 1 5 1280
169 1 5 1120
170 1 5 800
171 2 5 640
172 2 5 800
173 2 5 420
174 2 5 380
175 2 5 900
176 3 5 660
177 3 5 760
178 3 5 640
179 3 5 480
180 3 5 460
181 1 6 900
182 1 6 1350
183 1 6 1300
184 1 6 1100
185 1 6 600
186 2 6 750
187 2 6 560
188 2 6 750
189 2 6 250
190 2 6 600
191 3 6 360
192 3 6 300
193 3 6 150
194 3 6 200
195 3 6 200
196 1 6 1100
197 1 6 850
198 1 6 1100
199 1 6 1200
200 1 6 750
201 2 6 400
202 2 6 520
203 2 6 500
204 2 6 400
205 2 6 950
206 3 6 650
207 3 6 900
208 3 6 850
209 3 6 500
210 3 6 400
211 1 7 800
212 1 7 1250
213 1 7 1050
214 1 7 950
215 1 7 500
216 2 7 600
217 2 7 350
218 2 7 500
219 2 7 200
220 2 7 500
221 3 7 300
222 3 7 100
223 3 7 100
224 3 7 200
225 3 7 100
226 1 7 1000
227 1 7 1150
228 1 7 1120
229 1 7 1450
230 1 7 660
231 2 7 780
232 2 7 620
233 2 7 550
234 2 7 450
235 2 7 1000
236 3 7 550
237 3 7 820
238 3 7 520
239 3 7 630
240 3 7 500
%>% rename (., GeneticLine = EweType)
GeneticLine Diet Week MilkProd
1 2 1 0 1260
2 2 1 0 1900
3 2 1 0 1380
4 2 1 0 3910
5 2 1 0 2900
6 2 2 0 2210
7 2 2 0 1850
8 2 2 0 1750
9 2 2 0 1900
10 2 2 0 1950
11 2 3 0 1190
12 2 3 0 1190
13 2 3 0 590
14 2 3 0 1410
15 2 3 0 1320
16 1 1 0 4120
17 1 1 0 3530
18 1 1 0 1940
19 1 1 0 3130
20 1 1 0 3230
21 1 2 0 1480
22 1 2 0 2180
23 1 2 0 2610
24 1 2 0 2320
25 1 2 0 1740
26 1 3 0 1740
27 1 3 0 1680
28 1 3 0 1890
29 1 3 0 1970
30 1 3 0 2770
31 2 1 1 1640
32 2 1 1 2570
33 2 1 1 2760
34 2 1 1 3190
35 2 1 1 2440
36 2 2 1 2330
37 2 2 1 930
38 2 2 1 1810
39 2 2 1 1500
40 2 2 1 1800
41 2 3 1 760
42 2 3 1 1030
43 2 3 1 910
44 2 3 1 990
45 2 3 1 950
46 1 1 1 4810
47 1 1 1 3040
48 1 1 1 2000
49 1 1 1 2440
50 1 1 1 4040
51 1 2 1 1870
52 1 2 1 1700
53 1 2 1 1850
54 1 2 1 1420
55 1 2 1 1260
56 1 3 1 1190
57 1 3 1 1240
58 1 3 1 1380
59 1 3 1 1170
60 1 3 1 1790
61 2 1 2 1080
62 2 1 2 1100
63 2 1 2 1550
64 2 1 2 1050
65 2 1 2 1280
66 2 2 2 1700
67 2 2 2 850
68 2 2 2 1540
69 2 2 2 950
70 2 2 2 1350
71 2 3 2 540
72 2 3 2 700
73 2 3 2 600
74 2 3 2 750
75 2 3 2 700
76 1 1 2 1850
77 1 1 2 1380
78 1 1 2 1650
79 1 1 2 1230
80 1 1 2 1580
81 1 2 2 1500
82 1 2 2 1380
83 1 2 2 1120
84 1 2 2 1130
85 1 2 2 860
86 1 3 2 960
87 1 3 2 1080
88 1 3 2 1120
89 1 3 2 960
90 1 3 2 1020
91 2 1 3 1000
92 2 1 3 1520
93 2 1 3 980
94 2 1 3 1180
95 2 1 3 1540
96 2 2 3 1180
97 2 2 3 780
98 2 2 3 1210
99 2 2 3 500
100 2 2 3 1000
101 2 3 3 500
102 2 3 3 500
103 2 3 3 320
104 2 3 3 240
105 2 3 3 460
106 1 1 3 1600
107 1 1 3 1250
108 1 1 3 1420
109 1 1 3 1020
110 1 1 3 1450
111 1 2 3 1300
112 1 2 3 1100
113 1 2 3 750
114 1 2 3 900
115 1 2 3 640
116 1 3 3 600
117 1 3 3 980
118 1 3 3 940
119 1 3 3 750
120 1 3 3 570
121 2 1 4 950
122 2 1 4 1200
123 2 1 4 1380
124 2 1 4 980
125 2 1 4 740
126 2 2 4 890
127 2 2 4 380
128 2 2 4 810
129 2 2 4 260
130 2 2 4 800
131 2 3 4 370
132 2 3 4 350
133 2 3 4 250
134 2 3 4 170
135 2 3 4 380
136 1 1 4 1680
137 1 1 4 1200
138 1 1 4 960
139 1 1 4 1100
140 1 1 4 620
141 1 2 4 900
142 1 2 4 720
143 1 2 4 680
144 1 2 4 480
145 1 2 4 800
146 1 3 4 700
147 1 3 4 800
148 1 3 4 680
149 1 3 4 400
150 1 3 4 420
151 2 1 5 1000
152 2 1 5 1300
153 2 1 5 1000
154 2 1 5 850
155 2 1 5 800
156 2 2 5 850
157 2 2 5 300
158 2 2 5 600
159 2 2 5 300
160 2 2 5 650
161 2 3 5 250
162 2 3 5 250
163 2 3 5 200
164 2 3 5 100
165 2 3 5 270
166 1 1 5 1380
167 1 1 5 920
168 1 1 5 1280
169 1 1 5 1120
170 1 1 5 800
171 1 2 5 640
172 1 2 5 800
173 1 2 5 420
174 1 2 5 380
175 1 2 5 900
176 1 3 5 660
177 1 3 5 760
178 1 3 5 640
179 1 3 5 480
180 1 3 5 460
181 2 1 6 900
182 2 1 6 1350
183 2 1 6 1300
184 2 1 6 1100
185 2 1 6 600
186 2 2 6 750
187 2 2 6 560
188 2 2 6 750
189 2 2 6 250
190 2 2 6 600
191 2 3 6 360
192 2 3 6 300
193 2 3 6 150
194 2 3 6 200
195 2 3 6 200
196 1 1 6 1100
197 1 1 6 850
198 1 1 6 1100
199 1 1 6 1200
200 1 1 6 750
201 1 2 6 400
202 1 2 6 520
203 1 2 6 500
204 1 2 6 400
205 1 2 6 950
206 1 3 6 650
207 1 3 6 900
208 1 3 6 850
209 1 3 6 500
210 1 3 6 400
211 2 1 7 800
212 2 1 7 1250
213 2 1 7 1050
214 2 1 7 950
215 2 1 7 500
216 2 2 7 600
217 2 2 7 350
218 2 2 7 500
219 2 2 7 200
220 2 2 7 500
221 2 3 7 300
222 2 3 7 100
223 2 3 7 100
224 2 3 7 200
225 2 3 7 100
226 1 1 7 1000
227 1 1 7 1150
228 1 1 7 1120
229 1 1 7 1450
230 1 1 7 660
231 1 2 7 780
232 1 2 7 620
233 1 2 7 550
234 1 2 7 450
235 1 2 7 1000
236 1 3 7 550
237 1 3 7 820
238 1 3 7 520
239 1 3 7 630
240 1 3 7 500
You can add options to executable code like this unexpected ‘,’ in: “data2 %>% Early = Week %in% c(”0-2”),”
library (tidyverse)library (car)<- read.csv ("Liveweight.csv" , colClasses = c (NA , "numeric" ))head (data2)
Ewetype Diet Week LiveWeigth
1 1 1 0 67.5
2 1 1 0 86.0
3 1 1 0 85.5
4 1 1 0 74.5
5 1 1 0 84.0
6 1 2 0 80.0
'data.frame': 240 obs. of 4 variables:
$ Ewetype : int 1 1 1 1 1 1 1 1 1 1 ...
$ Diet : num 1 1 1 1 1 2 2 2 2 2 ...
$ Week : int 0 0 0 0 0 0 0 0 0 0 ...
$ LiveWeigth: num 67.5 86 85.5 74.5 84 80 76.5 71.5 75 78.5 ...
Rows: 240
Columns: 4
$ Ewetype <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2,~
$ Diet <dbl> 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1,~
$ Week <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,~
$ LiveWeigth <dbl> 67.5, 86.0, 85.5, 74.5, 84.0, 80.0, 76.5, 71.5, 75.0, 78.5,~
$ Ewetype<- as.factor (data2$ Ewetype)$ Diet<- as.factor (data2$ Diet)$ Week <- as.character (data2$ Week)$ LiveWeigth<- as.numeric (data2$ LiveWeigth)tail (data2)
Ewetype Diet Week LiveWeigth
235 2 2 7 63.0
236 2 3 7 57.5
237 2 3 7 62.5
238 2 3 7 62.5
239 2 3 7 83.5
240 2 3 7 80.0
Ewetype Diet Week LiveWeigth
1 1 1 0 67.5
2 1 1 0 86.0
3 1 1 0 85.5
4 1 1 0 74.5
5 1 1 0 84.0
6 1 2 0 80.0
7 1 2 0 76.5
8 1 2 0 71.5
9 1 2 0 75.0
10 1 2 0 78.5
11 1 3 0 70.0
12 1 3 0 93.5
13 1 3 0 77.5
14 1 3 0 91.5
15 1 3 0 83.5
16 2 1 0 79.5
17 2 1 0 88.5
18 2 1 0 76.5
19 2 1 0 59.5
20 2 1 0 90.5
21 2 2 0 87.5
22 2 2 0 70.0
23 2 2 0 72.0
24 2 2 0 64.0
25 2 2 0 62.5
26 2 3 0 55.5
27 2 3 0 65.0
28 2 3 0 64.0
29 2 3 0 81.0
30 2 3 0 81.5
31 1 1 1 68.0
32 1 1 1 88.0
33 1 1 1 87.0
34 1 1 1 77.5
35 1 1 1 85.5
36 1 2 1 81.0
37 1 2 1 71.0
38 1 2 1 72.0
39 1 2 1 75.5
40 1 2 1 81.0
41 1 3 1 66.5
42 1 3 1 89.0
43 1 3 1 74.0
44 1 3 1 86.5
45 1 3 1 75.5
46 2 1 1 82.5
47 2 1 1 89.5
48 2 1 1 77.0
49 2 1 1 62.5
50 2 1 1 91.0
51 2 2 1 85.5
52 2 2 1 69.5
53 2 2 1 70.5
54 2 2 1 63.0
55 2 2 1 62.0
56 2 3 1 54.5
57 2 3 1 64.0
58 2 3 1 63.5
59 2 3 1 78.5
60 2 3 1 81.0
61 1 1 2 68.0
62 1 1 2 90.0
63 1 1 2 88.0
64 1 1 2 80.5
65 1 1 2 87.5
66 1 2 2 81.0
67 1 2 2 67.5
68 1 2 2 72.0
69 1 2 2 75.5
70 1 2 2 82.5
71 1 3 2 62.0
72 1 3 2 85.5
73 1 3 2 70.0
74 1 3 2 78.5
75 1 3 2 69.5
76 2 1 2 86.0
77 2 1 2 88.0
78 2 1 2 77.0
79 2 1 2 64.0
80 2 1 2 91.0
81 2 2 2 84.5
82 2 2 2 68.0
83 2 2 2 67.0
84 2 2 2 62.0
85 2 2 2 60.5
86 2 3 2 55.0
87 2 3 2 62.5
88 2 3 2 64.0
89 2 3 2 77.0
90 2 3 2 80.0
91 1 1 3 66.5
92 1 1 3 89.5
93 1 1 3 87.0
94 1 1 3 84.0
95 1 1 3 89.5
96 1 2 3 80.0
97 1 2 3 67.5
98 1 2 3 69.0
99 1 2 3 77.0
100 1 2 3 82.0
101 1 3 3 63.0
102 1 3 3 83.5
103 1 3 3 73.5
104 1 3 3 76.5
105 1 3 3 71.0
106 2 1 3 94.5
107 2 1 3 88.0
108 2 1 3 77.5
109 2 1 3 66.0
110 2 1 3 92.0
111 2 2 3 83.0
112 2 2 3 67.0
113 2 2 3 65.5
114 2 2 3 61.5
115 2 2 3 61.0
116 2 3 3 54.5
117 2 3 3 61.0
118 2 3 3 62.5
119 2 3 3 75.5
120 2 3 3 80.5
121 1 1 4 69.5
122 1 1 4 90.0
123 1 1 4 82.0
124 1 1 4 86.0
125 1 1 4 89.0
126 1 2 4 82.5
127 1 2 4 71.0
128 1 2 4 70.5
129 1 2 4 79.5
130 1 2 4 80.5
131 1 3 4 63.5
132 1 3 4 84.0
133 1 3 4 75.5
134 1 3 4 75.0
135 1 3 4 76.0
136 2 1 4 83.5
137 2 1 4 86.0
138 2 1 4 78.0
139 2 1 4 64.5
140 2 1 4 90.5
141 2 2 4 82.5
142 2 2 4 68.0
143 2 2 4 64.5
144 2 2 4 62.5
145 2 2 4 61.5
146 2 3 4 53.5
147 2 3 4 61.0
148 2 3 4 62.5
149 2 3 4 75.5
150 2 3 4 80.5
151 1 1 5 69.5
152 1 1 5 87.5
153 1 1 5 80.5
154 1 1 5 83.0
155 1 1 5 83.0
156 1 2 5 80.0
157 1 2 5 71.5
158 1 2 5 71.5
159 1 2 5 80.0
160 1 2 5 79.5
161 1 3 5 61.0
162 1 3 5 81.5
163 1 3 5 71.0
164 1 3 5 71.0
165 1 3 5 70.0
166 2 1 5 81.5
167 2 1 5 83.5
168 2 1 5 73.5
169 2 1 5 61.5
170 2 1 5 87.5
171 2 2 5 80.5
172 2 2 5 65.0
173 2 2 5 59.5
174 2 2 5 60.0
175 2 2 5 60.0
176 2 3 5 52.0
177 2 3 5 59.0
178 2 3 5 61.5
179 2 3 5 75.0
180 2 3 5 79.0
181 1 1 6 72.0
182 1 1 6 92.5
183 1 1 6 84.0
184 1 1 6 88.0
185 1 1 6 87.5
186 1 2 6 82.0
187 1 2 6 74.0
188 1 2 6 74.0
189 1 2 6 83.0
190 1 2 6 81.0
191 1 3 6 63.0
192 1 3 6 82.5
193 1 3 6 75.0
194 1 3 6 72.0
195 1 3 6 75.0
196 2 1 6 85.5
197 2 1 6 89.5
198 2 1 6 79.5
199 2 1 6 63.0
200 2 1 6 94.5
201 2 2 6 85.5
202 2 2 6 68.5
203 2 2 6 60.5
204 2 2 6 65.5
205 2 2 6 62.0
206 2 3 6 54.5
207 2 3 6 61.0
208 2 3 6 62.0
209 2 3 6 80.0
210 2 3 6 79.0
211 1 1 7 77.5
212 1 1 7 98.5
213 1 1 7 88.5
214 1 1 7 92.5
215 1 1 7 92.0
216 1 2 7 85.0
217 1 2 7 77.5
218 1 2 7 77.5
219 1 2 7 85.0
220 1 2 7 82.0
221 1 3 7 67.5
222 1 3 7 83.5
223 1 3 7 81.0
224 1 3 7 72.5
225 1 3 7 76.5
226 2 1 7 93.5
227 2 1 7 94.5
228 2 1 7 85.0
229 2 1 7 64.5
230 2 1 7 99.5
231 2 2 7 90.0
232 2 2 7 72.0
233 2 2 7 62.0
234 2 2 7 70.0
235 2 2 7 63.0
236 2 3 7 57.5
237 2 3 7 62.5
238 2 3 7 62.5
239 2 3 7 83.5
240 2 3 7 80.0
###Question 2#### library (dplyr)%>% group_by (Week)
# A tibble: 240 x 4
# Groups: Week [8]
Ewetype Diet Week LiveWeigth
<fct> <fct> <chr> <dbl>
1 1 1 0 67.5
2 1 1 0 86
3 1 1 0 85.5
4 1 1 0 74.5
5 1 1 0 84
6 1 2 0 80
7 1 2 0 76.5
8 1 2 0 71.5
9 1 2 0 75
10 1 2 0 78.5
# i 230 more rows
%>% select (Week)%>% mutate (Early = Week %in% c (0 ,1 ,2 ),Late = if_else (Week %in% c (0 , 1 , 2 ), "Early" , "Late" )
Week Early Late
1 0 TRUE Early
2 0 TRUE Early
3 0 TRUE Early
4 0 TRUE Early
5 0 TRUE Early
6 0 TRUE Early
7 0 TRUE Early
8 0 TRUE Early
9 0 TRUE Early
10 0 TRUE Early
11 0 TRUE Early
12 0 TRUE Early
13 0 TRUE Early
14 0 TRUE Early
15 0 TRUE Early
16 0 TRUE Early
17 0 TRUE Early
18 0 TRUE Early
19 0 TRUE Early
20 0 TRUE Early
21 0 TRUE Early
22 0 TRUE Early
23 0 TRUE Early
24 0 TRUE Early
25 0 TRUE Early
26 0 TRUE Early
27 0 TRUE Early
28 0 TRUE Early
29 0 TRUE Early
30 0 TRUE Early
31 1 TRUE Early
32 1 TRUE Early
33 1 TRUE Early
34 1 TRUE Early
35 1 TRUE Early
36 1 TRUE Early
37 1 TRUE Early
38 1 TRUE Early
39 1 TRUE Early
40 1 TRUE Early
41 1 TRUE Early
42 1 TRUE Early
43 1 TRUE Early
44 1 TRUE Early
45 1 TRUE Early
46 1 TRUE Early
47 1 TRUE Early
48 1 TRUE Early
49 1 TRUE Early
50 1 TRUE Early
51 1 TRUE Early
52 1 TRUE Early
53 1 TRUE Early
54 1 TRUE Early
55 1 TRUE Early
56 1 TRUE Early
57 1 TRUE Early
58 1 TRUE Early
59 1 TRUE Early
60 1 TRUE Early
61 2 TRUE Early
62 2 TRUE Early
63 2 TRUE Early
64 2 TRUE Early
65 2 TRUE Early
66 2 TRUE Early
67 2 TRUE Early
68 2 TRUE Early
69 2 TRUE Early
70 2 TRUE Early
71 2 TRUE Early
72 2 TRUE Early
73 2 TRUE Early
74 2 TRUE Early
75 2 TRUE Early
76 2 TRUE Early
77 2 TRUE Early
78 2 TRUE Early
79 2 TRUE Early
80 2 TRUE Early
81 2 TRUE Early
82 2 TRUE Early
83 2 TRUE Early
84 2 TRUE Early
85 2 TRUE Early
86 2 TRUE Early
87 2 TRUE Early
88 2 TRUE Early
89 2 TRUE Early
90 2 TRUE Early
91 3 FALSE Late
92 3 FALSE Late
93 3 FALSE Late
94 3 FALSE Late
95 3 FALSE Late
96 3 FALSE Late
97 3 FALSE Late
98 3 FALSE Late
99 3 FALSE Late
100 3 FALSE Late
101 3 FALSE Late
102 3 FALSE Late
103 3 FALSE Late
104 3 FALSE Late
105 3 FALSE Late
106 3 FALSE Late
107 3 FALSE Late
108 3 FALSE Late
109 3 FALSE Late
110 3 FALSE Late
111 3 FALSE Late
112 3 FALSE Late
113 3 FALSE Late
114 3 FALSE Late
115 3 FALSE Late
116 3 FALSE Late
117 3 FALSE Late
118 3 FALSE Late
119 3 FALSE Late
120 3 FALSE Late
121 4 FALSE Late
122 4 FALSE Late
123 4 FALSE Late
124 4 FALSE Late
125 4 FALSE Late
126 4 FALSE Late
127 4 FALSE Late
128 4 FALSE Late
129 4 FALSE Late
130 4 FALSE Late
131 4 FALSE Late
132 4 FALSE Late
133 4 FALSE Late
134 4 FALSE Late
135 4 FALSE Late
136 4 FALSE Late
137 4 FALSE Late
138 4 FALSE Late
139 4 FALSE Late
140 4 FALSE Late
141 4 FALSE Late
142 4 FALSE Late
143 4 FALSE Late
144 4 FALSE Late
145 4 FALSE Late
146 4 FALSE Late
147 4 FALSE Late
148 4 FALSE Late
149 4 FALSE Late
150 4 FALSE Late
151 5 FALSE Late
152 5 FALSE Late
153 5 FALSE Late
154 5 FALSE Late
155 5 FALSE Late
156 5 FALSE Late
157 5 FALSE Late
158 5 FALSE Late
159 5 FALSE Late
160 5 FALSE Late
161 5 FALSE Late
162 5 FALSE Late
163 5 FALSE Late
164 5 FALSE Late
165 5 FALSE Late
166 5 FALSE Late
167 5 FALSE Late
168 5 FALSE Late
169 5 FALSE Late
170 5 FALSE Late
171 5 FALSE Late
172 5 FALSE Late
173 5 FALSE Late
174 5 FALSE Late
175 5 FALSE Late
176 5 FALSE Late
177 5 FALSE Late
178 5 FALSE Late
179 5 FALSE Late
180 5 FALSE Late
181 6 FALSE Late
182 6 FALSE Late
183 6 FALSE Late
184 6 FALSE Late
185 6 FALSE Late
186 6 FALSE Late
187 6 FALSE Late
188 6 FALSE Late
189 6 FALSE Late
190 6 FALSE Late
191 6 FALSE Late
192 6 FALSE Late
193 6 FALSE Late
194 6 FALSE Late
195 6 FALSE Late
196 6 FALSE Late
197 6 FALSE Late
198 6 FALSE Late
199 6 FALSE Late
200 6 FALSE Late
201 6 FALSE Late
202 6 FALSE Late
203 6 FALSE Late
204 6 FALSE Late
205 6 FALSE Late
206 6 FALSE Late
207 6 FALSE Late
208 6 FALSE Late
209 6 FALSE Late
210 6 FALSE Late
211 7 FALSE Late
212 7 FALSE Late
213 7 FALSE Late
214 7 FALSE Late
215 7 FALSE Late
216 7 FALSE Late
217 7 FALSE Late
218 7 FALSE Late
219 7 FALSE Late
220 7 FALSE Late
221 7 FALSE Late
222 7 FALSE Late
223 7 FALSE Late
224 7 FALSE Late
225 7 FALSE Late
226 7 FALSE Late
227 7 FALSE Late
228 7 FALSE Late
229 7 FALSE Late
230 7 FALSE Late
231 7 FALSE Late
232 7 FALSE Late
233 7 FALSE Late
234 7 FALSE Late
235 7 FALSE Late
236 7 FALSE Late
237 7 FALSE Late
238 7 FALSE Late
239 7 FALSE Late
240 7 FALSE Late
%>% mutate (LiveWeigth75kg = ifelse (LiveWeigth > 75 , "Above" , "Below" ))
Ewetype Diet Week LiveWeigth LiveWeigth75kg
1 1 1 0 67.5 Below
2 1 1 0 86.0 Above
3 1 1 0 85.5 Above
4 1 1 0 74.5 Below
5 1 1 0 84.0 Above
6 1 2 0 80.0 Above
7 1 2 0 76.5 Above
8 1 2 0 71.5 Below
9 1 2 0 75.0 Below
10 1 2 0 78.5 Above
11 1 3 0 70.0 Below
12 1 3 0 93.5 Above
13 1 3 0 77.5 Above
14 1 3 0 91.5 Above
15 1 3 0 83.5 Above
16 2 1 0 79.5 Above
17 2 1 0 88.5 Above
18 2 1 0 76.5 Above
19 2 1 0 59.5 Below
20 2 1 0 90.5 Above
21 2 2 0 87.5 Above
22 2 2 0 70.0 Below
23 2 2 0 72.0 Below
24 2 2 0 64.0 Below
25 2 2 0 62.5 Below
26 2 3 0 55.5 Below
27 2 3 0 65.0 Below
28 2 3 0 64.0 Below
29 2 3 0 81.0 Above
30 2 3 0 81.5 Above
31 1 1 1 68.0 Below
32 1 1 1 88.0 Above
33 1 1 1 87.0 Above
34 1 1 1 77.5 Above
35 1 1 1 85.5 Above
36 1 2 1 81.0 Above
37 1 2 1 71.0 Below
38 1 2 1 72.0 Below
39 1 2 1 75.5 Above
40 1 2 1 81.0 Above
41 1 3 1 66.5 Below
42 1 3 1 89.0 Above
43 1 3 1 74.0 Below
44 1 3 1 86.5 Above
45 1 3 1 75.5 Above
46 2 1 1 82.5 Above
47 2 1 1 89.5 Above
48 2 1 1 77.0 Above
49 2 1 1 62.5 Below
50 2 1 1 91.0 Above
51 2 2 1 85.5 Above
52 2 2 1 69.5 Below
53 2 2 1 70.5 Below
54 2 2 1 63.0 Below
55 2 2 1 62.0 Below
56 2 3 1 54.5 Below
57 2 3 1 64.0 Below
58 2 3 1 63.5 Below
59 2 3 1 78.5 Above
60 2 3 1 81.0 Above
61 1 1 2 68.0 Below
62 1 1 2 90.0 Above
63 1 1 2 88.0 Above
64 1 1 2 80.5 Above
65 1 1 2 87.5 Above
66 1 2 2 81.0 Above
67 1 2 2 67.5 Below
68 1 2 2 72.0 Below
69 1 2 2 75.5 Above
70 1 2 2 82.5 Above
71 1 3 2 62.0 Below
72 1 3 2 85.5 Above
73 1 3 2 70.0 Below
74 1 3 2 78.5 Above
75 1 3 2 69.5 Below
76 2 1 2 86.0 Above
77 2 1 2 88.0 Above
78 2 1 2 77.0 Above
79 2 1 2 64.0 Below
80 2 1 2 91.0 Above
81 2 2 2 84.5 Above
82 2 2 2 68.0 Below
83 2 2 2 67.0 Below
84 2 2 2 62.0 Below
85 2 2 2 60.5 Below
86 2 3 2 55.0 Below
87 2 3 2 62.5 Below
88 2 3 2 64.0 Below
89 2 3 2 77.0 Above
90 2 3 2 80.0 Above
91 1 1 3 66.5 Below
92 1 1 3 89.5 Above
93 1 1 3 87.0 Above
94 1 1 3 84.0 Above
95 1 1 3 89.5 Above
96 1 2 3 80.0 Above
97 1 2 3 67.5 Below
98 1 2 3 69.0 Below
99 1 2 3 77.0 Above
100 1 2 3 82.0 Above
101 1 3 3 63.0 Below
102 1 3 3 83.5 Above
103 1 3 3 73.5 Below
104 1 3 3 76.5 Above
105 1 3 3 71.0 Below
106 2 1 3 94.5 Above
107 2 1 3 88.0 Above
108 2 1 3 77.5 Above
109 2 1 3 66.0 Below
110 2 1 3 92.0 Above
111 2 2 3 83.0 Above
112 2 2 3 67.0 Below
113 2 2 3 65.5 Below
114 2 2 3 61.5 Below
115 2 2 3 61.0 Below
116 2 3 3 54.5 Below
117 2 3 3 61.0 Below
118 2 3 3 62.5 Below
119 2 3 3 75.5 Above
120 2 3 3 80.5 Above
121 1 1 4 69.5 Below
122 1 1 4 90.0 Above
123 1 1 4 82.0 Above
124 1 1 4 86.0 Above
125 1 1 4 89.0 Above
126 1 2 4 82.5 Above
127 1 2 4 71.0 Below
128 1 2 4 70.5 Below
129 1 2 4 79.5 Above
130 1 2 4 80.5 Above
131 1 3 4 63.5 Below
132 1 3 4 84.0 Above
133 1 3 4 75.5 Above
134 1 3 4 75.0 Below
135 1 3 4 76.0 Above
136 2 1 4 83.5 Above
137 2 1 4 86.0 Above
138 2 1 4 78.0 Above
139 2 1 4 64.5 Below
140 2 1 4 90.5 Above
141 2 2 4 82.5 Above
142 2 2 4 68.0 Below
143 2 2 4 64.5 Below
144 2 2 4 62.5 Below
145 2 2 4 61.5 Below
146 2 3 4 53.5 Below
147 2 3 4 61.0 Below
148 2 3 4 62.5 Below
149 2 3 4 75.5 Above
150 2 3 4 80.5 Above
151 1 1 5 69.5 Below
152 1 1 5 87.5 Above
153 1 1 5 80.5 Above
154 1 1 5 83.0 Above
155 1 1 5 83.0 Above
156 1 2 5 80.0 Above
157 1 2 5 71.5 Below
158 1 2 5 71.5 Below
159 1 2 5 80.0 Above
160 1 2 5 79.5 Above
161 1 3 5 61.0 Below
162 1 3 5 81.5 Above
163 1 3 5 71.0 Below
164 1 3 5 71.0 Below
165 1 3 5 70.0 Below
166 2 1 5 81.5 Above
167 2 1 5 83.5 Above
168 2 1 5 73.5 Below
169 2 1 5 61.5 Below
170 2 1 5 87.5 Above
171 2 2 5 80.5 Above
172 2 2 5 65.0 Below
173 2 2 5 59.5 Below
174 2 2 5 60.0 Below
175 2 2 5 60.0 Below
176 2 3 5 52.0 Below
177 2 3 5 59.0 Below
178 2 3 5 61.5 Below
179 2 3 5 75.0 Below
180 2 3 5 79.0 Above
181 1 1 6 72.0 Below
182 1 1 6 92.5 Above
183 1 1 6 84.0 Above
184 1 1 6 88.0 Above
185 1 1 6 87.5 Above
186 1 2 6 82.0 Above
187 1 2 6 74.0 Below
188 1 2 6 74.0 Below
189 1 2 6 83.0 Above
190 1 2 6 81.0 Above
191 1 3 6 63.0 Below
192 1 3 6 82.5 Above
193 1 3 6 75.0 Below
194 1 3 6 72.0 Below
195 1 3 6 75.0 Below
196 2 1 6 85.5 Above
197 2 1 6 89.5 Above
198 2 1 6 79.5 Above
199 2 1 6 63.0 Below
200 2 1 6 94.5 Above
201 2 2 6 85.5 Above
202 2 2 6 68.5 Below
203 2 2 6 60.5 Below
204 2 2 6 65.5 Below
205 2 2 6 62.0 Below
206 2 3 6 54.5 Below
207 2 3 6 61.0 Below
208 2 3 6 62.0 Below
209 2 3 6 80.0 Above
210 2 3 6 79.0 Above
211 1 1 7 77.5 Above
212 1 1 7 98.5 Above
213 1 1 7 88.5 Above
214 1 1 7 92.5 Above
215 1 1 7 92.0 Above
216 1 2 7 85.0 Above
217 1 2 7 77.5 Above
218 1 2 7 77.5 Above
219 1 2 7 85.0 Above
220 1 2 7 82.0 Above
221 1 3 7 67.5 Below
222 1 3 7 83.5 Above
223 1 3 7 81.0 Above
224 1 3 7 72.5 Below
225 1 3 7 76.5 Above
226 2 1 7 93.5 Above
227 2 1 7 94.5 Above
228 2 1 7 85.0 Above
229 2 1 7 64.5 Below
230 2 1 7 99.5 Above
231 2 2 7 90.0 Above
232 2 2 7 72.0 Below
233 2 2 7 62.0 Below
234 2 2 7 70.0 Below
235 2 2 7 63.0 Below
236 2 3 7 57.5 Below
237 2 3 7 62.5 Below
238 2 3 7 62.5 Below
239 2 3 7 83.5 Above
240 2 3 7 80.0 Above
%>% mutate (/ 1000 ) * 2.2 ,
Ewetype Diet Week LiveWeigth (LiveWeigth/1000) * 2.2
1 1 1 0 67.5 0.1485
2 1 1 0 86.0 0.1892
3 1 1 0 85.5 0.1881
4 1 1 0 74.5 0.1639
5 1 1 0 84.0 0.1848
6 1 2 0 80.0 0.1760
7 1 2 0 76.5 0.1683
8 1 2 0 71.5 0.1573
9 1 2 0 75.0 0.1650
10 1 2 0 78.5 0.1727
11 1 3 0 70.0 0.1540
12 1 3 0 93.5 0.2057
13 1 3 0 77.5 0.1705
14 1 3 0 91.5 0.2013
15 1 3 0 83.5 0.1837
16 2 1 0 79.5 0.1749
17 2 1 0 88.5 0.1947
18 2 1 0 76.5 0.1683
19 2 1 0 59.5 0.1309
20 2 1 0 90.5 0.1991
21 2 2 0 87.5 0.1925
22 2 2 0 70.0 0.1540
23 2 2 0 72.0 0.1584
24 2 2 0 64.0 0.1408
25 2 2 0 62.5 0.1375
26 2 3 0 55.5 0.1221
27 2 3 0 65.0 0.1430
28 2 3 0 64.0 0.1408
29 2 3 0 81.0 0.1782
30 2 3 0 81.5 0.1793
31 1 1 1 68.0 0.1496
32 1 1 1 88.0 0.1936
33 1 1 1 87.0 0.1914
34 1 1 1 77.5 0.1705
35 1 1 1 85.5 0.1881
36 1 2 1 81.0 0.1782
37 1 2 1 71.0 0.1562
38 1 2 1 72.0 0.1584
39 1 2 1 75.5 0.1661
40 1 2 1 81.0 0.1782
41 1 3 1 66.5 0.1463
42 1 3 1 89.0 0.1958
43 1 3 1 74.0 0.1628
44 1 3 1 86.5 0.1903
45 1 3 1 75.5 0.1661
46 2 1 1 82.5 0.1815
47 2 1 1 89.5 0.1969
48 2 1 1 77.0 0.1694
49 2 1 1 62.5 0.1375
50 2 1 1 91.0 0.2002
51 2 2 1 85.5 0.1881
52 2 2 1 69.5 0.1529
53 2 2 1 70.5 0.1551
54 2 2 1 63.0 0.1386
55 2 2 1 62.0 0.1364
56 2 3 1 54.5 0.1199
57 2 3 1 64.0 0.1408
58 2 3 1 63.5 0.1397
59 2 3 1 78.5 0.1727
60 2 3 1 81.0 0.1782
61 1 1 2 68.0 0.1496
62 1 1 2 90.0 0.1980
63 1 1 2 88.0 0.1936
64 1 1 2 80.5 0.1771
65 1 1 2 87.5 0.1925
66 1 2 2 81.0 0.1782
67 1 2 2 67.5 0.1485
68 1 2 2 72.0 0.1584
69 1 2 2 75.5 0.1661
70 1 2 2 82.5 0.1815
71 1 3 2 62.0 0.1364
72 1 3 2 85.5 0.1881
73 1 3 2 70.0 0.1540
74 1 3 2 78.5 0.1727
75 1 3 2 69.5 0.1529
76 2 1 2 86.0 0.1892
77 2 1 2 88.0 0.1936
78 2 1 2 77.0 0.1694
79 2 1 2 64.0 0.1408
80 2 1 2 91.0 0.2002
81 2 2 2 84.5 0.1859
82 2 2 2 68.0 0.1496
83 2 2 2 67.0 0.1474
84 2 2 2 62.0 0.1364
85 2 2 2 60.5 0.1331
86 2 3 2 55.0 0.1210
87 2 3 2 62.5 0.1375
88 2 3 2 64.0 0.1408
89 2 3 2 77.0 0.1694
90 2 3 2 80.0 0.1760
91 1 1 3 66.5 0.1463
92 1 1 3 89.5 0.1969
93 1 1 3 87.0 0.1914
94 1 1 3 84.0 0.1848
95 1 1 3 89.5 0.1969
96 1 2 3 80.0 0.1760
97 1 2 3 67.5 0.1485
98 1 2 3 69.0 0.1518
99 1 2 3 77.0 0.1694
100 1 2 3 82.0 0.1804
101 1 3 3 63.0 0.1386
102 1 3 3 83.5 0.1837
103 1 3 3 73.5 0.1617
104 1 3 3 76.5 0.1683
105 1 3 3 71.0 0.1562
106 2 1 3 94.5 0.2079
107 2 1 3 88.0 0.1936
108 2 1 3 77.5 0.1705
109 2 1 3 66.0 0.1452
110 2 1 3 92.0 0.2024
111 2 2 3 83.0 0.1826
112 2 2 3 67.0 0.1474
113 2 2 3 65.5 0.1441
114 2 2 3 61.5 0.1353
115 2 2 3 61.0 0.1342
116 2 3 3 54.5 0.1199
117 2 3 3 61.0 0.1342
118 2 3 3 62.5 0.1375
119 2 3 3 75.5 0.1661
120 2 3 3 80.5 0.1771
121 1 1 4 69.5 0.1529
122 1 1 4 90.0 0.1980
123 1 1 4 82.0 0.1804
124 1 1 4 86.0 0.1892
125 1 1 4 89.0 0.1958
126 1 2 4 82.5 0.1815
127 1 2 4 71.0 0.1562
128 1 2 4 70.5 0.1551
129 1 2 4 79.5 0.1749
130 1 2 4 80.5 0.1771
131 1 3 4 63.5 0.1397
132 1 3 4 84.0 0.1848
133 1 3 4 75.5 0.1661
134 1 3 4 75.0 0.1650
135 1 3 4 76.0 0.1672
136 2 1 4 83.5 0.1837
137 2 1 4 86.0 0.1892
138 2 1 4 78.0 0.1716
139 2 1 4 64.5 0.1419
140 2 1 4 90.5 0.1991
141 2 2 4 82.5 0.1815
142 2 2 4 68.0 0.1496
143 2 2 4 64.5 0.1419
144 2 2 4 62.5 0.1375
145 2 2 4 61.5 0.1353
146 2 3 4 53.5 0.1177
147 2 3 4 61.0 0.1342
148 2 3 4 62.5 0.1375
149 2 3 4 75.5 0.1661
150 2 3 4 80.5 0.1771
151 1 1 5 69.5 0.1529
152 1 1 5 87.5 0.1925
153 1 1 5 80.5 0.1771
154 1 1 5 83.0 0.1826
155 1 1 5 83.0 0.1826
156 1 2 5 80.0 0.1760
157 1 2 5 71.5 0.1573
158 1 2 5 71.5 0.1573
159 1 2 5 80.0 0.1760
160 1 2 5 79.5 0.1749
161 1 3 5 61.0 0.1342
162 1 3 5 81.5 0.1793
163 1 3 5 71.0 0.1562
164 1 3 5 71.0 0.1562
165 1 3 5 70.0 0.1540
166 2 1 5 81.5 0.1793
167 2 1 5 83.5 0.1837
168 2 1 5 73.5 0.1617
169 2 1 5 61.5 0.1353
170 2 1 5 87.5 0.1925
171 2 2 5 80.5 0.1771
172 2 2 5 65.0 0.1430
173 2 2 5 59.5 0.1309
174 2 2 5 60.0 0.1320
175 2 2 5 60.0 0.1320
176 2 3 5 52.0 0.1144
177 2 3 5 59.0 0.1298
178 2 3 5 61.5 0.1353
179 2 3 5 75.0 0.1650
180 2 3 5 79.0 0.1738
181 1 1 6 72.0 0.1584
182 1 1 6 92.5 0.2035
183 1 1 6 84.0 0.1848
184 1 1 6 88.0 0.1936
185 1 1 6 87.5 0.1925
186 1 2 6 82.0 0.1804
187 1 2 6 74.0 0.1628
188 1 2 6 74.0 0.1628
189 1 2 6 83.0 0.1826
190 1 2 6 81.0 0.1782
191 1 3 6 63.0 0.1386
192 1 3 6 82.5 0.1815
193 1 3 6 75.0 0.1650
194 1 3 6 72.0 0.1584
195 1 3 6 75.0 0.1650
196 2 1 6 85.5 0.1881
197 2 1 6 89.5 0.1969
198 2 1 6 79.5 0.1749
199 2 1 6 63.0 0.1386
200 2 1 6 94.5 0.2079
201 2 2 6 85.5 0.1881
202 2 2 6 68.5 0.1507
203 2 2 6 60.5 0.1331
204 2 2 6 65.5 0.1441
205 2 2 6 62.0 0.1364
206 2 3 6 54.5 0.1199
207 2 3 6 61.0 0.1342
208 2 3 6 62.0 0.1364
209 2 3 6 80.0 0.1760
210 2 3 6 79.0 0.1738
211 1 1 7 77.5 0.1705
212 1 1 7 98.5 0.2167
213 1 1 7 88.5 0.1947
214 1 1 7 92.5 0.2035
215 1 1 7 92.0 0.2024
216 1 2 7 85.0 0.1870
217 1 2 7 77.5 0.1705
218 1 2 7 77.5 0.1705
219 1 2 7 85.0 0.1870
220 1 2 7 82.0 0.1804
221 1 3 7 67.5 0.1485
222 1 3 7 83.5 0.1837
223 1 3 7 81.0 0.1782
224 1 3 7 72.5 0.1595
225 1 3 7 76.5 0.1683
226 2 1 7 93.5 0.2057
227 2 1 7 94.5 0.2079
228 2 1 7 85.0 0.1870
229 2 1 7 64.5 0.1419
230 2 1 7 99.5 0.2189
231 2 2 7 90.0 0.1980
232 2 2 7 72.0 0.1584
233 2 2 7 62.0 0.1364
234 2 2 7 70.0 0.1540
235 2 2 7 63.0 0.1386
236 2 3 7 57.5 0.1265
237 2 3 7 62.5 0.1375
238 2 3 7 62.5 0.1375
239 2 3 7 83.5 0.1837
240 2 3 7 80.0 0.1760
%>% group_by (LiveWeigth, Ewetype, Diet)%>% summarise (MeanWeekly = mean (LiveWeigth, na.rm = TRUE )
`summarise()` has grouped output by 'LiveWeigth', 'Ewetype'. You can override
using the `.groups` argument.
# A tibble: 152 x 4
# Groups: LiveWeigth, Ewetype [111]
LiveWeigth Ewetype Diet MeanWeekly
<dbl> <fct> <fct> <dbl>
1 52 2 3 52
2 53.5 2 3 53.5
3 54.5 2 3 54.5
4 55 2 3 55
5 55.5 2 3 55.5
6 57.5 2 3 57.5
7 59 2 3 59
8 59.5 2 1 59.5
9 59.5 2 2 59.5
10 60 2 2 60
# i 142 more rows
%>% group_by (LiveWeigth, Week, Diet) %>% summarise (MeanWeigth = mean (LiveWeigth, na.rm = TRUE ),SDWeight = ifelse (n () >= 2 & sd (LiveWeigth, na.rm = TRUE )> 0 , sd (LiveWeigth, na.rm = TRUE ), NA ),Count = n ()
`summarise()` has grouped output by 'LiveWeigth', 'Week'. You can override
using the `.groups` argument.
# A tibble: 222 x 6
# Groups: LiveWeigth, Week [199]
LiveWeigth Week Diet MeanWeigth SDWeight Count
<dbl> <chr> <fct> <dbl> <lgl> <int>
1 52 5 3 52 NA 1
2 53.5 4 3 53.5 NA 1
3 54.5 1 3 54.5 NA 1
4 54.5 3 3 54.5 NA 1
5 54.5 6 3 54.5 NA 1
6 55 2 3 55 NA 1
7 55.5 0 3 55.5 NA 1
8 57.5 7 3 57.5 NA 1
9 59 5 3 59 NA 1
10 59.5 0 1 59.5 NA 1
# i 212 more rows
Ewetype Diet Week LiveWeigth
1 1 1 0 67.5
2 1 1 0 86.0
3 1 1 0 85.5
4 1 1 0 74.5
5 1 1 0 84.0
6 1 2 0 80.0
7 1 2 0 76.5
8 1 2 0 71.5
9 1 2 0 75.0
10 1 2 0 78.5
11 1 3 0 70.0
12 1 3 0 93.5
13 1 3 0 77.5
14 1 3 0 91.5
15 1 3 0 83.5
16 2 1 0 79.5
17 2 1 0 88.5
18 2 1 0 76.5
19 2 1 0 59.5
20 2 1 0 90.5
21 2 2 0 87.5
22 2 2 0 70.0
23 2 2 0 72.0
24 2 2 0 64.0
25 2 2 0 62.5
26 2 3 0 55.5
27 2 3 0 65.0
28 2 3 0 64.0
29 2 3 0 81.0
30 2 3 0 81.5
31 1 1 1 68.0
32 1 1 1 88.0
33 1 1 1 87.0
34 1 1 1 77.5
35 1 1 1 85.5
36 1 2 1 81.0
37 1 2 1 71.0
38 1 2 1 72.0
39 1 2 1 75.5
40 1 2 1 81.0
41 1 3 1 66.5
42 1 3 1 89.0
43 1 3 1 74.0
44 1 3 1 86.5
45 1 3 1 75.5
46 2 1 1 82.5
47 2 1 1 89.5
48 2 1 1 77.0
49 2 1 1 62.5
50 2 1 1 91.0
51 2 2 1 85.5
52 2 2 1 69.5
53 2 2 1 70.5
54 2 2 1 63.0
55 2 2 1 62.0
56 2 3 1 54.5
57 2 3 1 64.0
58 2 3 1 63.5
59 2 3 1 78.5
60 2 3 1 81.0
61 1 1 2 68.0
62 1 1 2 90.0
63 1 1 2 88.0
64 1 1 2 80.5
65 1 1 2 87.5
66 1 2 2 81.0
67 1 2 2 67.5
68 1 2 2 72.0
69 1 2 2 75.5
70 1 2 2 82.5
71 1 3 2 62.0
72 1 3 2 85.5
73 1 3 2 70.0
74 1 3 2 78.5
75 1 3 2 69.5
76 2 1 2 86.0
77 2 1 2 88.0
78 2 1 2 77.0
79 2 1 2 64.0
80 2 1 2 91.0
81 2 2 2 84.5
82 2 2 2 68.0
83 2 2 2 67.0
84 2 2 2 62.0
85 2 2 2 60.5
86 2 3 2 55.0
87 2 3 2 62.5
88 2 3 2 64.0
89 2 3 2 77.0
90 2 3 2 80.0
91 1 1 3 66.5
92 1 1 3 89.5
93 1 1 3 87.0
94 1 1 3 84.0
95 1 1 3 89.5
96 1 2 3 80.0
97 1 2 3 67.5
98 1 2 3 69.0
99 1 2 3 77.0
100 1 2 3 82.0
101 1 3 3 63.0
102 1 3 3 83.5
103 1 3 3 73.5
104 1 3 3 76.5
105 1 3 3 71.0
106 2 1 3 94.5
107 2 1 3 88.0
108 2 1 3 77.5
109 2 1 3 66.0
110 2 1 3 92.0
111 2 2 3 83.0
112 2 2 3 67.0
113 2 2 3 65.5
114 2 2 3 61.5
115 2 2 3 61.0
116 2 3 3 54.5
117 2 3 3 61.0
118 2 3 3 62.5
119 2 3 3 75.5
120 2 3 3 80.5
121 1 1 4 69.5
122 1 1 4 90.0
123 1 1 4 82.0
124 1 1 4 86.0
125 1 1 4 89.0
126 1 2 4 82.5
127 1 2 4 71.0
128 1 2 4 70.5
129 1 2 4 79.5
130 1 2 4 80.5
131 1 3 4 63.5
132 1 3 4 84.0
133 1 3 4 75.5
134 1 3 4 75.0
135 1 3 4 76.0
136 2 1 4 83.5
137 2 1 4 86.0
138 2 1 4 78.0
139 2 1 4 64.5
140 2 1 4 90.5
141 2 2 4 82.5
142 2 2 4 68.0
143 2 2 4 64.5
144 2 2 4 62.5
145 2 2 4 61.5
146 2 3 4 53.5
147 2 3 4 61.0
148 2 3 4 62.5
149 2 3 4 75.5
150 2 3 4 80.5
151 1 1 5 69.5
152 1 1 5 87.5
153 1 1 5 80.5
154 1 1 5 83.0
155 1 1 5 83.0
156 1 2 5 80.0
157 1 2 5 71.5
158 1 2 5 71.5
159 1 2 5 80.0
160 1 2 5 79.5
161 1 3 5 61.0
162 1 3 5 81.5
163 1 3 5 71.0
164 1 3 5 71.0
165 1 3 5 70.0
166 2 1 5 81.5
167 2 1 5 83.5
168 2 1 5 73.5
169 2 1 5 61.5
170 2 1 5 87.5
171 2 2 5 80.5
172 2 2 5 65.0
173 2 2 5 59.5
174 2 2 5 60.0
175 2 2 5 60.0
176 2 3 5 52.0
177 2 3 5 59.0
178 2 3 5 61.5
179 2 3 5 75.0
180 2 3 5 79.0
181 1 1 6 72.0
182 1 1 6 92.5
183 1 1 6 84.0
184 1 1 6 88.0
185 1 1 6 87.5
186 1 2 6 82.0
187 1 2 6 74.0
188 1 2 6 74.0
189 1 2 6 83.0
190 1 2 6 81.0
191 1 3 6 63.0
192 1 3 6 82.5
193 1 3 6 75.0
194 1 3 6 72.0
195 1 3 6 75.0
196 2 1 6 85.5
197 2 1 6 89.5
198 2 1 6 79.5
199 2 1 6 63.0
200 2 1 6 94.5
201 2 2 6 85.5
202 2 2 6 68.5
203 2 2 6 60.5
204 2 2 6 65.5
205 2 2 6 62.0
206 2 3 6 54.5
207 2 3 6 61.0
208 2 3 6 62.0
209 2 3 6 80.0
210 2 3 6 79.0
211 1 1 7 77.5
212 1 1 7 98.5
213 1 1 7 88.5
214 1 1 7 92.5
215 1 1 7 92.0
216 1 2 7 85.0
217 1 2 7 77.5
218 1 2 7 77.5
219 1 2 7 85.0
220 1 2 7 82.0
221 1 3 7 67.5
222 1 3 7 83.5
223 1 3 7 81.0
224 1 3 7 72.5
225 1 3 7 76.5
226 2 1 7 93.5
227 2 1 7 94.5
228 2 1 7 85.0
229 2 1 7 64.5
230 2 1 7 99.5
231 2 2 7 90.0
232 2 2 7 72.0
233 2 2 7 62.0
234 2 2 7 70.0
235 2 2 7 63.0
236 2 3 7 57.5
237 2 3 7 62.5
238 2 3 7 62.5
239 2 3 7 83.5
240 2 3 7 80.0