R data frames from the base, outbreaks and tidyverse packages

1 Intro

A listing of all R datasets

package_data_raw <- 
  data()$results %>%  
  as_tibble() %>%
  filter(Package != ".") %>% 
  mutate(Item = gsub("\\s*\\([^\\)]+\\)", "", Item), 
         Item = trimws(Item))

types = c()

for (i in 1:nrow(package_data_raw)){
  obj_type <- class(get(package_data_raw$Item[i])) %>% last()
  types <- c(types, obj_type) 
}
package_data_raw$Type = types


package_data <- 
  package_data_raw %>% 
  filter(Type %in% c("data.frame"))
  
packages <- package_data %>% pull(Package) %>% unique()

for (i in 1:length(packages)) {

  cat(paste("#", packages[i]), "\n", "\n")


  datasets <- 
    package_data %>% 
    filter(Package == packages[i]) %>% 
    pull(Item)
  
  titles <- 
    package_data %>% 
    filter(Package == packages[i]) %>% 
    pull(Title)
  
  for (j in 1:length(datasets)){
  
    cat(paste("##", datasets[j]), "\n", "\n")
    cat(paste0("**", titles[j], "**"))
    
    print(gt::gt(head(get(datasets[j]), 
                      20
                      )))
  
  }
  
}

2 forcats

2.1 gss_cat

A sample of categorical variables from the General Social survey

year	marital	age	race	rincome	partyid	relig	denom	tvhours
2000	Never married	26	White	$8000 to 9999	Ind,near rep	Protestant	Southern baptist	12
2000	Divorced	48	White	$8000 to 9999	Not str republican	Protestant	Baptist-dk which	NA
2000	Widowed	67	White	Not applicable	Independent	Protestant	No denomination	2
2000	Never married	39	White	Not applicable	Ind,near rep	Orthodox-christian	Not applicable	4
2000	Divorced	25	White	Not applicable	Not str democrat	None	Not applicable	1
2000	Married	25	White	$20000 - 24999	Strong democrat	Protestant	Southern baptist	NA
2000	Never married	36	White	$25000 or more	Not str republican	Christian	Not applicable	3
2000	Divorced	44	White	$7000 to 7999	Ind,near dem	Protestant	Lutheran-mo synod	NA
2000	Married	44	White	$25000 or more	Not str democrat	Protestant	Other	0
2000	Married	47	White	$25000 or more	Strong republican	Protestant	Southern baptist	3
2000	Married	53	White	$25000 or more	Not str democrat	Protestant	Other	2
2000	Married	52	White	$25000 or more	Ind,near rep	None	Not applicable	NA
2000	Married	52	White	$25000 or more	Strong democrat	Protestant	Southern baptist	1
2000	Married	51	White	$25000 or more	Strong republican	Protestant	United methodist	NA
2000	Divorced	52	White	$25000 or more	Ind,near dem	None	Not applicable	1
2000	Married	40	Black	$25000 or more	Strong democrat	Protestant	Baptist-dk which	7
2000	Widowed	77	White	Not applicable	Strong republican	Jewish	Not applicable	NA
2000	Never married	44	White	$25000 or more	Independent	None	Not applicable	3
2000	Married	40	White	$10000 - 14999	Not str democrat	Catholic	Not applicable	3
2000	Married	45	Black	Not applicable	Independent	Protestant	United methodist	NA

3 dplyr

3.1 band_instruments

Band membership

name	plays
John	guitar
Paul	bass
Keith	guitar

3.2 band_instruments2

Band membership

artist	plays
John	guitar
Paul	bass
Keith	guitar

3.3 band_members

Band membership

name	band
Mick	Stones
John	Beatles
Paul	Beatles

3.4 starwars

Starwars characters

name	height	mass	hair_color	skin_color	eye_color	birth_year	sex	gender	homeworld	species	films	vehicles	starships
Luke Skywalker	172	77	blond	fair	blue	19.0	male	masculine	Tatooine	Human	The Empire Strikes Back, Revenge of the Sith, Return of the Jedi, A New Hope, The Force Awakens	Snowspeeder, Imperial Speeder Bike	X-wing, Imperial shuttle
C-3PO	167	75	NA	gold	yellow	112.0	none	masculine	Tatooine	Droid	The Empire Strikes Back, Attack of the Clones, The Phantom Menace, Revenge of the Sith, Return of the Jedi, A New Hope
R2-D2	96	32	NA	white, blue	red	33.0	none	masculine	Naboo	Droid	The Empire Strikes Back, Attack of the Clones, The Phantom Menace, Revenge of the Sith, Return of the Jedi, A New Hope, The Force Awakens
Darth Vader	202	136	none	white	yellow	41.9	male	masculine	Tatooine	Human	The Empire Strikes Back, Revenge of the Sith, Return of the Jedi, A New Hope		TIE Advanced x1
Leia Organa	150	49	brown	light	brown	19.0	female	feminine	Alderaan	Human	The Empire Strikes Back, Revenge of the Sith, Return of the Jedi, A New Hope, The Force Awakens	Imperial Speeder Bike
Owen Lars	178	120	brown, grey	light	blue	52.0	male	masculine	Tatooine	Human	Attack of the Clones, Revenge of the Sith, A New Hope
Beru Whitesun lars	165	75	brown	light	blue	47.0	female	feminine	Tatooine	Human	Attack of the Clones, Revenge of the Sith, A New Hope
R5-D4	97	32	NA	white, red	red	NA	none	masculine	Tatooine	Droid	A New Hope
Biggs Darklighter	183	84	black	light	brown	24.0	male	masculine	Tatooine	Human	A New Hope		X-wing
Obi-Wan Kenobi	182	77	auburn, white	fair	blue-gray	57.0	male	masculine	Stewjon	Human	The Empire Strikes Back, Attack of the Clones, The Phantom Menace, Revenge of the Sith, Return of the Jedi, A New Hope	Tribubble bongo	Jedi starfighter, Trade Federation cruiser, Naboo star skiff, Jedi Interceptor, Belbullab-22 starfighter
Anakin Skywalker	188	84	blond	fair	blue	41.9	male	masculine	Tatooine	Human	Attack of the Clones, The Phantom Menace, Revenge of the Sith	Zephyr-G swoop bike, XJ-6 airspeeder	Trade Federation cruiser, Jedi Interceptor, Naboo fighter
Wilhuff Tarkin	180	NA	auburn, grey	fair	blue	64.0	male	masculine	Eriadu	Human	Revenge of the Sith, A New Hope
Chewbacca	228	112	brown	unknown	blue	200.0	male	masculine	Kashyyyk	Wookiee	The Empire Strikes Back, Revenge of the Sith, Return of the Jedi, A New Hope, The Force Awakens	AT-ST	Millennium Falcon, Imperial shuttle
Han Solo	180	80	brown	fair	brown	29.0	male	masculine	Corellia	Human	The Empire Strikes Back, Return of the Jedi, A New Hope, The Force Awakens		Millennium Falcon, Imperial shuttle
Greedo	173	74	NA	green	black	44.0	male	masculine	Rodia	Rodian	A New Hope
Jabba Desilijic Tiure	175	1358	NA	green-tan, brown	orange	600.0	hermaphroditic	masculine	Nal Hutta	Hutt	The Phantom Menace, Return of the Jedi, A New Hope
Wedge Antilles	170	77	brown	fair	hazel	21.0	male	masculine	Corellia	Human	The Empire Strikes Back, Return of the Jedi, A New Hope	Snowspeeder	X-wing
Jek Tono Porkins	180	110	brown	fair	blue	NA	male	masculine	Bestine IV	Human	A New Hope		X-wing
Yoda	66	17	white	green	brown	896.0	male	masculine	NA	Yoda’s species	The Empire Strikes Back, Attack of the Clones, The Phantom Menace, Revenge of the Sith, Return of the Jedi
Palpatine	170	75	grey	pale	yellow	82.0	male	masculine	Naboo	Human	The Empire Strikes Back, Attack of the Clones, The Phantom Menace, Revenge of the Sith, Return of the Jedi

3.5 storms

Storm tracks data

name	year	month	day	hour	lat	long	status	category	wind	pressure	tropicalstorm_force_diameter	hurricane_force_diameter
Amy	1975	6	27	0	27.5	-79.0	tropical depression	-1	25	1013	NA	NA
Amy	1975	6	27	6	28.5	-79.0	tropical depression	-1	25	1013	NA	NA
Amy	1975	6	27	12	29.5	-79.0	tropical depression	-1	25	1013	NA	NA
Amy	1975	6	27	18	30.5	-79.0	tropical depression	-1	25	1013	NA	NA
Amy	1975	6	28	0	31.5	-78.8	tropical depression	-1	25	1012	NA	NA
Amy	1975	6	28	6	32.4	-78.7	tropical depression	-1	25	1012	NA	NA
Amy	1975	6	28	12	33.3	-78.0	tropical depression	-1	25	1011	NA	NA
Amy	1975	6	28	18	34.0	-77.0	tropical depression	-1	30	1006	NA	NA
Amy	1975	6	29	0	34.4	-75.8	tropical storm	0	35	1004	NA	NA
Amy	1975	6	29	6	34.0	-74.8	tropical storm	0	40	1002	NA	NA
Amy	1975	6	29	12	33.8	-73.8	tropical storm	0	45	1000	NA	NA
Amy	1975	6	29	18	33.8	-72.8	tropical storm	0	50	998	NA	NA
Amy	1975	6	30	0	34.3	-71.6	tropical storm	0	50	998	NA	NA
Amy	1975	6	30	6	35.6	-70.8	tropical storm	0	55	998	NA	NA
Amy	1975	6	30	12	35.9	-70.5	tropical storm	0	60	987	NA	NA
Amy	1975	6	30	18	36.2	-70.2	tropical storm	0	60	987	NA	NA
Amy	1975	7	1	0	36.2	-69.8	tropical storm	0	60	984	NA	NA
Amy	1975	7	1	6	36.2	-69.4	tropical storm	0	60	984	NA	NA
Amy	1975	7	1	12	36.2	-68.3	tropical storm	0	60	984	NA	NA
Amy	1975	7	1	18	36.7	-67.2	tropical storm	0	60	984	NA	NA

4 tidyr

4.1 billboard

Song rankings for Billboard top 100 in the year 2000

artist	track	date.entered	wk1	wk2	wk3	wk4	wk5	wk6	wk7	wk8	wk9	wk10	wk11	wk12	wk13	wk14	wk15	wk16	wk17	wk18	wk19	wk20	wk21	wk22	wk23	wk24	wk25	wk26	wk27	wk28	wk29	wk30	wk31	wk32	wk33	wk34	wk35	wk36	wk37	wk38	wk39	wk40	wk41	wk42	wk43	wk44	wk45	wk46	wk47	wk48	wk49	wk50	wk51	wk52	wk53	wk54	wk55	wk56	wk57	wk58	wk59	wk60	wk61	wk62	wk63	wk64	wk65	wk66	wk67	wk68	wk69	wk70	wk71	wk72	wk73	wk74	wk75	wk76
2 Pac	Baby Don’t Cry (Keep…	2000-02-26	87	82	72	77	87	94	99	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
2Ge+her	The Hardest Part Of …	2000-09-02	91	87	92	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
3 Doors Down	Kryptonite	2000-04-08	81	70	68	67	66	57	54	53	51	51	51	51	47	44	38	28	22	18	18	14	12	7	6	6	6	5	5	4	4	4	4	3	3	3	4	5	5	9	9	15	14	13	14	16	17	21	22	24	28	33	42	42	49	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
3 Doors Down	Loser	2000-10-21	76	76	72	69	67	65	55	59	62	61	61	59	61	66	72	76	75	67	73	70	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
504 Boyz	Wobble Wobble	2000-04-15	57	34	25	17	17	31	36	49	53	57	64	70	75	76	78	85	92	96	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
98^0	Give Me Just One Nig…	2000-08-19	51	39	34	26	26	19	2	2	3	6	7	22	29	36	47	67	66	84	93	94	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
A*Teens	Dancing Queen	2000-07-08	97	97	96	95	100	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Aaliyah	I Don’t Wanna	2000-01-29	84	62	51	41	38	35	35	38	38	36	37	37	38	49	61	63	62	67	83	86	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Aaliyah	Try Again	2000-03-18	59	53	38	28	21	18	16	14	12	10	9	8	6	1	2	2	2	2	3	4	5	5	6	9	13	14	16	23	22	33	36	43	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Adams, Yolanda	Open My Heart	2000-08-26	76	76	74	69	68	67	61	58	57	59	66	68	61	67	59	63	67	71	79	89	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Adkins, Trace	More	2000-04-29	84	84	75	73	73	69	68	65	73	83	92	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Aguilera, Christina	Come On Over Baby (A…	2000-08-05	57	47	45	29	23	18	11	9	9	11	1	1	1	1	4	8	12	22	23	43	44	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Aguilera, Christina	I Turn To You	2000-04-15	50	39	30	28	21	19	20	17	17	17	17	3	3	7	10	17	25	29	29	40	43	50	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Aguilera, Christina	What A Girl Wants	1999-11-27	71	51	28	18	13	13	11	1	1	2	2	3	3	4	12	11	13	15	18	20	30	40	39	44	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Alice Deejay	Better Off Alone	2000-04-08	79	65	53	48	45	36	34	29	27	30	36	37	39	49	57	63	65	68	79	86	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Allan, Gary	Smoke Rings In The D…	2000-01-22	80	78	76	77	92	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Amber	Sexual	1999-07-17	99	99	96	96	100	93	93	96	NA	NA	99	NA	96	96	99	98	98	NA	95	88	88	79	76	69	69	59	58	58	49	44	42	46	50	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Anastacia	I’m Outta Love	2000-04-01	92	NA	NA	95	NA	NA	NA	NA	NA	NA	NA	97	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Anthony, Marc	My Baby You	2000-09-16	82	76	76	70	82	81	74	80	76	76	73	74	87	83	89	93	94	94	91	90	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Anthony, Marc	You Sang To Me	2000-02-26	77	54	50	43	30	27	21	18	15	13	13	13	13	5	2	2	5	7	9	12	12	16	20	20	22	25	26	29	35	33	40	44	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

4.2 construction

Completed construction in the US in 2018

Year	Month	1 unit	2 to 4 units	5 units or more	Northeast	Midwest	South	West
2018	January	859	NA	348	114	169	596	339
2018	February	882	NA	400	138	160	655	336
2018	March	862	NA	356	150	154	595	330
2018	April	797	NA	447	144	196	613	304
2018	May	875	NA	364	90	169	673	319
2018	June	867	NA	342	76	170	610	360
2018	July	829	NA	360	108	183	594	310
2018	August	939	NA	286	90	205	649	286
2018	September	835	NA	304	117	175	560	296

4.3 fish_encounters

Fish encounters

fish	station	seen
4842	Release	1
4842	I80_1	1
4842	Lisbon	1
4842	Rstr	1
4842	Base_TD	1
4842	BCE	1
4842	BCW	1
4842	BCE2	1
4842	BCW2	1
4842	MAE	1
4842	MAW	1
4843	Release	1
4843	I80_1	1
4843	Lisbon	1
4843	Rstr	1
4843	Base_TD	1
4843	BCE	1
4843	BCW	1
4843	BCE2	1
4843	BCW2	1

4.4 population

World Health Organization TB data

country	year	population
Afghanistan	1995	17586073
Afghanistan	1996	18415307
Afghanistan	1997	19021226
Afghanistan	1998	19496836
Afghanistan	1999	19987071
Afghanistan	2000	20595360
Afghanistan	2001	21347782
Afghanistan	2002	22202806
Afghanistan	2003	23116142
Afghanistan	2004	24018682
Afghanistan	2005	24860855
Afghanistan	2006	25631282
Afghanistan	2007	26349243
Afghanistan	2008	27032197
Afghanistan	2009	27708187
Afghanistan	2010	28397812
Afghanistan	2011	29105480
Afghanistan	2012	29824536
Afghanistan	2013	30551674
Albania	1995	3357858

4.5 relig_income

Pew religion and income survey

religion	<$10k	$10-20k	$20-30k	$30-40k	$40-50k	$50-75k	$75-100k	$100-150k	>150k	Don’t know/refused
Agnostic	27	34	60	81	76	137	122	109	84	96
Atheist	12	27	37	52	35	70	73	59	74	76
Buddhist	27	21	30	34	33	58	62	39	53	54
Catholic	418	617	732	670	638	1116	949	792	633	1489
Don’t know/refused	15	14	15	11	10	35	21	17	18	116
Evangelical Prot	575	869	1064	982	881	1486	949	723	414	1529
Hindu	1	9	7	9	11	34	47	48	54	37
Historically Black Prot	228	244	236	238	197	223	131	81	78	339
Jehovah’s Witness	20	27	24	24	21	30	15	11	6	37
Jewish	19	19	25	25	30	95	69	87	151	162
Mainline Prot	289	495	619	655	651	1107	939	753	634	1328
Mormon	29	40	48	51	56	112	85	49	42	69
Muslim	6	7	9	10	9	23	16	8	6	22
Orthodox	13	17	23	32	32	47	38	42	46	73
Other Christian	9	7	11	13	13	14	18	14	12	18
Other Faiths	20	33	40	46	49	63	46	40	41	71
Other World Religions	5	2	3	4	2	7	3	4	4	8
Unaffiliated	217	299	374	365	341	528	407	321	258	597

4.6 smiths

Some data about the Smith family

subject	time	age	weight	height
John Smith	1	33	90	1.87
Mary Smith	1	NA	NA	1.54

4.7 table1

Example tabular representations

country	year	cases	population
Afghanistan	1999	745	19987071
Afghanistan	2000	2666	20595360
Brazil	1999	37737	172006362
Brazil	2000	80488	174504898
China	1999	212258	1272915272
China	2000	213766	1280428583

4.8 table2

Example tabular representations

country	year	type	count
Afghanistan	1999	cases	745
Afghanistan	1999	population	19987071
Afghanistan	2000	cases	2666
Afghanistan	2000	population	20595360
Brazil	1999	cases	37737
Brazil	1999	population	172006362
Brazil	2000	cases	80488
Brazil	2000	population	174504898
China	1999	cases	212258
China	1999	population	1272915272
China	2000	cases	213766
China	2000	population	1280428583

4.9 table3

Example tabular representations

country	year	rate
Afghanistan	1999	745/19987071
Afghanistan	2000	2666/20595360
Brazil	1999	37737/172006362
Brazil	2000	80488/174504898
China	1999	212258/1272915272
China	2000	213766/1280428583

4.10 table4a

Example tabular representations

country	1999	2000
Afghanistan	745	2666
Brazil	37737	80488
China	212258	213766

4.11 table4b

Example tabular representations

country	1999	2000
Afghanistan	19987071	20595360
Brazil	172006362	174504898
China	1272915272	1280428583

4.12 table5

Example tabular representations

country	century	year	rate
Afghanistan	19	99	745/19987071
Afghanistan	20	00	2666/20595360
Brazil	19	99	37737/172006362
Brazil	20	00	80488/174504898
China	19	99	212258/1272915272
China	20	00	213766/1280428583

4.13 us_rent_income

US rent and income data

GEOID	NAME	variable	estimate	moe
01	Alabama	income	24476	136
01	Alabama	rent	747	3
02	Alaska	income	32940	508
02	Alaska	rent	1200	13
04	Arizona	income	27517	148
04	Arizona	rent	972	4
05	Arkansas	income	23789	165
05	Arkansas	rent	709	5
06	California	income	29454	109
06	California	rent	1358	3
08	Colorado	income	32401	109
08	Colorado	rent	1125	5
09	Connecticut	income	35326	195
09	Connecticut	rent	1123	5
10	Delaware	income	31560	247
10	Delaware	rent	1076	10
11	District of Columbia	income	43198	681
11	District of Columbia	rent	1424	17
12	Florida	income	25952	70
12	Florida	rent	1077	3

4.14 who

World Health Organization TB data

country	iso2	iso3	year	new_sp_m014	new_sp_m1524	new_sp_m2534	new_sp_m3544	new_sp_m4554	new_sp_m5564	new_sp_m65	new_sp_f014	new_sp_f1524	new_sp_f2534	new_sp_f3544	new_sp_f4554	new_sp_f5564	new_sp_f65	new_sn_m014	new_sn_m1524	new_sn_m2534	new_sn_m3544	new_sn_m4554	new_sn_m5564	new_sn_m65	new_sn_f014	new_sn_f1524	new_sn_f2534	new_sn_f3544	new_sn_f4554	new_sn_f5564	new_sn_f65	new_ep_m014	new_ep_m1524	new_ep_m2534	new_ep_m3544	new_ep_m4554	new_ep_m5564	new_ep_m65	new_ep_f014	new_ep_f1524	new_ep_f2534	new_ep_f3544	new_ep_f4554	new_ep_f5564	new_ep_f65	newrel_m014	newrel_m1524	newrel_m2534	newrel_m3544	newrel_m4554	newrel_m5564	newrel_m65	newrel_f014	newrel_f1524	newrel_f2534	newrel_f3544	newrel_f4554	newrel_f5564	newrel_f65
Afghanistan	AF	AFG	1980	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1981	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1982	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1983	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1984	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1985	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1986	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1987	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1988	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1989	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1990	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1991	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1992	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1993	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1994	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1995	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1996	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1997	0	10	6	3	5	2	0	5	38	36	14	8	0	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1998	30	129	128	90	89	64	41	45	350	419	194	118	61	20	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
Afghanistan	AF	AFG	1999	8	55	55	47	34	21	8	25	139	160	110	50	25	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

4.15 world_bank_pop

Population data from the world bank

country	indicator	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017
ABW	SP.URB.TOTL	4.244400e+04	4.304800e+04	4.367000e+04	4.424600e+04	4.466900e+04	4.488900e+04	4.488100e+04	4.468600e+04	4.437500e+04	4.405200e+04	4.377800e+04	4.382200e+04	4.406400e+04	4.436000e+04	4.467400e+04	4.497900e+04	4.527500e+04	4.557200e+04
ABW	SP.URB.GROW	1.182632e+00	1.413021e+00	1.434560e+00	1.310360e+00	9.514777e-01	4.913027e-01	-1.782333e-02	-4.354289e-01	-6.984006e-01	-7.305493e-01	-6.239346e-01	1.004566e-01	5.507148e-01	6.695040e-01	7.053514e-01	6.804037e-01	6.559290e-01	6.538489e-01
ABW	SP.POP.TOTL	9.085300e+04	9.289800e+04	9.499200e+04	9.701700e+04	9.873700e+04	1.000310e+05	1.008320e+05	1.012200e+05	1.013530e+05	1.014530e+05	1.016690e+05	1.020530e+05	1.025770e+05	1.031870e+05	1.037950e+05	1.043410e+05	1.048220e+05	1.052640e+05
ABW	SP.POP.GROW	2.055027e+00	2.225930e+00	2.229056e+00	2.109354e+00	1.757353e+00	1.302039e+00	7.975628e-01	3.840600e-01	1.313107e-01	9.861642e-02	2.126801e-01	3.769848e-01	5.121450e-01	5.929140e-01	5.874924e-01	5.246582e-01	4.599292e-01	4.207807e-01
AFG	SP.URB.TOTL	4.436299e+06	4.648055e+06	4.892951e+06	5.155686e+06	5.426770e+06	5.691823e+06	5.931413e+06	6.151939e+06	6.364968e+06	6.588859e+06	6.837008e+06	7.114615e+06	7.416385e+06	7.733964e+06	8.054214e+06	8.367663e+06	8.670939e+06	8.971345e+06
AFG	SP.URB.GROW	3.912228e+00	4.662838e+00	5.134675e+00	5.230459e+00	5.124393e+00	4.768647e+00	4.123188e+00	3.650485e+00	3.404189e+00	3.457099e+00	3.697002e+00	3.980091e+00	4.154062e+00	4.192980e+00	4.057389e+00	3.817920e+00	3.560246e+00	3.405852e+00
AFG	SP.POP.TOTL	2.009376e+07	2.096646e+07	2.197992e+07	2.306485e+07	2.411898e+07	2.507080e+07	2.589345e+07	2.661679e+07	2.729403e+07	2.800433e+07	2.880317e+07	2.970860e+07	3.069696e+07	3.173169e+07	3.275802e+07	3.373649e+07	3.465603e+07	3.553008e+07
AFG	SP.POP.GROW	3.494659e+00	4.251504e+00	4.720528e+00	4.818041e+00	4.468918e+00	3.870470e+00	3.228630e+00	2.755225e+00	2.512574e+00	2.569114e+00	2.812617e+00	3.095119e+00	3.272703e+00	3.315224e+00	3.183201e+00	2.943234e+00	2.689163e+00	2.490790e+00
AGO	SP.URB.TOTL	8.234766e+06	8.708000e+06	9.218787e+06	9.765197e+06	1.034351e+07	1.094942e+07	1.150175e+07	1.207871e+07	1.268182e+07	1.331190e+07	1.397077e+07	1.465901e+07	1.537591e+07	1.611949e+07	1.688748e+07	1.767562e+07	1.848355e+07	1.931177e+07
AGO	SP.URB.GROW	5.437494e+00	5.587720e+00	5.700132e+00	5.758127e+00	5.753414e+00	5.692797e+00	4.921217e+00	4.894529e+00	4.872555e+00	4.848851e+00	4.830877e+00	4.808822e+00	4.774657e+00	4.722723e+00	4.654324e+00	4.561361e+00	4.469503e+00	4.383387e+00
AGO	SP.POP.TOTL	1.644092e+07	1.698327e+07	1.757265e+07	1.820337e+07	1.886572e+07	1.955254e+07	2.026240e+07	2.099769e+07	2.175942e+07	2.254955e+07	2.336913e+07	2.421856e+07	2.509615e+07	2.599834e+07	2.692047e+07	2.785930e+07	2.881346e+07	2.978419e+07
AGO	SP.POP.GROW	3.032943e+00	3.245491e+00	3.411515e+00	3.526303e+00	3.573962e+00	3.575900e+00	3.566160e+00	3.564539e+00	3.563448e+00	3.566821e+00	3.570099e+00	3.570352e+00	3.559496e+00	3.531824e+00	3.485413e+00	3.428021e+00	3.367572e+00	3.313507e+00
ALB	SP.URB.TOTL	1.289391e+06	1.298584e+06	1.327220e+06	1.354848e+06	1.381828e+06	1.407298e+06	1.430886e+06	1.452398e+06	1.473392e+06	1.495260e+06	1.519519e+06	1.546929e+06	1.575788e+06	1.603505e+06	1.630119e+06	1.654503e+06	1.680247e+06	1.706345e+06
ALB	SP.URB.GROW	7.424786e-01	7.104426e-01	2.181209e+00	2.060274e+00	1.971799e+00	1.826429e+00	1.662228e+00	1.492215e+00	1.435124e+00	1.473288e+00	1.609373e+00	1.787784e+00	1.848379e+00	1.743639e+00	1.646116e+00	1.484764e+00	1.544014e+00	1.541285e+00
ALB	SP.POP.TOTL	3.089027e+06	3.060173e+06	3.051010e+06	3.039616e+06	3.026939e+06	3.011487e+06	2.992547e+06	2.970017e+06	2.947314e+06	2.927519e+06	2.913021e+06	2.905195e+06	2.900401e+06	2.895092e+06	2.889104e+06	2.880703e+06	2.876101e+06	2.873457e+06
ALB	SP.POP.GROW	-6.373568e-01	-9.384704e-01	-2.998767e-01	-3.741492e-01	-4.179314e-01	-5.117901e-01	-6.309112e-01	-7.557188e-01	-7.673430e-01	-6.738940e-01	-4.964620e-01	-2.690173e-01	-1.651510e-01	-1.832114e-01	-2.070470e-01	-2.912058e-01	-1.598804e-01	-9.197229e-02
AND	SP.URB.TOTL	6.041700e+04	6.199100e+04	6.419400e+04	6.674700e+04	6.919200e+04	7.120500e+04	7.273600e+04	7.384300e+04	7.464000e+04	7.509700e+04	7.500700e+04	7.430900e+04	7.305900e+04	7.152700e+04	7.006600e+04	6.892100e+04	6.819900e+04	6.784500e+04
AND	SP.URB.GROW	1.279314e+00	2.571869e+00	3.492054e+00	3.899960e+00	3.597590e+00	2.867779e+00	2.127341e+00	1.510477e+00	1.073534e+00	6.104055e-01	-1.199169e-01	-9.349368e-01	-1.696474e+00	-2.119233e+00	-2.063735e+00	-1.647673e+00	-1.053102e+00	-5.204210e-01
AND	SP.POP.TOTL	6.539000e+04	6.734100e+04	7.004900e+04	7.318200e+04	7.624400e+04	7.886700e+04	8.099100e+04	8.268300e+04	8.386100e+04	8.446200e+04	8.444900e+04	8.375100e+04	8.243100e+04	8.078800e+04	7.922300e+04	7.801400e+04	7.728100e+04	7.696500e+04
AND	SP.POP.GROW	1.572166e+00	2.939992e+00	3.942573e+00	4.375449e+00	4.098923e+00	3.382417e+00	2.657515e+00	2.067598e+00	1.414665e+00	7.141063e-01	-1.539272e-02	-8.299691e-01	-1.588653e+00	-2.013314e+00	-1.956178e+00	-1.537836e+00	-9.440168e-01	-4.097357e-01

5 ggplot2

5.1 diamonds

Prices of over 50,000 round cut diamonds

carat	cut	color	clarity	depth	table	price	x	y	z
0.23	Ideal	E	SI2	61.5	55	326	3.95	3.98	2.43
0.21	Premium	E	SI1	59.8	61	326	3.89	3.84	2.31
0.23	Good	E	VS1	56.9	65	327	4.05	4.07	2.31
0.29	Premium	I	VS2	62.4	58	334	4.20	4.23	2.63
0.31	Good	J	SI2	63.3	58	335	4.34	4.35	2.75
0.24	Very Good	J	VVS2	62.8	57	336	3.94	3.96	2.48
0.24	Very Good	I	VVS1	62.3	57	336	3.95	3.98	2.47
0.26	Very Good	H	SI1	61.9	55	337	4.07	4.11	2.53
0.22	Fair	E	VS2	65.1	61	337	3.87	3.78	2.49
0.23	Very Good	H	VS1	59.4	61	338	4.00	4.05	2.39
0.30	Good	J	SI1	64.0	55	339	4.25	4.28	2.73
0.23	Ideal	J	VS1	62.8	56	340	3.93	3.90	2.46
0.22	Premium	F	SI1	60.4	61	342	3.88	3.84	2.33
0.31	Ideal	J	SI2	62.2	54	344	4.35	4.37	2.71
0.20	Premium	E	SI2	60.2	62	345	3.79	3.75	2.27
0.32	Premium	E	I1	60.9	58	345	4.38	4.42	2.68
0.30	Ideal	I	SI2	62.0	54	348	4.31	4.34	2.68
0.30	Good	J	SI1	63.4	54	351	4.23	4.29	2.70
0.30	Good	J	SI1	63.8	56	351	4.23	4.26	2.71
0.30	Very Good	J	SI1	62.7	59	351	4.21	4.27	2.66

5.2 economics

US economic time series

date	pce	pop	psavert	uempmed	unemploy
1967-07-01	506.7	198712	12.6	4.5	2944
1967-08-01	509.8	198911	12.6	4.7	2945
1967-09-01	515.6	199113	11.9	4.6	2958
1967-10-01	512.2	199311	12.9	4.9	3143
1967-11-01	517.4	199498	12.8	4.7	3066
1967-12-01	525.1	199657	11.8	4.8	3018
1968-01-01	530.9	199808	11.7	5.1	2878
1968-02-01	533.6	199920	12.3	4.5	3001
1968-03-01	544.3	200056	11.7	4.1	2877
1968-04-01	544.0	200208	12.3	4.6	2709
1968-05-01	549.8	200361	12.0	4.4	2740
1968-06-01	556.3	200536	11.7	4.4	2938
1968-07-01	563.2	200706	10.7	4.5	2883
1968-08-01	567.0	200898	10.5	4.2	2768
1968-09-01	568.2	201095	10.6	4.6	2686
1968-10-01	571.6	201290	10.8	4.8	2689
1968-11-01	576.7	201466	10.6	4.4	2715
1968-12-01	576.5	201621	11.1	4.4	2685
1969-01-01	583.5	201760	10.3	4.4	2718
1969-02-01	588.7	201881	9.7	4.9	2692

5.3 economics_long

US economic time series

date	variable	value	value01
1967-07-01	pce	506.7	0.0000000000
1967-08-01	pce	509.8	0.0002652497
1967-09-01	pce	515.6	0.0007615234
1967-10-01	pce	512.2	0.0004706043
1967-11-01	pce	517.4	0.0009155394
1967-12-01	pce	525.1	0.0015743854
1968-01-01	pce	530.9	0.0020706591
1968-02-01	pce	533.6	0.0023016831
1968-03-01	pce	544.3	0.0032172224
1968-04-01	pce	544.0	0.0031915531
1968-05-01	pce	549.8	0.0036878267
1968-06-01	pce	556.3	0.0042439955
1968-07-01	pce	563.2	0.0048343901
1968-08-01	pce	567.0	0.0051595349
1968-09-01	pce	568.2	0.0052622122
1968-10-01	pce	571.6	0.0055531312
1968-11-01	pce	576.7	0.0059895098
1968-12-01	pce	576.5	0.0059723969
1969-01-01	pce	583.5	0.0065713479
1969-02-01	pce	588.7	0.0070162829

5.4 faithfuld

2d density estimate of Old Faithful data

eruptions	waiting	density
1.600000	43	0.003216159
1.647297	43	0.003835375
1.694595	43	0.004435548
1.741892	43	0.004977614
1.789189	43	0.005424238
1.836486	43	0.005744544
1.883784	43	0.005918012
1.931081	43	0.005936762
1.978378	43	0.005805861
2.025676	43	0.005541706
2.072973	43	0.005168979
2.120270	43	0.004716903
2.167568	43	0.004215592
2.214865	43	0.003693071
2.262162	43	0.003173317
2.309459	43	0.002675315
2.356757	43	0.002212951
2.404054	43	0.001795434
2.451351	43	0.001427956
2.498649	43	0.001112406

5.5 luv_colours

‘colors()’ in Luv space

L	u	v	col
9341.570	-3.370649e-12	0.0000	white
9100.962	-4.749170e+02	-635.3502	aliceblue
8809.518	1.008865e+03	1668.0042	antiquewhite
8935.225	1.065698e+03	1674.5948	antiquewhite1
8452.499	1.014911e+03	1609.5923	antiquewhite2
7498.378	9.029892e+02	1401.7026	antiquewhite3
5512.045	6.054413e+02	1027.3461	antiquewhite4
8669.674	-5.536858e+03	2237.0224	aquamarine
8669.674	-5.536858e+03	2237.0224	aquamarine1
8202.140	-5.253706e+03	2104.2950	aquamarine2
7277.339	-4.653237e+03	1911.1716	aquamarine3
5330.488	-3.408627e+03	1336.8782	aquamarine4
9249.918	-8.118799e+02	-175.0022	azure
9249.918	-8.118799e+02	-175.0022	azure1
8752.459	-7.682056e+02	-165.5881	azure2
7766.124	-6.783397e+02	-146.2173	azure3
5688.546	-4.886049e+02	-105.3196	azure4
8997.169	1.376358e+02	1854.8768	beige
8664.919	1.864555e+03	2650.6931	bisque
8664.919	1.864555e+03	2650.6931	bisque1

5.6 midwest

Midwest demographics

PID	county	state	area	poptotal	popdensity	popwhite	popblack	popamerindian	popasian	popother	percwhite	percblack	percamerindan	percasian	percother	popadults	perchsd	percollege	percprof	poppovertyknown	percpovertyknown	percbelowpoverty	percchildbelowpovert	percadultpoverty	percelderlypoverty	inmetro	category
561	ADAMS	IL	0.052	66090	1270.9615	63917	1702	98	249	124	96.71206	2.57527614	0.14828264	0.37675897	0.18762294	43298	75.10740	19.63139	4.355859	63628	96.27478	13.151443	18.011717	11.009776	12.443812	0	AAR
562	ALEXANDER	IL	0.014	10626	759.0000	7054	3496	19	48	9	66.38434	32.90043290	0.17880670	0.45172219	0.08469791	6724	59.72635	11.24331	2.870315	10529	99.08714	32.244278	45.826514	27.385647	25.228976	0	LHR
563	BOND	IL	0.022	14991	681.4091	14477	429	35	16	34	96.57128	2.86171703	0.23347342	0.10673071	0.22680275	9669	69.33499	17.03382	4.488572	14235	94.95697	12.068844	14.036061	10.852090	12.697410	0	AAR
564	BOONE	IL	0.017	30806	1812.1176	29344	127	46	150	1139	95.25417	0.41225735	0.14932156	0.48691813	3.69733169	19272	75.47219	17.27895	4.197800	30337	98.47757	7.209019	11.179536	5.536013	6.217047	1	ALU
565	BROWN	IL	0.018	5836	324.2222	5264	547	14	5	6	90.19877	9.37285812	0.23989034	0.08567512	0.10281014	3979	68.86152	14.47600	3.367680	4815	82.50514	13.520249	13.022889	11.143211	19.200000	0	AAR
566	BUREAU	IL	0.050	35688	713.7600	35157	50	65	195	221	98.51210	0.14010312	0.18213405	0.54640215	0.61925577	23444	76.62941	18.90462	3.275891	35107	98.37200	10.399635	14.158819	8.179287	11.008586	0	AAR
567	CALHOUN	IL	0.017	5322	313.0588	5298	1	8	15	0	99.54904	0.01878993	0.15031943	0.28184893	0.00000000	3583	62.82445	11.91739	3.209601	5241	98.47802	15.149781	13.787761	12.932331	21.085271	0	LAR
568	CARROLL	IL	0.027	16805	622.4074	16519	111	30	61	84	98.29813	0.66051770	0.17851830	0.36298721	0.49985123	11323	75.95160	16.19712	3.055727	16455	97.91729	11.710726	17.225462	10.027037	9.525052	0	AAR
569	CASS	IL	0.024	13437	559.8750	13384	16	8	23	6	99.60557	0.11907420	0.05953710	0.17116916	0.04465282	8825	72.27195	14.10765	3.206799	13081	97.35060	13.875086	17.994784	11.914343	13.660180	0	AAR
570	CHAMPAIGN	IL	0.058	173025	2983.1897	146506	16559	331	8033	1596	84.67331	9.57029331	0.19130183	4.64268169	0.92241006	95971	87.49935	41.29581	17.757448	154934	89.54429	15.572437	14.132234	17.562728	8.105017	1	HAU
571	CHRISTIAN	IL	0.042	34418	819.4762	34176	82	51	89	20	99.29688	0.23824743	0.14817828	0.25858562	0.05810913	22945	73.07474	13.56723	3.089998	33788	98.16956	11.708299	16.320612	9.569700	11.490641	0	AAR
572	CLARK	IL	0.030	15921	530.7000	15842	10	26	36	7	99.50380	0.06281012	0.16330632	0.22611645	0.04396709	10734	71.33408	15.11086	2.776225	15615	98.07801	12.007685	15.321547	10.131775	12.595420	0	AAR
573	CLAY	IL	0.028	14460	516.4286	14403	4	17	29	7	99.60581	0.02766252	0.11756570	0.20055325	0.04840941	9647	65.56442	13.68301	2.788432	14248	98.53389	16.774284	20.582578	14.464114	17.670078	0	LAR
574	CLINTON	IL	0.029	33944	1170.4828	32688	1021	48	104	83	96.29979	3.00789536	0.14140938	0.30638699	0.24452039	21563	67.16598	15.38747	2.875296	32190	94.83267	10.223672	13.299402	9.253834	8.323176	1	LAU
575	COLES	IL	0.030	51644	1721.4667	50177	925	92	341	109	97.15940	1.79110836	0.17814267	0.66028968	0.21106034	29136	76.10516	25.17504	8.144563	45693	88.47688	16.748736	16.341941	18.792914	10.993608	0	AAR
576	COOK	IL	0.058	5105067	88018.3966	3204947	1317147	10289	188565	384119	62.77972	25.80077790	0.20154486	3.69368316	7.52426951	3291995	73.40582	28.01812	8.329964	5023523	98.40269	14.198303	22.293497	11.665542	10.825269	1	AAU
577	CRAWFORD	IL	0.026	19464	748.6154	19300	63	34	48	19	99.15742	0.32367448	0.17468146	0.24660912	0.09761611	13317	76.03064	16.98581	3.334084	19123	98.24805	10.537050	13.809825	8.870243	10.803387	0	AAR
578	CUMBERLAND	IL	0.020	10670	533.5000	10627	5	6	26	6	99.59700	0.04686036	0.05623243	0.24367385	0.05623243	6727	72.24617	14.59789	2.690650	10590	99.25023	12.049103	13.603185	9.822264	15.284626	0	AAR
579	DE KALB	IL	0.038	77932	2050.8421	72968	2069	123	1751	1021	93.63034	2.65487861	0.15782990	2.24683057	1.31011651	41817	83.87976	32.83593	11.150967	69127	88.70169	13.544635	8.678238	17.047419	6.453908	1	HAU
580	DE WITT	IL	0.023	16516	718.0870	16387	25	37	43	24	99.21894	0.15136837	0.22402519	0.26035360	0.14531364	10941	74.64583	16.19596	3.308656	16238	98.31678	10.315310	13.568426	7.955993	12.255345	0	AAR

5.7 mpg

Fuel economy data from 1999 to 2008 for 38 popular models of cars

manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
audi	a4	2.0	2008	4	manual(m6)	f	20	31	p	compact
audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact
audi	a4	2.8	1999	6	manual(m5)	f	18	26	p	compact
audi	a4	3.1	2008	6	auto(av)	f	18	27	p	compact
audi	a4 quattro	1.8	1999	4	manual(m5)	4	18	26	p	compact
audi	a4 quattro	1.8	1999	4	auto(l5)	4	16	25	p	compact
audi	a4 quattro	2.0	2008	4	manual(m6)	4	20	28	p	compact
audi	a4 quattro	2.0	2008	4	auto(s6)	4	19	27	p	compact
audi	a4 quattro	2.8	1999	6	auto(l5)	4	15	25	p	compact
audi	a4 quattro	2.8	1999	6	manual(m5)	4	17	25	p	compact
audi	a4 quattro	3.1	2008	6	auto(s6)	4	17	25	p	compact
audi	a4 quattro	3.1	2008	6	manual(m6)	4	15	25	p	compact
audi	a6 quattro	2.8	1999	6	auto(l5)	4	15	24	p	midsize
audi	a6 quattro	3.1	2008	6	auto(s6)	4	17	25	p	midsize
audi	a6 quattro	4.2	2008	8	auto(s6)	4	16	23	p	midsize
chevrolet	c1500 suburban 2wd	5.3	2008	8	auto(l4)	r	14	20	r	suv
chevrolet	c1500 suburban 2wd	5.3	2008	8	auto(l4)	r	11	15	e	suv

5.8 msleep

An updated and expanded version of the mammals sleep dataset

name	genus	vore	order	conservation	sleep_total	sleep_rem	sleep_cycle	awake	brainwt	bodywt
Cheetah	Acinonyx	carni	Carnivora	lc	12.1	NA	NA	11.9	NA	50.000
Owl monkey	Aotus	omni	Primates	NA	17.0	1.8	NA	7.0	0.01550	0.480
Mountain beaver	Aplodontia	herbi	Rodentia	nt	14.4	2.4	NA	9.6	NA	1.350
Greater short-tailed shrew	Blarina	omni	Soricomorpha	lc	14.9	2.3	0.1333333	9.1	0.00029	0.019
Cow	Bos	herbi	Artiodactyla	domesticated	4.0	0.7	0.6666667	20.0	0.42300	600.000
Three-toed sloth	Bradypus	herbi	Pilosa	NA	14.4	2.2	0.7666667	9.6	NA	3.850
Northern fur seal	Callorhinus	carni	Carnivora	vu	8.7	1.4	0.3833333	15.3	NA	20.490
Vesper mouse	Calomys	NA	Rodentia	NA	7.0	NA	NA	17.0	NA	0.045
Dog	Canis	carni	Carnivora	domesticated	10.1	2.9	0.3333333	13.9	0.07000	14.000
Roe deer	Capreolus	herbi	Artiodactyla	lc	3.0	NA	NA	21.0	0.09820	14.800
Goat	Capri	herbi	Artiodactyla	lc	5.3	0.6	NA	18.7	0.11500	33.500
Guinea pig	Cavis	herbi	Rodentia	domesticated	9.4	0.8	0.2166667	14.6	0.00550	0.728
Grivet	Cercopithecus	omni	Primates	lc	10.0	0.7	NA	14.0	NA	4.750
Chinchilla	Chinchilla	herbi	Rodentia	domesticated	12.5	1.5	0.1166667	11.5	0.00640	0.420
Star-nosed mole	Condylura	omni	Soricomorpha	lc	10.3	2.2	NA	13.7	0.00100	0.060
African giant pouched rat	Cricetomys	omni	Rodentia	NA	8.3	2.0	NA	15.7	0.00660	1.000
Lesser short-tailed shrew	Cryptotis	omni	Soricomorpha	lc	9.1	1.4	0.1500000	14.9	0.00014	0.005
Long-nosed armadillo	Dasypus	carni	Cingulata	lc	17.4	3.1	0.3833333	6.6	0.01080	3.500
Tree hyrax	Dendrohyrax	herbi	Hyracoidea	lc	5.3	0.5	NA	18.7	0.01230	2.950
North American Opossum	Didelphis	omni	Didelphimorphia	lc	18.0	4.9	0.3333333	6.0	0.00630	1.700

5.9 presidential

Terms of 11 presidents from Eisenhower to Obama

name	start	end	party
Eisenhower	1953-01-20	1961-01-20	Republican
Kennedy	1961-01-20	1963-11-22	Democratic
Johnson	1963-11-22	1969-01-20	Democratic
Nixon	1969-01-20	1974-08-09	Republican
Ford	1974-08-09	1977-01-20	Republican
Carter	1977-01-20	1981-01-20	Democratic
Reagan	1981-01-20	1989-01-20	Republican
Bush	1989-01-20	1993-01-20	Republican
Clinton	1993-01-20	2001-01-20	Democratic
Bush	2001-01-20	2009-01-20	Republican
Obama	2009-01-20	2017-01-20	Democratic

5.10 seals

Vector field of seal movements

lat	long	delta_long	delta_lat
29.7	-172.8	-0.91504624	0.143475254
30.7	-172.8	-0.86701252	0.128388724
31.7	-172.8	-0.81892489	0.113232481
32.7	-172.8	-0.77077630	0.098020371
33.7	-172.8	-0.72255967	0.082766237
34.7	-172.8	-0.67426795	0.067483925
35.7	-172.8	-0.62589407	0.052187280
36.7	-172.8	-0.57743097	0.036890146
37.7	-172.8	-0.52887159	0.021606367
38.7	-172.8	-0.48020886	0.006349790
39.7	-172.8	-0.43143573	-0.008865742
40.7	-172.8	-0.38254512	-0.024026384
41.7	-172.8	-0.33352997	-0.039118291
42.7	-172.8	-0.28438323	-0.054127618
43.7	-172.8	-0.23509783	-0.069040521
44.7	-172.8	-0.18566671	-0.083843154
45.7	-172.8	-0.13608280	-0.098521673
46.7	-172.8	-0.08633904	-0.113062233
47.7	-172.8	-0.03642838	-0.127450990
48.7	-172.8	0.01365626	-0.141674098

5.11 txhousing

Housing sales in TX

city	year	month	sales	volume	median	listings	inventory	date
Abilene	2000	1	72	5380000	71400	701	6.3	2000.000
Abilene	2000	2	98	6505000	58700	746	6.6	2000.083
Abilene	2000	3	130	9285000	58100	784	6.8	2000.167
Abilene	2000	4	98	9730000	68600	785	6.9	2000.250
Abilene	2000	5	141	10590000	67300	794	6.8	2000.333
Abilene	2000	6	156	13910000	66900	780	6.6	2000.417
Abilene	2000	7	152	12635000	73500	742	6.2	2000.500
Abilene	2000	8	131	10710000	75000	765	6.4	2000.583
Abilene	2000	9	104	7615000	64500	771	6.5	2000.667
Abilene	2000	10	101	7040000	59300	764	6.6	2000.750
Abilene	2000	11	100	7890000	70900	721	6.2	2000.833
Abilene	2000	12	92	7285000	65000	658	5.7	2000.917
Abilene	2001	1	75	5730000	64500	779	6.8	2001.000
Abilene	2001	2	112	8670000	68900	700	6.0	2001.083
Abilene	2001	3	118	9550000	72300	738	6.4	2001.167
Abilene	2001	4	105	8705000	71500	810	7.0	2001.250
Abilene	2001	5	150	11850000	71000	772	6.6	2001.333
Abilene	2001	6	139	11290000	78100	825	7.2	2001.417
Abilene	2001	7	134	13175000	86700	801	7.1	2001.500
Abilene	2001	8	151	11840000	69000	891	7.7	2001.583

6 outbreaks

6.1 covid19_england_nhscalls_2020

Potential COVID19 cases reported through NHS pathways

site_type	date	sex	age	ccg_code	ccg_name	count	postcode	nhs_region	day	weekday
111	2020-03-18	female	missing	e38000062	nhs_gloucestershire_ccg	1	gl34fe	South West	0	rest_of_week
111	2020-03-18	female	missing	e38000163	nhs_south_tyneside_ccg	1	ne325nn	North East and Yorkshire	0	rest_of_week
111	2020-03-18	female	0-18	e38000001	nhs_airedale_wharfedale_and_craven_ccg	8	bd57jr	North East and Yorkshire	0	rest_of_week
111	2020-03-18	female	0-18	e38000002	nhs_ashford_ccg	7	tn254ab	South East	0	rest_of_week
111	2020-03-18	female	0-18	e38000004	nhs_barking_and_dagenham_ccg	35	rm13ae	London	0	rest_of_week
111	2020-03-18	female	0-18	e38000005	nhs_barnet_ccg	9	n111np	London	0	rest_of_week
111	2020-03-18	female	0-18	e38000006	nhs_barnsley_ccg	11	s752py	North East and Yorkshire	0	rest_of_week
111	2020-03-18	female	0-18	e38000007	nhs_basildon_and_brentwood_ccg	19	ss143hg	East of England	0	rest_of_week
111	2020-03-18	female	0-18	e38000008	nhs_bassetlaw_ccg	6	dn227xf	North East and Yorkshire	0	rest_of_week
111	2020-03-18	female	0-18	e38000009	nhs_bath_and_north_east_somerset_ccg	9	ba25rp	South West	0	rest_of_week
111	2020-03-18	female	0-18	e38000010	nhs_bedfordshire_ccg	27	mk454hr	East of England	0	rest_of_week
111	2020-03-18	female	0-18	e38000011	nhs_bexley_ccg	13	da67at	London	0	rest_of_week
111	2020-03-18	female	0-18	e38000014	nhs_blackburn_with_darwen_ccg	9	bb12fd	North West	0	rest_of_week
111	2020-03-18	female	0-18	e38000015	nhs_blackpool_ccg	13	fy16jx	North West	0	rest_of_week
111	2020-03-18	female	0-18	e38000016	nhs_bolton_ccg	20	bl11pp	North West	0	rest_of_week
111	2020-03-18	female	0-18	e38000018	nhs_bradford_city_ccg	6	bd57jr	North East and Yorkshire	0	rest_of_week
111	2020-03-18	female	0-18	e38000019	nhs_bradford_districts_ccg	21	bd57jr	North East and Yorkshire	0	rest_of_week
111	2020-03-18	female	0-18	e38000020	nhs_brent_ccg	21	ha04uz	London	0	rest_of_week
111	2020-03-18	female	0-18	e38000021	nhs_brighton_and_hove_ccg	13	bn34ah	South East	0	rest_of_week
111	2020-03-18	female	0-18	e38000023	nhs_bromley_ccg	11	br33ql	London	0	rest_of_week

6.2 dengue_fais_2011

Dengue on the island of Fais, Micronesia, 2011

onset_date	nr	value
2011-09-15	7	0
2011-09-22	14	0
2011-09-29	21	0
2011-10-06	28	0
2011-10-13	35	0
2011-10-20	42	0
2011-10-27	49	0
2011-11-03	56	0
2011-11-10	63	1
2011-11-11	64	0
2011-11-12	65	0
2011-11-13	66	0
2011-11-14	67	0
2011-11-15	68	0
2011-11-16	69	0
2011-11-17	70	0
2011-11-18	71	0
2011-11-19	72	0
2011-11-20	73	0
2011-11-21	74	0

6.3 dengue_yap_2011

Dengue on the Yap Main Islands, Micronesia, 2011

onset_date	nr	value
2011-07-07	7	0
2011-07-14	14	0
2011-07-21	21	0
2011-07-28	28	0
2011-08-04	35	0
2011-08-11	42	0
2011-08-18	49	0
2011-08-25	56	0
2011-09-01	63	1
2011-09-02	64	2
2011-09-03	65	0
2011-09-04	66	0
2011-09-05	67	0
2011-09-06	68	0
2011-09-07	69	0
2011-09-08	70	0
2011-09-09	71	1
2011-09-10	72	0
2011-09-11	73	0
2011-09-12	74	0

6.4 ebola_kikwit_1995

Ebola in Kikwit, Democratic Republic of the Congo, 1995

date	onset	death	reporting
1995-01-06	1	0	TRUE
1995-01-07	0	0	FALSE
1995-01-08	0	0	FALSE
1995-01-09	0	0	FALSE
1995-01-10	0	0	FALSE
1995-01-11	0	0	FALSE
1995-01-12	0	0	FALSE
1995-01-13	0	0	FALSE
1995-01-14	0	0	FALSE
1995-01-15	0	0	FALSE
1995-01-16	0	0	FALSE
1995-01-17	0	0	FALSE
1995-01-18	0	0	FALSE
1995-01-19	0	0	FALSE
1995-01-20	0	0	FALSE
1995-01-21	0	0	FALSE
1995-01-22	0	0	FALSE
1995-01-23	0	0	FALSE
1995-01-24	0	0	FALSE
1995-01-25	0	0	FALSE

6.5 ebola_sierraleone_2014

Ebola in Sierra Leone, 2014

id	age	sex	status	date_of_onset	date_of_sample	district	chiefdom
1	20	F	confirmed	2014-05-18	2014-05-23	Kailahun	Kissi Teng
2	42	F	confirmed	2014-05-20	2014-05-25	Kailahun	Kissi Teng
3	45	F	confirmed	2014-05-20	2014-05-25	Kailahun	Kissi Tonge
4	15	F	confirmed	2014-05-21	2014-05-26	Kailahun	Kissi Teng
5	19	F	confirmed	2014-05-21	2014-05-26	Kailahun	Kissi Teng
6	55	F	confirmed	2014-05-21	2014-05-26	Kailahun	Kissi Teng
7	50	F	confirmed	2014-05-21	2014-05-26	Kailahun	Kissi Teng
8	8	F	confirmed	2014-05-22	2014-05-27	Kailahun	Kissi Teng
9	54	F	confirmed	2014-05-22	2014-05-27	Kailahun	Kissi Teng
10	57	F	confirmed	2014-05-22	2014-05-27	Kailahun	Kissi Teng
11	50	F	confirmed	2014-05-22	2014-05-27	Kailahun	Kissi Teng
12	27	F	confirmed	2014-05-22	2014-05-27	Kailahun	Kissi Tonge
13	38	F	confirmed	2014-05-22	2014-05-27	Kailahun	Kissi Tonge
14	29	F	suspected	2014-05-23	2014-05-28	Western Urban	Freetowm
15	43	F	suspected	2014-05-24	2014-05-29	Kailahun	Penguia
16	NA	F	suspected	2014-05-24	2014-05-29	Western Urban	Freetowm
17	38	F	confirmed	2014-05-26	2014-05-31	Kailahun	Jawei
18	36	F	suspected	2014-05-26	2014-05-31	Bombali	Bombali Sebora
19	35	F	suspected	2014-05-26	2014-05-31	Kailahun	Kissi Tonge
20	3	F	suspected	2014-05-26	2014-05-31	Kailahun	Kissi Tonge

6.6 fluH7N9_china_2013

Influenza A H7N9 in China, 2013

case_id	date_of_onset	date_of_hospitalisation	date_of_outcome	outcome	gender	age	province
1	2013-02-19	NA	2013-03-04	Death	m	87	Shanghai
2	2013-02-27	2013-03-03	2013-03-10	Death	m	27	Shanghai
3	2013-03-09	2013-03-19	2013-04-09	Death	f	35	Anhui
4	2013-03-19	2013-03-27	NA	NA	f	45	Jiangsu
5	2013-03-19	2013-03-30	2013-05-15	Recover	f	48	Jiangsu
6	2013-03-21	2013-03-28	2013-04-26	Death	f	32	Jiangsu
7	2013-03-20	2013-03-29	2013-04-09	Death	m	83	Jiangsu
8	2013-03-07	2013-03-18	2013-03-27	Death	m	38	Zhejiang
9	2013-03-25	2013-03-25	NA	NA	m	67	Zhejiang
10	2013-03-28	2013-04-01	2013-04-03	Death	m	48	Shanghai
11	2013-03-29	2013-03-31	2013-04-04	Death	m	64	Zhejiang
12	2013-03-27	NA	2013-04-03	Death	f	52	Shanghai
13	2013-03-22	2013-03-25	2013-04-03	Death	f	67	Shanghai
14	2013-03-31	NA	2013-04-10	Recover	m	4	Shanghai
15	2013-03-20	NA	NA	NA	f	61	Jiangsu
16	2013-03-21	NA	NA	NA	m	79	Jiangsu
17	2013-03-28	2013-04-03	2013-04-11	Death	m	74	Shanghai
18	2013-03-29	2013-04-02	2013-04-18	Recover	m	66	Shanghai
19	2013-03-25	2013-03-30	2013-05-31	Death	m	59	Shanghai
20	2013-03-28	2013-04-01	2013-04-19	Recover	m	55	Anhui

6.7 influenza_england_1978_school

Influenza in a boarding school in England, 1978

date	in_bed	convalescent
1978-01-22	3	0
1978-01-23	8	0
1978-01-24	26	0
1978-01-25	76	0
1978-01-26	225	9
1978-01-27	298	17
1978-01-28	258	105
1978-01-29	233	162
1978-01-30	189	176
1978-01-31	128	166
1978-02-01	68	150
1978-02-02	29	85
1978-02-03	14	47
1978-02-04	4	20

6.8 measles_hagelloch_1861

Measles in Hagelloch, Germany, 1861

case_ID	infector	date_of_prodrome	date_of_rash	date_of_death	age	gender	family_ID	class	complications	x_loc	y_loc
1	45	1861-11-21	1861-11-25	NA	7	f	41	1	yes	142.5	100.0
2	45	1861-11-23	1861-11-27	NA	6	f	41	1	yes	142.5	100.0
3	172	1861-11-28	1861-12-02	NA	4	f	41	0	yes	142.5	100.0
4	180	1861-11-27	1861-11-28	NA	13	m	61	2	yes	165.0	102.5
5	45	1861-11-22	1861-11-27	NA	8	f	42	1	yes	145.0	120.0
6	180	1861-11-26	1861-11-29	NA	12	m	42	2	yes	145.0	120.0
7	42	1861-11-24	1861-11-28	NA	6	m	26	0	yes	272.5	147.5
8	45	1861-11-21	1861-11-26	NA	10	m	44	1	yes	97.5	155.0
9	182	1861-11-26	1861-11-30	NA	13	m	44	2	yes	97.5	155.0
10	45	1861-11-21	1861-11-25	NA	7	f	29	1	yes	240.0	75.0
11	182	1861-11-25	1861-11-30	NA	11	f	27	2	yes	270.0	135.0
12	45	1861-11-20	1861-11-25	NA	7	f	32	1	yes	195.0	27.5
13	12	1861-11-30	1861-12-05	NA	13	m	32	2	yes	195.0	27.5
14	181	1861-11-22	1861-11-29	NA	13	f	22	2	yes	227.5	185.0
15	45	1861-11-24	1861-11-29	NA	8	m	22	1	yes	227.5	185.0
16	181	1861-11-21	1861-11-25	NA	15	f	43	2	yes	172.5	172.5
17	181	1861-11-20	1861-11-25	NA	10	f	43	2	yes	172.5	172.5
18	175	1861-11-23	1861-11-27	NA	2	f	43	0	yes	172.5	172.5
19	181	1861-11-20	1861-11-24	NA	11	m	11	2	yes	167.5	5.0
20	181	1861-11-22	1861-11-27	NA	10	m	11	2	yes	167.5	5.0

6.9 nipah_malaysia

Nipah in Malaysia and Sinagapore, 1997-1999

date	perak	negeri_sembilan	selangor	singapore
1997-01-04	0	0	0	0
1997-01-11	1	0	0	0
1997-01-18	0	0	0	0
1997-01-25	1	0	0	0
1997-02-01	1	0	0	0
1997-02-08	0	0	0	0
1997-02-15	1	0	0	0
1997-02-22	1	0	0	0
1997-03-01	0	0	0	0
1997-03-08	0	0	0	0
1997-03-15	0	0	0	0
1997-03-22	0	0	0	0
1997-03-29	0	0	0	0
1997-04-05	0	0	0	0
1997-04-12	0	0	0	0
1997-04-19	0	0	0	0
1997-04-26	0	0	0	0
1997-05-03	0	0	0	0
1997-05-10	0	0	0	0
1997-05-17	0	0	0	0

6.10 norovirus_derbyshire_2001_school

Norovirus in a primary school in Derbyshire, England, 2001

class	day_absent	start_illness	end_illness	day_vomiting
1	23	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	22	22	0
1	0	24	28	0
1	15	0	0	0
1	0	0	0	0
1	15	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	0	0	0	0
1	15	0	0	0

6.11 sars_canada_2003

Severe Acute Respiratory Syndrome in Canada, 2003

date	cases_travel	cases_household	cases_healthcare	cases_other
2003-02-23	1	0	0	0
2003-02-24	0	0	0	0
2003-02-25	0	0	0	0
2003-02-26	0	1	0	0
2003-02-27	0	0	0	0
2003-02-28	1	0	0	0
2003-03-01	0	0	0	0
2003-03-02	0	0	0	0
2003-03-03	0	1	0	0
2003-03-04	0	0	0	0
2003-03-05	0	1	0	0
2003-03-06	0	0	0	0
2003-03-07	0	1	0	0
2003-03-08	0	0	0	0
2003-03-09	0	0	1	0
2003-03-10	0	0	1	0
2003-03-11	0	0	0	0
2003-03-12	0	0	2	0
2003-03-13	1	0	2	0
2003-03-14	0	0	0	0

6.12 sarscov2_who_2019

SARS-CoV-2 World Health Organization Situation Reports 2019 Outbreak (COVID-19)

situation_report	date	cases_chn	cases_kor	cases_aus	cases_jpn	cases_mys	cases_phl	cases_sgp	cases_nzl	cases_vnm	cases_brn	cases_khm	cases_mng	cases_fji	cases_lao	cases_png	cases_gum	cases_pyf	cases_ncl	cases_mnp	cases_region_westernpacific	cases_idn	cases_tha	cases_ind	cases_lka	cases_mdv	cases_bgd	cases_btn	cases_npl	cases_mmr	cases_tls	cases_region_southeastasia	cases_usa	cases_can	cases_bra	cases_chl	cases_ecu	cases_mex	cases_dom	cases_pan	cases_per	cases_arg	cases_col	cases_cri	cases_ury	cases_cub	cases_hnd	cases_ven	cases_bol	cases_tto	cases_pry	cases_gtm	cases_jam	cases_slv	cases_brb	cases_bhm	cases_guy	cases_hti	cases_lca	cases_dma	cases_grd	cases_sur	cases_kna	cases_atg	cases_nic	cases_blz	cases_vct	cases_pri	cases_mtq	cases_glp	cases_abw	cases_guf	cases_vir	cases_bmu	cases_cym	cases_sxm	cases_maf	cases_cuw	cases_blm	cases_msr	cases_tca	cases_aia	cases_vgb	cases_bes	cases_flk	cases_spm	cases_region_americas	cases_esp	cases_ita	cases_deu	cases_fra	cases_gbr	cases_tur	cases_bel	cases_che	cases_nld	cases_prt	cases_aut	cases_rus	cases_isr	cases_swe	cases_irl	cases_nor	cases_dnk	cases_pol	cases_cze	cases_rou	cases_lux	cases_srb	cases_fin	cases_ukr	cases_grc	cases_isl	cases_hrv	cases_mda	cases_est	cases_hun	cases_svn	cases_blr	cases_ltu	cases_arm	cases_aze	cases_bih	cases_kaz	cases_svk	cases_mkd	cases_bgr	cases_uzb	cases_and	cases_lva	cases_cyp	cases_alb	cases_smr	cases_mlt	cases_kgz	cases_mne	cases_geo	cases_lie	cases_mco	cases_vat	cases_kosovo	cases_fro	cases_ggy	cases_jey	cases_imn	cases_gib	cases_grl	cases_region_european	cases_irn	cases_pak	cases_sau	cases_qat	cases_egy	cases_irq	cases_are	cases_mar	cases_bhr	cases_lbn	cases_tun	cases_jor	cases_kwt	cases_omn	cases_afg	cases_dji	cases_syr	cases_lby	cases_sdn	cases_som	cases_yem	cases_pse	cases_region_easternmediterranean	cases_zaf	cases_dza	cases_bfa	cases_civ	cases_sen	cases_gha	cases_cmr	cases_nga	cases_mus	cases_cod	cases_rwa	cases_mdg	cases_ken	cases_zmb	cases_tgo	cases_uga	cases_eth	cases_ner	cases_cog	cases_tza	cases_mli	cases_gin	cases_gnq	cases_nam	cases_swz	cases_moz	cases_syc	cases_gab	cases_ben	cases_caf	cases_eri	cases_cpv	cases_tcd	cases_mrt	cases_zwe	cases_gmb	cases_lbr	cases_ago	cases_gnb	cases_bwa	cases_mwi	cases_stp	cases_bdi	cases_sle	cases_ssd	cases_reu	cases_myt	cases_region_african	cases_internationalconveyance	cases_global	deaths_global	deaths_chn	deaths_kor	deaths_aus	deaths_mys	deaths_jpn	deaths_sgp	deaths_phl	deaths_nzl	deaths_gum	deaths_brn	deaths_mnp	deaths_region_westernpacific	deaths_ita	deaths_esp	deaths_deu	deaths_fra	deaths_gbr	deaths_tur	deaths_che	deaths_bel	deaths_nld	deaths_aut	deaths_prt	deaths_isr	deaths_swe	deaths_nor	deaths_irl	deaths_cze	deaths_rus	deaths_dnk	deaths_pol	deaths_rou	deaths_lux	deaths_fin	deaths_grc	deaths_srb	deaths_isl	deaths_ukr	deaths_hrv	deaths_est	deaths_svn	deaths_ltu	deaths_arm	deaths_hun	deaths_mda	deaths_bih	deaths_lva	deaths_bgr	deaths_kaz	deaths_aze	deaths_and	deaths_mkd	deaths_cyp	deaths_alb	deaths_blr	deaths_smr	deaths_svk	deaths_uzb	deaths_mne	deaths_geo	deaths_mlt	deaths_kgz	deaths_mco	deaths_lie	deaths_kosovo	deaths_jey	deaths_ggy	deaths_imn	deaths_gib	deaths_region_european	deaths_tha	deaths_idn	deaths_ind	deaths_bgd	deaths_lka	deaths_mmr	deaths_region_southeastasia	deaths_irn	deaths_pak	deaths_sau	deaths_are	deaths_qat	deaths_egy	deaths_mar	deaths_irq	deaths_kwt	deaths_bhr	deaths_tun	deaths_lbn	deaths_afg	deaths_omn	deaths_jor	deaths_dji	deaths_lby	deaths_syr	deaths_sdn	deaths_som	deaths_pse	deaths_region_easternmediterranean	deaths_usa	deaths_can	deaths_bra	deaths_chl	deaths_ecu	deaths_per	deaths_dom	deaths_mex	deaths_pan	deaths_arg	deaths_col	deaths_cri	deaths_ury	deaths_cub	deaths_hnd	Venezuela.deaths	deaths_bol	deaths_tto	deaths_pry	deaths_gtm	deaths_jam	deaths_slv	deaths_bhm	deaths_guy	deaths_atg	deaths_sur	deaths_brb	deaths_hti	deaths_blz	deaths_nic	deaths_pri	deaths_mtq	deaths_glp	deaths_vir	Aruba.deaths	deaths_guf	deaths_bmu	deaths_cym	deaths_cuw	deaths_maf	deaths_sxm	deaths_tca	deaths_vgb	deaths_region_americas	deaths_zaf	deaths_dza	deaths_bfa	deaths_gha	deaths_sen	deaths_mus	deaths_cmr	deaths_gin	deaths_nga	deaths_cod	deaths_ken	deaths_ner	deaths_tgo	deaths_cog	deaths_eth	deaths_mli	deaths_zmb	deaths_civ	deaths_tza	deaths_ago	deaths_lbr	deaths_zwe	deaths_ben	deaths_gab	deaths_swz	deaths_mwi	deaths_cpv	deaths_bwa	deaths_mrt	deaths_gmb	deaths_bdi	deaths_myt	deaths_region_african	deaths_internationalconveyance	Region.Other.deaths	critical_chn	clinical_chn_hubei	cases_outside_chn	countries_outside_chn	deaths_outside_chn	risk_chn	risk_regional	risk_global	cases_health_care_workers	cases_chn_wuhan	cases_chn_hubei	cases_chn_guangdong	cases_chn_beijing	cases_chn_shanghai	cases_chn_chongqing	cases_chn_zhejiang	cases_chn_jiangxi	cases_chn_sichuan	cases_chn_tianjin	cases_chn_henan	cases_chn_hunan	cases_chn_shandong	cases_chn_yunnan	cases_chn_taiwan	cases_chn_taipei	cases_chn_hkg	cases_chn_mac	cases_chn_unspecified	cases_chn_anhui	cases_chn_jiangsu	cases_chn_fujian	cases_chn_shaanxi	cases_chn_guangxi	cases_chn_hebei	cases_chn_heilongjiang	cases_chn_liaoning	cases_chn_hainan	cases_chn_shanxi	cases_chn_gansu	cases_chn_guizhou	cases_chn_ningxia	cases_chn_mng	cases_chn_xinjiang	cases_chn_jilin	cases_chn_qinghai	cases_chn_xizang	deaths_chn_hubei	deaths_chn_guangdong	deaths_chn_beijing	deaths_chn_shanghai	deaths_chn_chongqing	deaths_chn_zhejiang	deaths_chn_jiangxi	deaths_chn_sichuan	deaths_chn_tianjin	deaths_chn_henan	deaths_chn_hunan	deaths_chn_shandong	deaths_chn_yunnan	deaths_chn_taipei	deaths_chn_hkg	deaths_chn_mac	deaths_chn_anhui	deaths_chn_jiangsu	deaths_chn_fujian	deaths_chn_shaanxi	deaths_chn_guangxi	deaths_chn_hebei	deaths_chn_heilongjiang	deaths_chn_liaoning	deaths_chn_hainan	deaths_chn_shanxi	deaths_chn_gansu	deaths_chn_guizhou	deaths_chn_ningxia	deaths_chn_mng	deaths_chn_xinjiang	deaths_chn_jilin	deaths_chn_qinghai	deaths_chn_xizang	suspected_chn	severe_chn	cases_outside_chn_wuhan_travel_history	cases_outside_chn_chn_travel_history
1	2020-01-20	278	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	2	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	282	NA	6	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	12	NA	NA	NA	NA				NA	60	258	14	5	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	51	4	NA
2	2020-01-21	309	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	2	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	314	NA	6	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	12	NA	4	NA	NA				16	82	270	17	5	2	1	5	2	1	2	1	1	1	1	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	51	4	NA
3	2020-01-23	571	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	4	0	0	0	0	0	0	0	0	NA	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	581	NA	17	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	NA	NA	NA	Very High	High	High	NA	NA	375	26	10	9	5	5	2	2	2	1	1	1	1	NA	1	1	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	95	NA	NA
4	2020-01-24	830	2	0	1	0	0	1	0	2	0	0	0	0	0	0	0	0	0	0	NA	0	4	0	0	0	0	0	0	0	0	NA	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	846	NA	25	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	11	6	NA	Very High	High	High	NA	NA	375	32	10	9	5	5	2	2	2	1	1	1	1	NA	1	2	2	384	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	177	10	NA
5	2020-01-25	1297	2	3	3	0	0	3	0	2	0	0	0	0	0	0	0	0	0	0	NA	0	4	0	0	0	0	0	1	0	0	NA	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	1320	NA	41	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	23	9	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	5	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	39	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	1965	237	21	NA
6	2020-01-26	1985	2	4	3	3	0	4	0	2	0	0	0	0	0	0	0	0	0	0	NA	0	5	0	0	0	0	0	1	0	0	NA	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	2014	NA	56	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	29	10	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	5	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	52	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	324	26	NA
7	2020-01-27	2761	4	4	4	4	0	4	0	2	0	0	0	0	0	0	0	0	0	0	NA	0	5	0	0	0	0	0	1	0	0	NA	5	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	2798	NA	80	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	37	11	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	8	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	5794	461	NA	NA
8	2020-01-28	4537	4	5	6	4	0	7	0	2	0	1	0	0	0	0	0	0	0	0	NA	0	14	0	1	0	0	0	1	0	0	NA	5	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	1	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	4593	NA	106	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	56	14	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	7	8	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	6973	976	NA	NA
9	2020-01-29	5997	4	7	7	4	0	7	0	2	0	1	0	0	0	0	0	0	0	0	NA	0	14	0	1	0	0	0	1	0	0	NA	5	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	4	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	6065	NA	132	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	68	15	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	8	8	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	9239	1239	NA	NA
10	2020-01-30	7736	4	7	11	7	1	10	0	2	0	1	0	0	0	0	0	0	0	0	NA	0	14	1	1	0	0	0	1	0	0	NA	5	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	4	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	7818	NA	170	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	82	18	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	8	10	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	12167	1370	NA	NA
11	2020-01-31	9720	11	9	14	8	1	13	0	5	0	1	0	0	0	0	0	0	0	0	NA	0	14	1	1	0	0	0	1	0	0	NA	6	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	2	5	6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	9826	NA	213	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	106	19	NA	Very High	High	High	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	9	12	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	15238	1527	NA	NA
12	2020-02-01	11821	12	12	17	8	1	16	0	6	0	1	0	0	0	0	0	0	0	0	NA	0	19	1	1	0	0	0	1	0	0	NA	7	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	2	7	6	2	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	11953	NA	259	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	132	23	NA	Very High	High	High	NA	NA	7153	520	156	153	238	599	286	207	34	422	389	202	91	NA	10	13	7	NA	297	202	144	101	100	96	80	60	57	47	35	29	26	23	18	17	8	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1795	NA	NA
13	2020-02-02	14411	15	12	20	8	2	18	0	7	0	1	0	0	0	0	0	0	0	0	NA	0	19	2	1	0	0	0	1	0	0	NA	8	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	2	8	6	2	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	14557	NA	304	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	146	23	1	Very High	High	High	NA	NA	9074	604	183	177	262	661	333	236	40	493	463	225	99	NA	10	14	7	NA	340	231	159	116	111	104	95	64	63	56	45	40	28	26	23	21	9	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2110	NA	NA
14	2020-02-03	17238	15	12	20	8	2	18	0	8	0	1	0	0	0	0	0	0	0	0	NA	0	19	3	1	0	0	0	1	0	0	NA	11	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	2	10	6	2	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	17391	NA	361	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	153	23	1	Very High	High	High	NA	NA	11177	683	212	193	300	724	391	254	49	566	521	246	109	NA	10	15	8	NA	408	271	179	128	127	113	118	70	70	66	51	46	31	33	24	31	13	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2296	NA	NA
15	2020-02-04	20471	16	12	20	10	2	18	0	9	0	1	0	0	0	0	0	0	0	0	NA	0	19	3	1	0	0	0	1	0	0	NA	11	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	2	12	6	2	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	20630	NA	425	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	159	23	1	Very High	High	High	NA	NA	13522	797	228	208	337	829	476	282	63	675	593	270	117	NA	10	15	8	NA	480	308	194	142	139	126	155	74	79	74	56	56	34	37	29	42	15	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2788	NA	NA
16	2020-02-05	24363	18	13	33	10	3	24	0	10	0	1	0	0	0	0	0	0	0	0	NA	0	25	3	1	0	0	0	1	0	0	NA	11	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	2	12	6	2	0	1	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	24554	NA	491	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	191	24	1	Very High	High	High	NA	NA	16678	870	253	233	366	895	548	301	67	764	661	298	122	NA	11	18	10	NA	530	341	205	165	150	135	190	81	89	81	57	64	34	42	32	54	17	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3219	NA	NA
17	2020-02-06	28060	23	14	25	12	3	28	0	10	0	1	0	0	0	0	0	0	0	0	NA	0	25	3	1	0	0	0	1	0	0	NA	12	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	2	12	6	2	0	1	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	20	28276	NA	564	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	216	24	1	Very High	High	High	NA	NA	19665	944	274	254	389	954	600	321	70	851	711	343	128	NA	11	21	10	NA	591	373	215	173	168	157	227	89	100	90	62	69	40	46	36	59	18	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3859	NA	NA
18	2020-02-07	31211	24	15	25	14	3	30	0	12	0	1	0	0	0	0	0	0	0	0	NA	0	25	3	1	0	0	0	1	0	0	NA	12	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	3	13	6	3	0	1	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	61	31481	NA	637	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	270	24	1	Very High	High	High	NA	NA	22112	1018	297	269	411	1006	661	344	79	914	772	379	135	NA	16	24	10	NA	665	408	224	184	172	171	277	94	111	96	70	77	43	49	39	65	18	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4821	NA	NA
19	2020-02-08	34598	24	15	25	15	3	33	0	13	0	1	0	0	0	0	0	0	0	0	NA	0	32	3	1	0	0	0	1	0	0	NA	12	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	3	14	6	3	0	1	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	64	34886	NA	723	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	288	24	1	Very High	High	High	NA	NA	24953	1075	315	281	426	1048	698	363	81	981	803	407	138	NA	16	26	10	NA	733	439	239	195	183	195	282	99	123	104	71	89	45	50	42	69	18	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	6101	NA	NA
20	2020-02-09	37251	27	15	26	17	3	40	0	14	0	1	0	0	0	0	0	0	0	0	NA	0	32	3	1	0	0	0	1	0	0	NA	12	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	1	3	14	11	3	0	1	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	64	37558	NA	812	0	0	0	0	0	1	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	NA	0	NA	NA	NA	307	24	1	Very High	High	High	NA	NA	27100	1120	326	292	446	1075	740	386	88	1033	838	435	140	NA	17	26	10	NA	779	468	250	208	195	206	307	105	128	115	81	96	45	54	45	78	18	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	6188	NA	NA

6.13 smallpox_abakaliki_1967

Smallpox in Abakaliki, Nigeria, 1967

case_ID	date_of_onset	age	gender	vaccinated	vaccscar	ftc	compound
1	1967-04-05	10	f	n	n	y	1
2	1967-04-18	25	f	n	n	y	1
3	1967-04-25	35	m	n	n	y	1
4	1967-04-27	4	f	n	n	y	1
5	1967-04-30	11	m	n	n	y	1
6	1967-04-30	1	m	n	n	y	1
7	1967-04-30	4	f	n	n	y	1
8	1967-05-01	8	f	y	n	y	2
9	1967-05-05	12	m	y	y	y	2
10	1967-05-10	2	m	n	n	y	1
11	1967-05-13	35	m	n	n	y	4
12	1967-05-15	28	f	n	n	y	5
13	1967-05-15	3	m	n	n	y	1
14	1967-05-17	1	f	n	n	y	1
15	1967-05-17	2	m	n	n	y	1
16	1967-05-22	3	f	n	n	y	1
17	1967-05-25	1	f	n	n	y	5
18	1967-05-26	30	f	n	n	y	2
19	1967-05-30	4	f	n	n	y	1
20	1967-05-30	13	m	y	n	y	2

6.14 varicella_sim_berlin

Simulated Varicella outbreak

sex	ethnicity	firstname	lastname	age	center1	arrival1	leave1	center2	arrival2	leave2	onset	disease
female	arabic	Saleema	al-Ismael	16	Oranienburger Str	2015-05-06	2015-06-20	Bizetstr	2015-06-27	2015-08-19	NA	NA
male	hispanic	Domonic	Jaramillo	25	Platz der Luftbruecke	2015-01-19	2015-01-21	Bizetstr	2015-01-30	2015-03-02	NA	NA
female	arabic	Haaniya	el-Mitri	34	Platz der Luftbruecke	2015-04-11	2015-07-09	Platz der Luftbruecke	2015-07-18	2015-10-03	2015-07-06	varicella
female	asian	Erica	Tanghal	11	Platz der Luftbruecke	2015-01-20	2015-03-30	Oranienburger Str	2015-04-08	2015-07-13	2015-08-20	varicella
male	asian	Fermin Joshua	Kikuchi	34	Platz der Luftbruecke	2015-06-15	2015-08-17	Platz der Luftbruecke	2015-08-22	2015-11-01	NA	NA
male	arabic	Muslim	al-Moussa	5	Bizetstr	2014-11-18	2015-02-03	Platz der Luftbruecke	2015-02-17	2015-04-27	NA	NA
male	arabic	Abdul Baari	al-Ozer	35	Oranienburger Str	2015-07-19	2015-10-28	Oranienburger Str	2015-11-06	2015-11-09	NA	NA
female	arabic	Wadha	el-Dia	11	Platz der Luftbruecke	2015-02-15	2015-04-10	Platz der Luftbruecke	2015-04-16	2015-06-08	2015-06-24	varicella
male	asian	Binh	Kaneko	13	Bizetstr	2015-05-06	2015-06-23	Bizetstr	2015-06-29	2015-08-28	2015-03-16	varicella
female	native-american	Ruby	Cook	15	Platz der Luftbruecke	2014-12-15	2015-01-07	Bizetstr	2015-01-13	2015-01-16	NA	NA
female	asian	Kelyn	Maranto	1	Platz der Luftbruecke	2015-05-19	2015-06-29	Platz der Luftbruecke	2015-07-11	2015-09-10	NA	NA
male	caucasian	Aaron	Arendall	3	Platz der Luftbruecke	2014-12-30	2015-02-17	Platz der Luftbruecke	2015-03-02	2015-03-14	NA	NA
male	hispanic	Trey	Munoz	7	Oranienburger Str	2015-05-16	2015-07-04	Bizetstr	2015-07-18	2015-08-11	NA	NA
female	african	Tia	Busterna	26	Platz der Luftbruecke	2014-12-20	2015-03-07	Bizetstr	2015-03-17	2015-03-30	NA	NA
male	caucasian	Jessie	Montgomery	24	Platz der Luftbruecke	2015-05-01	2015-07-23	Bizetstr	2015-08-05	2015-09-17	2015-08-15	varicella
female	african	Amira	Jackson	17	Platz der Luftbruecke	2015-01-03	2015-02-14	Platz der Luftbruecke	2015-02-19	2015-04-14	NA	NA
male	asian	John	Van Zee	8	Bizetstr	2015-08-19	2015-10-06	Buchholzerstr	2015-10-21	2015-12-28	NA	NA
female	hispanic	Lorrana	Orozco	23	Bizetstr	2014-12-28	2015-02-13	Platz der Luftbruecke	2015-02-18	2015-05-03	NA	NA
female	arabic	Tasneem	al-Naqvi	15	Platz der Luftbruecke	2015-04-18	2015-05-11	Buchholzerstr	2015-05-18	2015-07-14	2015-06-25	varicella
male	asian	Max	Schultz	22	Oranienburger Str	2014-12-09	2015-01-31	Platz der Luftbruecke	2015-02-12	2015-04-19	NA	NA

6.15 zika_girardot_2015

Zika in Girardot, Colombia, 2015

date	cases
2015-10-19	1
2015-10-22	2
2015-10-23	1
2015-10-24	4
2015-10-25	2
2015-10-26	5
2015-10-27	2
2015-10-28	4
2015-10-29	5
2015-10-30	4
2015-10-31	6
2015-11-01	8
2015-11-02	11
2015-11-03	11
2015-11-04	22
2015-11-05	31
2015-11-06	32
2015-11-07	40
2015-11-08	42
2015-11-09	54

6.16 zika_sanandres_2015

Zika in San Andres, Colombia, 2015

date	cases
2015-09-06	1
2015-09-07	1
2015-09-08	1
2015-09-13	1
2015-09-15	4
2015-09-19	1
2015-09-20	1
2015-09-23	1
2015-09-24	1
2015-09-26	1
2015-09-28	2
2015-09-29	1
2015-09-30	2
2015-10-01	6
2015-10-02	5
2015-10-03	3
2015-10-04	3
2015-10-05	6
2015-10-06	9
2015-10-07	7

6.17 zika_yap_2007

Zika on the Yap Main Islands, Micronesia, 2007

onset_date	nr	value
2007-02-18	7	0
2007-02-25	14	0
2007-03-04	21	0
2007-03-11	28	0
2007-03-18	35	0
2007-03-25	42	0
2007-04-01	49	0
2007-04-08	56	0
2007-04-15	63	1
2007-04-22	70	2
2007-04-29	77	0
2007-05-06	84	1
2007-05-13	91	1
2007-05-20	98	9
2007-05-27	105	29
2007-06-03	112	15
2007-06-10	119	9
2007-06-17	126	15
2007-06-24	133	19
2007-07-01	140	6

7 datasets

7.1 BOD

Biochemical Oxygen Demand

Time	demand
1	8.3
2	10.3
3	19.0
4	16.0
5	15.6
7	19.8

7.2 CO2

Carbon Dioxide Uptake in Grass Plants

Plant	Type	Treatment	conc	uptake
Qn1	Quebec	nonchilled	95	16.0
Qn1	Quebec	nonchilled	175	30.4
Qn1	Quebec	nonchilled	250	34.8
Qn1	Quebec	nonchilled	350	37.2
Qn1	Quebec	nonchilled	500	35.3
Qn1	Quebec	nonchilled	675	39.2
Qn1	Quebec	nonchilled	1000	39.7
Qn2	Quebec	nonchilled	95	13.6
Qn2	Quebec	nonchilled	175	27.3
Qn2	Quebec	nonchilled	250	37.1
Qn2	Quebec	nonchilled	350	41.8
Qn2	Quebec	nonchilled	500	40.6
Qn2	Quebec	nonchilled	675	41.4
Qn2	Quebec	nonchilled	1000	44.3
Qn3	Quebec	nonchilled	95	16.2
Qn3	Quebec	nonchilled	175	32.4
Qn3	Quebec	nonchilled	250	40.3
Qn3	Quebec	nonchilled	350	42.1
Qn3	Quebec	nonchilled	500	42.9
Qn3	Quebec	nonchilled	675	43.9

7.3 ChickWeight

Weight versus age of chicks on different diets

weight	Time	Chick	Diet
42	0	1	1
51	2	1	1
59	4	1	1
64	6	1	1
76	8	1	1
93	10	1	1
106	12	1	1
125	14	1	1
149	16	1	1
171	18	1	1
199	20	1	1
205	21	1	1
40	0	2	1
49	2	2	1
58	4	2	1
72	6	2	1
84	8	2	1
103	10	2	1
122	12	2	1
138	14	2	1

7.4 DNase

Elisa assay of DNase

Run	conc	density
1	0.04882812	0.017
1	0.04882812	0.018
1	0.19531250	0.121
1	0.19531250	0.124
1	0.39062500	0.206
1	0.39062500	0.215
1	0.78125000	0.377
1	0.78125000	0.374
1	1.56250000	0.614
1	1.56250000	0.609
1	3.12500000	1.019
1	3.12500000	1.001
1	6.25000000	1.334
1	6.25000000	1.364
1	12.50000000	1.730
1	12.50000000	1.710
2	0.04882812	0.045
2	0.04882812	0.050
2	0.19531250	0.137
2	0.19531250	0.123

7.5 Formaldehyde

Determination of Formaldehyde

carb	optden
0.1	0.086
0.3	0.269
0.5	0.446
0.6	0.538
0.7	0.626
0.9	0.782

7.6 Indometh

Pharmacokinetics of Indomethacin

Subject	time	conc
1	0.25	1.50
1	0.50	0.94
1	0.75	0.78
1	1.00	0.48
1	1.25	0.37
1	2.00	0.19
1	3.00	0.12
1	4.00	0.11
1	5.00	0.08
1	6.00	0.07
1	8.00	0.05
2	0.25	2.03
2	0.50	1.63
2	0.75	0.71
2	1.00	0.70
2	1.25	0.64
2	2.00	0.36
2	3.00	0.32
2	4.00	0.20
2	5.00	0.25

7.7 InsectSprays

Effectiveness of Insect Sprays

count	spray
10	A
7	A
20	A
14	A
14	A
12	A
10	A
23	A
17	A
20	A
14	A
13	A
11	B
17	B
21	B
11	B
16	B
14	B
17	B
17	B

7.8 LifeCycleSavings

Intercountry Life-Cycle Savings Data

sr	pop15	pop75	dpi	ddpi
11.43	29.35	2.87	2329.68	2.87
12.07	23.32	4.41	1507.99	3.93
13.17	23.80	4.43	2108.47	3.82
5.75	41.89	1.67	189.13	0.22
12.88	42.19	0.83	728.47	4.56
8.79	31.72	2.85	2982.88	2.43
0.60	39.74	1.34	662.86	2.67
11.90	44.75	0.67	289.52	6.51
4.98	46.64	1.06	276.65	3.08
10.78	47.64	1.14	471.24	2.80
16.85	24.42	3.93	2496.53	3.99
3.59	46.31	1.19	287.77	2.19
11.24	27.84	2.37	1681.25	4.32
12.64	25.06	4.70	2213.82	4.52
12.55	23.31	3.35	2457.12	3.44
10.67	25.62	3.10	870.85	6.28
3.01	46.05	0.87	289.71	1.48
7.70	47.32	0.58	232.44	3.19
1.27	34.03	3.08	1900.10	1.12
9.00	41.31	0.96	88.94	1.54

7.9 Loblolly

Growth of Loblolly pine trees

height	age	Seed
4.51	3	301
10.89	5	301
28.72	10	301
41.74	15	301
52.70	20	301
60.92	25	301
4.55	3	303
10.92	5	303
29.07	10	303
42.83	15	303
53.88	20	303
63.39	25	303
4.79	3	305
11.37	5	305
30.21	10	305
44.40	15	305
55.82	20	305
64.10	25	305
3.91	3	307
9.48	5	307

7.10 Orange

Growth of Orange Trees

Tree	age	circumference
1	118	30
1	484	58
1	664	87
1	1004	115
1	1231	120
1	1372	142
1	1582	145
2	118	33
2	484	69
2	664	111
2	1004	156
2	1231	172
2	1372	203
2	1582	203
3	118	30
3	484	51
3	664	75
3	1004	108
3	1231	115
3	1372	139

7.11 OrchardSprays

Potency of Orchard Sprays

decrease	rowpos	colpos	treatment
57	1	1	D
95	2	1	E
8	3	1	B
69	4	1	H
92	5	1	G
90	6	1	F
15	7	1	C
2	8	1	A
84	1	2	C
6	2	2	B
127	3	2	H
36	4	2	D
51	5	2	E
2	6	2	A
69	7	2	F
71	8	2	G
87	1	3	F
72	2	3	H
5	3	3	A
39	4	3	E

7.12 PlantGrowth

Results from an Experiment on Plant Growth

weight	group
4.17	ctrl
5.58	ctrl
5.18	ctrl
6.11	ctrl
4.50	ctrl
4.61	ctrl
5.17	ctrl
4.53	ctrl
5.33	ctrl
5.14	ctrl
4.81	trt1
4.17	trt1
4.41	trt1
3.59	trt1
5.87	trt1
3.83	trt1
6.03	trt1
4.89	trt1
4.32	trt1
4.69	trt1

7.13 Puromycin

Reaction Velocity of an Enzymatic Reaction

conc	rate	state
0.02	76	treated
0.02	47	treated
0.06	97	treated
0.06	107	treated
0.11	123	treated
0.11	139	treated
0.22	159	treated
0.22	152	treated
0.56	191	treated
0.56	201	treated
1.10	207	treated
1.10	200	treated
0.02	67	untreated
0.02	51	untreated
0.06	84	untreated
0.06	86	untreated
0.11	98	untreated
0.11	115	untreated
0.22	131	untreated
0.22	124	untreated

7.14 Theoph

Pharmacokinetics of Theophylline

Subject	Wt	Dose	Time	conc
1	79.6	4.02	0.00	0.74
1	79.6	4.02	0.25	2.84
1	79.6	4.02	0.57	6.57
1	79.6	4.02	1.12	10.50
1	79.6	4.02	2.02	9.66
1	79.6	4.02	3.82	8.58
1	79.6	4.02	5.10	8.36
1	79.6	4.02	7.03	7.47
1	79.6	4.02	9.05	6.89
1	79.6	4.02	12.12	5.94
1	79.6	4.02	24.37	3.28
2	72.4	4.40	0.00	0.00
2	72.4	4.40	0.27	1.72
2	72.4	4.40	0.52	7.91
2	72.4	4.40	1.00	8.31
2	72.4	4.40	1.92	8.33
2	72.4	4.40	3.50	6.85
2	72.4	4.40	5.02	6.08
2	72.4	4.40	7.03	5.40
2	72.4	4.40	9.00	4.55

7.15 ToothGrowth

The Effect of Vitamin C on Tooth Growth in Guinea Pigs

len	supp	dose
4.2	VC	0.5
11.5	VC	0.5
7.3	VC	0.5
5.8	VC	0.5
6.4	VC	0.5
10.0	VC	0.5
11.2	VC	0.5
11.2	VC	0.5
5.2	VC	0.5
7.0	VC	0.5
16.5	VC	1.0
16.5	VC	1.0
15.2	VC	1.0
17.3	VC	1.0
22.5	VC	1.0
17.3	VC	1.0
13.6	VC	1.0
14.5	VC	1.0
18.8	VC	1.0
15.5	VC	1.0

7.16 USArrests

Violent Crime Rates by US State

Murder	Assault	UrbanPop	Rape
13.2	236	58	21.2
10.0	263	48	44.5
8.1	294	80	31.0
8.8	190	50	19.5
9.0	276	91	40.6
7.9	204	78	38.7
3.3	110	77	11.1
5.9	238	72	15.8
15.4	335	80	31.9
17.4	211	60	25.8
5.3	46	83	20.2
2.6	120	54	14.2
10.4	249	83	24.0
7.2	113	65	21.0
2.2	56	57	11.3
6.0	115	66	18.0
9.7	109	52	16.3
15.4	249	66	22.2
2.1	83	51	7.8
11.3	300	67	27.8

7.17 USJudgeRatings

Lawyers’ Ratings of State Judges in the US Superior Court

CONT	INTG	DMNR	DILG	CFMG	DECI	PREP	FAMI	ORAL	WRIT	PHYS	RTEN
5.7	7.9	7.7	7.3	7.1	7.4	7.1	7.1	7.1	7.0	8.3	7.8
6.8	8.9	8.8	8.5	7.8	8.1	8.0	8.0	7.8	7.9	8.5	8.7
7.2	8.1	7.8	7.8	7.5	7.6	7.5	7.5	7.3	7.4	7.9	7.8
6.8	8.8	8.5	8.8	8.3	8.5	8.7	8.7	8.4	8.5	8.8	8.7
7.3	6.4	4.3	6.5	6.0	6.2	5.7	5.7	5.1	5.3	5.5	4.8
6.2	8.8	8.7	8.5	7.9	8.0	8.1	8.0	8.0	8.0	8.6	8.6
10.6	9.0	8.9	8.7	8.5	8.5	8.5	8.5	8.6	8.4	9.1	9.0
7.0	5.9	4.9	5.1	5.4	5.9	4.8	5.1	4.7	4.9	6.8	5.0
7.3	8.9	8.9	8.7	8.6	8.5	8.4	8.4	8.4	8.5	8.8	8.8
8.2	7.9	6.7	8.1	7.9	8.0	7.9	8.1	7.7	7.8	8.5	7.9
7.0	8.0	7.6	7.4	7.3	7.5	7.1	7.2	7.1	7.2	8.4	7.7
6.5	8.0	7.6	7.2	7.0	7.1	6.9	7.0	7.0	7.1	6.9	7.2
6.7	8.6	8.2	6.8	6.9	6.6	7.1	7.3	7.2	7.2	8.1	7.7
7.0	7.5	6.4	6.8	6.5	7.0	6.6	6.8	6.3	6.6	6.2	6.5
6.5	8.1	8.0	8.0	7.9	8.0	7.9	7.8	7.8	7.8	8.4	8.0
7.3	8.0	7.4	7.7	7.3	7.3	7.3	7.2	7.1	7.2	8.0	7.6
8.0	7.6	6.6	7.2	6.5	6.5	6.8	6.7	6.4	6.5	6.9	6.7
7.7	7.7	6.7	7.5	7.4	7.5	7.1	7.3	7.1	7.3	8.1	7.4
8.3	8.2	7.4	7.8	7.7	7.7	7.7	7.8	7.5	7.6	8.0	8.0
9.6	6.9	5.7	6.6	6.9	6.6	6.2	6.0	5.8	5.8	7.2	6.0

7.18 airquality

New York Air Quality Measurements

Ozone	Solar.R	Wind	Temp	Month	Day
41	190	7.4	67	5	1
36	118	8.0	72	5	2
12	149	12.6	74	5	3
18	313	11.5	62	5	4
NA	NA	14.3	56	5	5
28	NA	14.9	66	5	6
23	299	8.6	65	5	7
19	99	13.8	59	5	8
8	19	20.1	61	5	9
NA	194	8.6	69	5	10
7	NA	6.9	74	5	11
16	256	9.7	69	5	12
11	290	9.2	66	5	13
14	274	10.9	68	5	14
18	65	13.2	58	5	15
14	334	11.5	64	5	16
34	307	12.0	66	5	17
6	78	18.4	57	5	18
30	322	11.5	68	5	19
11	44	9.7	62	5	20

7.19 anscombe

Anscombe’s Quartet of ‘Identical’ Simple Linear Regressions

x1	x2	x3	x4	y1	y2	y3	y4
10	10	10	8	8.04	9.14	7.46	6.58
8	8	8	8	6.95	8.14	6.77	5.76
13	13	13	8	7.58	8.74	12.74	7.71
9	9	9	8	8.81	8.77	7.11	8.84
11	11	11	8	8.33	9.26	7.81	8.47
14	14	14	8	9.96	8.10	8.84	7.04
6	6	6	8	7.24	6.13	6.08	5.25
4	4	4	19	4.26	3.10	5.39	12.50
12	12	12	8	10.84	9.13	8.15	5.56
7	7	7	8	4.82	7.26	6.42	7.91
5	5	5	8	5.68	4.74	5.73	6.89

7.20 attenu

The Joyner-Boore Attenuation Data

event	mag	station	dist	accel
1	7.0	117	12.0	0.359
2	7.4	1083	148.0	0.014
2	7.4	1095	42.0	0.196
2	7.4	283	85.0	0.135
2	7.4	135	107.0	0.062
2	7.4	475	109.0	0.054
2	7.4	113	156.0	0.014
2	7.4	1008	224.0	0.018
2	7.4	1028	293.0	0.010
2	7.4	2001	359.0	0.004
2	7.4	117	370.0	0.004
3	5.3	1117	8.0	0.127
4	6.1	1438	16.1	0.411
4	6.1	1083	63.6	0.018
4	6.1	1013	6.6	0.509
4	6.1	1014	9.3	0.467
4	6.1	1015	13.0	0.279
4	6.1	1016	17.3	0.072
4	6.1	1095	105.0	0.012
4	6.1	1011	112.0	0.006

7.21 attitude

The Chatterjee-Price Attitude Data

rating	complaints	privileges	learning	raises	critical	advance
43	51	30	39	61	92	45
63	64	51	54	63	73	47
71	70	68	69	76	86	48
61	63	45	47	54	84	35
81	78	56	66	71	83	47
43	55	49	44	54	49	34
58	67	42	56	66	68	35
71	75	50	55	70	66	41
72	82	72	67	71	83	31
67	61	45	47	62	80	41
64	53	53	58	58	67	34
67	60	47	39	59	74	41
69	62	57	42	55	63	25
68	83	83	45	59	77	35
77	77	54	72	79	77	46
81	90	50	72	60	54	36
74	85	64	69	79	79	63
65	60	65	75	55	80	60
65	70	46	57	75	85	46
50	58	68	54	64	78	52

7.22 beaver1

Body Temperature Series of Two Beavers

day	time	temp	activ
346	840	36.33	0
346	850	36.34	0
346	900	36.35	0
346	910	36.42	0
346	920	36.55	0
346	930	36.69	0
346	940	36.71	0
346	950	36.75	0
346	1000	36.81	0
346	1010	36.88	0
346	1020	36.89	0
346	1030	36.91	0
346	1040	36.85	0
346	1050	36.89	0
346	1100	36.89	0
346	1110	36.67	0
346	1120	36.50	0
346	1130	36.74	0
346	1140	36.77	0
346	1150	36.76	0

7.23 beaver2

Body Temperature Series of Two Beavers

day	time	temp	activ
307	930	36.58	0
307	940	36.73	0
307	950	36.93	0
307	1000	37.15	0
307	1010	37.23	0
307	1020	37.24	0
307	1030	37.24	0
307	1040	36.90	0
307	1050	36.95	0
307	1100	36.89	0
307	1110	36.95	0
307	1120	37.00	0
307	1130	36.90	0
307	1140	36.99	0
307	1150	36.99	0
307	1200	37.01	0
307	1210	37.04	0
307	1220	37.04	0
307	1230	37.14	0
307	1240	37.07	0

7.24 cars

Speed and Stopping Distances of Cars

speed	dist
4	2
4	10
7	4
7	22
8	16
9	10
10	18
10	26
10	34
11	17
11	28
12	14
12	20
12	24
12	28
13	26
13	34
13	34
13	46
14	26

7.25 chickwts

Chicken Weights by Feed Type

weight	feed
179	horsebean
160	horsebean
136	horsebean
227	horsebean
217	horsebean
168	horsebean
108	horsebean
124	horsebean
143	horsebean
140	horsebean
309	linseed
229	linseed
181	linseed
141	linseed
260	linseed
203	linseed
148	linseed
169	linseed
213	linseed
257	linseed

7.26 esoph

Smoking, Alcohol and (O)esophageal Cancer

agegp	alcgp	tobgp	ncases	ncontrols
25-34	0-39g/day	0-9g/day	0	40
25-34	0-39g/day	10-19	0	10
25-34	0-39g/day	20-29	0	6
25-34	0-39g/day	30+	0	5
25-34	40-79	0-9g/day	0	27
25-34	40-79	10-19	0	7
25-34	40-79	20-29	0	4
25-34	40-79	30+	0	7
25-34	80-119	0-9g/day	0	2
25-34	80-119	10-19	0	1
25-34	80-119	30+	0	2
25-34	120+	0-9g/day	0	1
25-34	120+	10-19	1	0
25-34	120+	20-29	0	1
25-34	120+	30+	0	2
35-44	0-39g/day	0-9g/day	0	60
35-44	0-39g/day	10-19	1	13
35-44	0-39g/day	20-29	0	7
35-44	0-39g/day	30+	0	8
35-44	40-79	0-9g/day	0	35

7.27 faithful

Old Faithful Geyser Data

eruptions	waiting
3.600	79
1.800	54
3.333	74
2.283	62
4.533	85
2.883	55
4.700	88
3.600	85
1.950	51
4.350	85
1.833	54
3.917	84
4.200	78
1.750	47
4.700	83
2.167	52
1.750	62
4.800	84
1.600	52
4.250	79

7.28 freeny

Freeny’s Revenue Data

y	lag.quarterly.revenue	price.index	income.level	market.potential
8.79236	8.79636	4.70997	5.82110	12.9699
8.79137	8.79236	4.70217	5.82558	12.9733
8.81486	8.79137	4.68944	5.83112	12.9774
8.81301	8.81486	4.68558	5.84046	12.9806
8.90751	8.81301	4.64019	5.85036	12.9831
8.93673	8.90751	4.62553	5.86464	12.9854
8.96161	8.93673	4.61991	5.87769	12.9900
8.96044	8.96161	4.61654	5.89763	12.9943
9.00868	8.96044	4.61407	5.92574	12.9992
9.03049	9.00868	4.60766	5.94232	13.0033
9.06906	9.03049	4.60227	5.95365	13.0099
9.05871	9.06906	4.58960	5.96120	13.0159
9.10698	9.05871	4.57592	5.97805	13.0212
9.12685	9.10698	4.58661	6.00377	13.0265
9.17096	9.12685	4.57997	6.02829	13.0351
9.18665	9.17096	4.57176	6.03475	13.0429
9.23823	9.18665	4.56104	6.03906	13.0497
9.26487	9.23823	4.54906	6.05046	13.0551
9.28436	9.26487	4.53957	6.05563	13.0634
9.31378	9.28436	4.51018	6.06093	13.0693

7.29 infert

Infertility after Spontaneous and Induced Abortion

education	age	parity	induced	case	spontaneous	stratum	pooled.stratum
0-5yrs	26	6	1	1	2	1	3
0-5yrs	42	1	1	1	0	2	1
0-5yrs	39	6	2	1	0	3	4
0-5yrs	34	4	2	1	0	4	2
6-11yrs	35	3	1	1	1	5	32
6-11yrs	36	4	2	1	1	6	36
6-11yrs	23	1	0	1	0	7	6
6-11yrs	32	2	0	1	0	8	22
6-11yrs	21	1	0	1	1	9	5
6-11yrs	28	2	0	1	0	10	19
6-11yrs	29	2	1	1	0	11	20
6-11yrs	37	4	2	1	1	12	37
6-11yrs	31	1	1	1	0	13	9
6-11yrs	29	3	2	1	0	14	29
6-11yrs	31	2	1	1	1	15	21
6-11yrs	27	2	2	1	0	16	18
6-11yrs	30	5	2	1	1	17	38
6-11yrs	26	1	0	1	1	18	7
6-11yrs	25	3	2	1	1	19	28
6-11yrs	44	1	0	1	1	20	17

7.30 iris

Edgar Anderson’s Iris Data

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
5.1	3.5	1.4	0.2	setosa
4.9	3.0	1.4	0.2	setosa
4.7	3.2	1.3	0.2	setosa
4.6	3.1	1.5	0.2	setosa
5.0	3.6	1.4	0.2	setosa
5.4	3.9	1.7	0.4	setosa
4.6	3.4	1.4	0.3	setosa
5.0	3.4	1.5	0.2	setosa
4.4	2.9	1.4	0.2	setosa
4.9	3.1	1.5	0.1	setosa
5.4	3.7	1.5	0.2	setosa
4.8	3.4	1.6	0.2	setosa
4.8	3.0	1.4	0.1	setosa
4.3	3.0	1.1	0.1	setosa
5.8	4.0	1.2	0.2	setosa
5.7	4.4	1.5	0.4	setosa
5.4	3.9	1.3	0.4	setosa
5.1	3.5	1.4	0.3	setosa
5.7	3.8	1.7	0.3	setosa
5.1	3.8	1.5	0.3	setosa

7.31 longley

Longley’s Economic Regression Data

GNP.deflator	GNP	Unemployed	Armed.Forces	Population	Year	Employed
83.0	234.289	235.6	159.0	107.608	1947	60.323
88.5	259.426	232.5	145.6	108.632	1948	61.122
88.2	258.054	368.2	161.6	109.773	1949	60.171
89.5	284.599	335.1	165.0	110.929	1950	61.187
96.2	328.975	209.9	309.9	112.075	1951	63.221
98.1	346.999	193.2	359.4	113.270	1952	63.639
99.0	365.385	187.0	354.7	115.094	1953	64.989
100.0	363.112	357.8	335.0	116.219	1954	63.761
101.2	397.469	290.4	304.8	117.388	1955	66.019
104.6	419.180	282.2	285.7	118.734	1956	67.857
108.4	442.769	293.6	279.8	120.445	1957	68.169
110.8	444.546	468.1	263.7	121.950	1958	66.513
112.6	482.704	381.3	255.2	123.366	1959	68.655
114.2	502.601	393.1	251.4	125.368	1960	69.564
115.7	518.173	480.6	257.2	127.852	1961	69.331
116.9	554.894	400.7	282.7	130.081	1962	70.551

7.32 morley

Michelson Speed of Light Data

Expt	Run	Speed
1	1	850
1	2	740
1	3	900
1	4	1070
1	5	930
1	6	850
1	7	950
1	8	980
1	9	980
1	10	880
1	11	1000
1	12	980
1	13	930
1	14	650
1	15	760
1	16	810
1	17	1000
1	18	1000
1	19	960
1	20	960

7.33 mtcars

Motor Trend Car Road Tests

mpg	cyl	disp	hp	drat	wt	qsec	vs	am	gear	carb
21.0	6	160.0	110	3.90	2.620	16.46	0	1	4	4
21.0	6	160.0	110	3.90	2.875	17.02	0	1	4	4
22.8	4	108.0	93	3.85	2.320	18.61	1	1	4	1
21.4	6	258.0	110	3.08	3.215	19.44	1	0	3	1
18.7	8	360.0	175	3.15	3.440	17.02	0	0	3	2
18.1	6	225.0	105	2.76	3.460	20.22	1	0	3	1
14.3	8	360.0	245	3.21	3.570	15.84	0	0	3	4
24.4	4	146.7	62	3.69	3.190	20.00	1	0	4	2
22.8	4	140.8	95	3.92	3.150	22.90	1	0	4	2
19.2	6	167.6	123	3.92	3.440	18.30	1	0	4	4
17.8	6	167.6	123	3.92	3.440	18.90	1	0	4	4
16.4	8	275.8	180	3.07	4.070	17.40	0	0	3	3
17.3	8	275.8	180	3.07	3.730	17.60	0	0	3	3
15.2	8	275.8	180	3.07	3.780	18.00	0	0	3	3
10.4	8	472.0	205	2.93	5.250	17.98	0	0	3	4
10.4	8	460.0	215	3.00	5.424	17.82	0	0	3	4
14.7	8	440.0	230	3.23	5.345	17.42	0	0	3	4
32.4	4	78.7	66	4.08	2.200	19.47	1	1	4	1
30.4	4	75.7	52	4.93	1.615	18.52	1	1	4	2
33.9	4	71.1	65	4.22	1.835	19.90	1	1	4	1

7.34 npk

Classical N, P, K Factorial Experiment

block	N	P	K	yield
1	0	1	1	49.5
1	1	1	0	62.8
1	0	0	0	46.8
1	1	0	1	57.0
2	1	0	0	59.8
2	1	1	1	58.5
2	0	0	1	55.5
2	0	1	0	56.0
3	0	1	0	62.8
3	1	1	1	55.8
3	1	0	0	69.5
3	0	0	1	55.0
4	1	0	0	62.0
4	1	1	1	48.8
4	0	0	1	45.5
4	0	1	0	44.2
5	1	1	0	52.0
5	0	0	0	51.5
5	1	0	1	49.8
5	0	1	1	48.8

7.35 pressure

Vapor Pressure of Mercury as a Function of Temperature

temperature	pressure
0	0.0002
20	0.0012
40	0.0060
60	0.0300
80	0.0900
100	0.2700
120	0.7500
140	1.8500
160	4.2000
180	8.8000
200	17.3000
220	32.1000
240	57.0000
260	96.0000
280	157.0000
300	247.0000
320	376.0000
340	558.0000
360	806.0000

7.36 quakes

Locations of Earthquakes off Fiji

lat	long	depth	mag	stations
-20.42	181.62	562	4.8	41
-20.62	181.03	650	4.2	15
-26.00	184.10	42	5.4	43
-17.97	181.66	626	4.1	19
-20.42	181.96	649	4.0	11
-19.68	184.31	195	4.0	12
-11.70	166.10	82	4.8	43
-28.11	181.93	194	4.4	15
-28.74	181.74	211	4.7	35
-17.47	179.59	622	4.3	19
-21.44	180.69	583	4.4	13
-12.26	167.00	249	4.6	16
-18.54	182.11	554	4.4	19
-21.00	181.66	600	4.4	10
-20.70	169.92	139	6.1	94
-15.94	184.95	306	4.3	11
-13.64	165.96	50	6.0	83
-17.83	181.50	590	4.5	21
-23.50	179.78	570	4.4	13
-22.63	180.31	598	4.4	18

7.37 randu

Random Numbers from Congruential Generator RANDU

x	y	z
0.000031	0.000183	0.000824
0.044495	0.155732	0.533939
0.822440	0.873416	0.838542
0.322291	0.648545	0.990648
0.393595	0.826873	0.418881
0.309097	0.926590	0.777664
0.826368	0.308540	0.413932
0.729424	0.741526	0.884338
0.317649	0.393468	0.501968
0.599793	0.846041	0.678107
0.647603	0.281525	0.860718
0.547048	0.948790	0.769314
0.529873	0.348011	0.319211
0.908040	0.013456	0.908380
0.835195	0.814513	0.370327
0.068696	0.275943	0.037394
0.984329	0.927687	0.707165
0.945783	0.689675	0.626002
0.017137	0.166494	0.844727
0.772506	0.282393	0.741801

7.38 rock

Measurements on Petroleum Rock Samples

area	peri	shape	perm
4990	2791.90	0.0903296	6.3
7002	3892.60	0.1486220	6.3
7558	3930.66	0.1833120	6.3
7352	3869.32	0.1170630	6.3
7943	3948.54	0.1224170	17.1
7979	4010.15	0.1670450	17.1
9333	4345.75	0.1896510	17.1
8209	4344.75	0.1641270	17.1
8393	3682.04	0.2036540	119.0
6425	3098.65	0.1623940	119.0
9364	4480.05	0.1509440	119.0
8624	3986.24	0.1481410	119.0
10651	4036.54	0.2285950	82.4
8868	3518.04	0.2316230	82.4
9417	3999.37	0.1725670	82.4
8874	3629.07	0.1534810	82.4
10962	4608.66	0.2043140	58.6
10743	4787.62	0.2627270	58.6
11878	4864.22	0.2000710	58.6
9867	4479.41	0.1448100	58.6

7.39 sleep

Student’s Sleep Data

extra	group	ID
0.7	1	1
-1.6	1	2
-0.2	1	3
-1.2	1	4
-0.1	1	5
3.4	1	6
3.7	1	7
0.8	1	8
0.0	1	9
2.0	1	10
1.9	2	1
0.8	2	2
1.1	2	3
0.1	2	4
-0.1	2	5
4.4	2	6
5.5	2	7
1.6	2	8
4.6	2	9
3.4	2	10

7.40 stackloss

Brownlee’s Stack Loss Plant Data

Air.Flow	Water.Temp	Acid.Conc.	stack.loss
80	27	89	42
80	27	88	37
75	25	90	37
62	24	87	28
62	22	87	18
62	23	87	18
62	24	93	19
62	24	93	20
58	23	87	15
58	18	80	14
58	18	89	14
58	17	88	13
58	18	82	11
58	19	93	12
50	18	89	8
50	18	86	7
50	19	72	8
50	19	79	8
50	20	80	9
56	20	82	15

7.41 swiss

Swiss Fertility and Socioeconomic Indicators (1888) Data

Fertility	Agriculture	Examination	Education	Catholic	Infant.Mortality
80.2	17.0	15	12	9.96	22.2
83.1	45.1	6	9	84.84	22.2
92.5	39.7	5	5	93.40	20.2
85.8	36.5	12	7	33.77	20.3
76.9	43.5	17	15	5.16	20.6
76.1	35.3	9	7	90.57	26.6
83.8	70.2	16	7	92.85	23.6
92.4	67.8	14	8	97.16	24.9
82.4	53.3	12	7	97.67	21.0
82.9	45.2	16	13	91.38	24.4
87.1	64.5	14	6	98.61	24.5
64.1	62.0	21	12	8.52	16.5
66.9	67.5	14	7	2.27	19.1
68.9	60.7	19	12	4.43	22.7
61.7	69.3	22	5	2.82	18.7
68.3	72.6	18	2	24.20	21.2
71.7	34.0	17	8	3.30	20.0
55.7	19.4	26	28	12.11	20.2
54.3	15.2	31	20	2.15	10.8
65.1	73.0	19	9	2.84	20.0

7.42 trees

Diameter, Height and Volume for Black Cherry Trees

Girth	Height	Volume
8.3	70	10.3
8.6	65	10.3
8.8	63	10.2
10.5	72	16.4
10.7	81	18.8
10.8	83	19.7
11.0	66	15.6
11.0	75	18.2
11.1	80	22.6
11.2	75	19.9
11.3	79	24.2
11.4	76	21.0
11.4	76	21.4
11.7	69	21.3
12.0	75	19.1
12.9	74	22.2
12.9	85	33.8
13.3	86	27.4
13.7	71	25.7
13.8	64	24.9

7.43 warpbreaks

The Number of Breaks in Yarn during Weaving

breaks	wool	tension
26	A	L
30	A	L
54	A	L
25	A	L
70	A	L
52	A	L
51	A	L
26	A	L
67	A	L
18	A	M
21	A	M
29	A	M
17	A	M
12	A	M
18	A	M
35	A	M
30	A	M
36	A	M
36	A	H
21	A	H

7.44 women

Average Heights and Weights for American Women

height	weight
58	115
59	117
60	120
61	123
62	126
63	129
64	132
65	135
66	139
67	142
68	146
69	150
70	154
71	159
72	164