1 datasets-islr

1.1 auto🔗ℹ

392 rows × 9 columns. Gas mileage, horsepower, and other information for 392 vehicles. The 392 vehicles with a known horsepower: ISLR2 dropped 5 of the 397 rows of Auto.data, and the numeric row names that index them are not kept. name is categorical with all 304 R levels. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
mpg	mpg	real	miles per gallon; miles per gallon; ()
cylinders	cylinders	integer	Number of cylinders between 4 and 8; #f; ()
displacement	displacement	real	Engine displacement (cu. inches); #f; ()
horsepower	horsepower	integer	Engine horsepower; #f; ()
weight	weight	integer	Vehicle weight (lbs.); lbs; ()
acceleration	acceleration	real	Time to accelerate from 0 to 60 mph (sec.); #f; ()
year	year	integer	Model year (modulo 100); #f; ()
origin	origin	integer	Origin of car (1. American, 2. European, 3. Japanese); #f; ()
name	name	categorical	Vehicle name; #f; (amc ambassador brougham amc ambassador dpl amc ambassador sst amc concord amc concord d/l amc concord dl 6 amc gremlin amc hornet amc hornet sportabout (sw) amc matador amc matador (sw) amc pacer amc pacer d/l amc rebel sst amc spirit dl audi 100 ls audi 100ls audi 4000 audi 5000 audi 5000s (diesel) audi fox bmw 2002 bmw 320i buick century buick century 350 buick century limited buick century luxus (sw) buick century special buick electra 225 custom buick estate wagon (sw) buick lesabre custom buick opel isuzu deluxe buick regal sport coupe (turbo) buick skyhawk buick skylark buick skylark 320 buick skylark limited cadillac eldorado cadillac seville capri ii chevroelt chevelle malibu chevrolet bel air chevrolet camaro chevrolet caprice classic chevrolet cavalier chevrolet cavalier 2-door chevrolet cavalier wagon chevrolet chevelle concours (sw) chevrolet chevelle malibu chevrolet chevelle malibu classic chevrolet chevette chevrolet citation chevrolet concours chevrolet impala chevrolet malibu chevrolet malibu classic (sw) chevrolet monte carlo chevrolet monte carlo landau chevrolet monte carlo s chevrolet monza 2+2 chevrolet nova chevrolet nova custom chevrolet vega chevrolet vega (sw) chevrolet vega 2300 chevrolet woody chevy c10 chevy c20 chevy s-10 chrysler cordoba chrysler lebaron medallion chrysler lebaron salon chrysler lebaron town @ country (sw) chrysler new yorker brougham chrysler newport royal datsun 1200 datsun 200-sx datsun 200sx datsun 210 datsun 210 mpg datsun 280-zx datsun 310 datsun 310 gx datsun 510 datsun 510 (sw) datsun 510 hatchback datsun 610 datsun 710 datsun 810 datsun 810 maxima datsun b-210 datsun b210 datsun b210 gx datsun f-10 hatchback datsun pl510 dodge aries se dodge aries wagon (sw) dodge aspen dodge aspen 6 dodge aspen se dodge challenger se dodge charger 2.2 dodge colt dodge colt (sw) dodge colt hardtop dodge colt hatchback custom dodge colt m/m dodge coronet brougham dodge coronet custom dodge coronet custom (sw) dodge d100 dodge d200 dodge dart custom dodge diplomat dodge magnum xe dodge monaco (sw) dodge monaco brougham dodge omni dodge rampage dodge st. regis fiat 124 sport coupe fiat 124 tc fiat 124b fiat 128 fiat 131 fiat strada custom fiat x1.9 ford country ford country squire (sw) ford escort 2h ford escort 4w ford f108 ford f250 ford fairmont ford fairmont (auto) ford fairmont (man) ford fairmont 4 ford fairmont futura ford fiesta ford futura ford galaxie 500 ford gran torino ford gran torino (sw) ford granada ford granada ghia ford granada gl ford granada l ford ltd ford ltd landau ford maverick ford mustang ford mustang cobra ford mustang gl ford mustang ii ford mustang ii 2+2 ford pinto ford pinto (sw) ford pinto runabout ford ranger ford thunderbird ford torino ford torino 500 hi 1200d honda accord honda accord cvcc honda accord lx honda civic honda civic (auto) honda civic 1300 honda civic 1500 gl honda civic cvcc honda prelude maxda glc deluxe maxda rx3 mazda 626 mazda glc mazda glc 4 mazda glc custom mazda glc custom l mazda glc deluxe mazda rx-4 mazda rx-7 gs mazda rx2 coupe mercedes benz 300d mercedes-benz 240d mercedes-benz 280s mercury capri 2000 mercury capri v6 mercury cougar brougham mercury grand marquis mercury lynx l mercury marquis mercury marquis brougham mercury monarch mercury monarch ghia mercury zephyr mercury zephyr 6 nissan stanza xe oldsmobile cutlass ciera (diesel) oldsmobile cutlass ls oldsmobile cutlass salon brougham oldsmobile cutlass supreme oldsmobile delta 88 royale oldsmobile omega oldsmobile omega brougham oldsmobile starfire sx oldsmobile vista cruiser opel 1900 opel manta peugeot 304 peugeot 504 peugeot 504 (sw) peugeot 505s turbo diesel peugeot 604sl plymouth 'cuda 340 plymouth arrow gs plymouth champ plymouth cricket plymouth custom suburb plymouth duster plymouth fury plymouth fury gran sedan plymouth fury iii plymouth grand fury plymouth horizon plymouth horizon 4 plymouth horizon miser plymouth horizon tc3 plymouth reliant plymouth sapporo plymouth satellite plymouth satellite custom plymouth satellite custom (sw) plymouth satellite sebring plymouth valiant plymouth valiant custom plymouth volare plymouth volare custom plymouth volare premier v8 pontiac astro pontiac catalina pontiac catalina brougham pontiac firebird pontiac grand prix pontiac grand prix lj pontiac j2000 se hatchback pontiac lemans v6 pontiac phoenix pontiac phoenix lj pontiac safari (sw) pontiac sunbird coupe pontiac ventura sj renault 12 (sw) renault 12tl renault 18i renault 5 gtl renault lecar deluxe saab 99e saab 99gle saab 99le subaru subaru dl toyota carina toyota celica gt toyota celica gt liftback toyota corolla toyota corolla 1200 toyota corolla 1600 (sw) toyota corolla liftback toyota corolla tercel toyota corona toyota corona hardtop toyota corona liftback toyota corona mark ii toyota cressida toyota mark ii toyota starlet toyota tercel toyouta corona mark ii (sw) triumph tr7 coupe vokswagen rabbit volkswagen 1131 deluxe sedan volkswagen 411 (sw) volkswagen dasher volkswagen jetta volkswagen model 111 volkswagen rabbit volkswagen rabbit custom volkswagen rabbit custom diesel volkswagen rabbit l volkswagen scirocco volkswagen super beetle volkswagen type 3 volvo 144ea volvo 145e (sw) volvo 244dl volvo 245 volvo 264gl volvo diesel vw dasher (diesel) vw pickup vw rabbit vw rabbit c (diesel) vw rabbit custom)

1.2 bikeshare🔗ℹ

8645 rows × 15 columns. This data set contains the hourly and daily count of rental bikes between years 2011 and 2012 in Capital bikeshare system, along with weather and seasonal information. Only 2011 is included: 8,645 hours, day 1 to 365. hr is categorical with levels "0" to "23"; mnth keeps R’s level labels. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
season	season	integer	Season of the year, coded as Winter=1, Spring=2, Summer=3, Fall=4.; #f; ()
mnth	mnth	categorical	Month of the year, coded as a factor.; #f; (Jan Feb March April May June July Aug Sept Oct Nov Dec)
day	day	integer	Day of the year, from 1 to 365; #f; ()
hr	hr	categorical	Hour of the day, coded as a factor from 0 to 23.; #f; (0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23)
holiday	holiday	integer	Is it a holiday? Yes=1, No=0.; #f; ()
weekday	weekday	integer	Day of the week, coded from 0 to 6, where Sunday=0, Monday=1, Tuesday=2, etc.; #f; ()
workingday	workingday	integer	Is it a work day? Yes=1, No=0.; #f; ()
weathersit	weathersit	categorical	Weather, coded as a factor.; #f; (clear cloudy/misty light rain/snow heavy rain/snow)
temp	temp	real	Normalized temperature in Celsius. The values are derived via (t-t_min)/(t_max-t_min), t_min=-8, t_max=+39.; #f; ()
atemp	atemp	real	Normalized feeling temperature in Celsius. The values are derived via (t-t_min)/(t_max-t_min), t_min=-16, t_max=+50.; #f; ()
hum	hum	real	Normalized humidity. The values are divided to 100 (max).; #f; ()
windspeed	windspeed	real	Normalized wind speed. The values are divided by 67 (max).; #f; ()
casual	casual	integer	Number of casual bikers.; #f; ()
registered	registered	integer	Number of registered bikers.; #f; ()
bikers	bikers	integer	Total number of bikers.; #f; ()

1.3 boston🔗ℹ

506 rows × 13 columns. A data set containing housing values in 506 suburbs of Boston. ISLR2’s Boston: MASS::Boston without the black column. names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
crim	crim	real	per capita crime rate by town.; #f; ()
zn	zn	real	proportion of residential land zoned for lots over 25,000 sq.ft.; #f; ()
indus	indus	real	proportion of non-retail business acres per town.; #f; ()
chas	chas	integer	Charles River dummy variable (= 1 if tract bounds river; 0 otherwise).; #f; ()
nox	nox	real	nitrogen oxides concentration (parts per 10 million).; #f; ()
rm	rm	real	average number of rooms per dwelling.; #f; ()
age	age	real	proportion of owner-occupied units built prior to 1940.; #f; ()
dis	dis	real	weighted mean of distances to five Boston employment centres.; #f; ()
rad	rad	integer	index of accessibility to radial highways.; #f; ()
tax	tax	integer	full-value property-tax rate per $10,000.; #f; ()
ptratio	ptratio	real	pupil-teacher ratio by town.; #f; ()
lstat	lstat	real	lower status of the population (percent).; #f; ()
medv	medv	real	median value of owner-occupied homes in $1000s.; $1000s; ()

1.4 brain-cancer🔗ℹ

88 rows × 8 columns. A data set consisting of survival times for patients diagnosed with brain cancer. Survival data: time with status 1 = event observed, 0 = censored. One diagnosis is missing. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
sex	sex	categorical	Factor with levels "Female" and "Male"; #f; (Female Male)
diagnosis	diagnosis	categorical	Factor with levels "Meningioma", "LG glioma", "HG glioma", and "Other".; #f; (Meningioma LG glioma HG glioma Other)
loc	loc	categorical	Location factor with levels "Infratentorial" and "Supratentorial".; #f; (Infratentorial Supratentorial)
ki	ki	integer	Karnofsky index.; #f; ()
gtv	gtv	real	Gross tumor volume, in cubic centimeters.; cm^3; ()
stereo	stereo	categorical	Stereotactic method factor with levels "SRS" and "SRT".; #f; (SRS SRT)
status	status	integer	Whether the patient is still alive at the end of the study: 0=Yes, 1=No.; #f; ()
time	time	real	Survival time, in months.; months; ()

1.5 caravan🔗ℹ

5822 rows × 86 columns. The data contains 5822 real customer records. Each record consists of 86 variables, containing sociodemographic data (variables 1-43) and product ownership (variables 44-86). The sociodemographic data is derived from zip codes. All customers living in areas with the same zip code have the same sociodemographic attributes. Variable 86 (Purchase) indicates whether the customer purchased a caravan insurance policy. Further information on the individual variables can be obtained at http://www.liacs.nl/~putten/library/cc2000/data.html. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
mostype	MOSTYPE	integer	MOSTYPE; #f; ()
maanthui	MAANTHUI	integer	MAANTHUI; #f; ()
mgemomv	MGEMOMV	integer	MGEMOMV; #f; ()
mgemleef	MGEMLEEF	integer	MGEMLEEF; #f; ()
moshoofd	MOSHOOFD	integer	MOSHOOFD; #f; ()
mgodrk	MGODRK	integer	MGODRK; #f; ()
mgodpr	MGODPR	integer	MGODPR; #f; ()
mgodov	MGODOV	integer	MGODOV; #f; ()
mgodge	MGODGE	integer	MGODGE; #f; ()
mrelge	MRELGE	integer	MRELGE; #f; ()
mrelsa	MRELSA	integer	MRELSA; #f; ()
mrelov	MRELOV	integer	MRELOV; #f; ()
mfalleen	MFALLEEN	integer	MFALLEEN; #f; ()
mfgekind	MFGEKIND	integer	MFGEKIND; #f; ()
mfwekind	MFWEKIND	integer	MFWEKIND; #f; ()
moplhoog	MOPLHOOG	integer	MOPLHOOG; #f; ()
moplmidd	MOPLMIDD	integer	MOPLMIDD; #f; ()
mopllaag	MOPLLAAG	integer	MOPLLAAG; #f; ()
mberhoog	MBERHOOG	integer	MBERHOOG; #f; ()
mberzelf	MBERZELF	integer	MBERZELF; #f; ()
mberboer	MBERBOER	integer	MBERBOER; #f; ()
mbermidd	MBERMIDD	integer	MBERMIDD; #f; ()
mberarbg	MBERARBG	integer	MBERARBG; #f; ()
mberarbo	MBERARBO	integer	MBERARBO; #f; ()
mska	MSKA	integer	MSKA; #f; ()
mskb1	MSKB1	integer	MSKB1; #f; ()
mskb2	MSKB2	integer	MSKB2; #f; ()
mskc	MSKC	integer	MSKC; #f; ()
mskd	MSKD	integer	MSKD; #f; ()
mhhuur	MHHUUR	integer	MHHUUR; #f; ()
mhkoop	MHKOOP	integer	MHKOOP; #f; ()
maut1	MAUT1	integer	MAUT1; #f; ()
maut2	MAUT2	integer	MAUT2; #f; ()
maut0	MAUT0	integer	MAUT0; #f; ()
mzfonds	MZFONDS	integer	MZFONDS; #f; ()
mzpart	MZPART	integer	MZPART; #f; ()
minkm30	MINKM30	integer	MINKM30; #f; ()
mink3045	MINK3045	integer	MINK3045; #f; ()
mink4575	MINK4575	integer	MINK4575; #f; ()
mink7512	MINK7512	integer	MINK7512; #f; ()
mink123m	MINK123M	integer	MINK123M; #f; ()
minkgem	MINKGEM	integer	MINKGEM; #f; ()
mkoopkla	MKOOPKLA	integer	MKOOPKLA; #f; ()
pwapart	PWAPART	integer	PWAPART; #f; ()
pwabedr	PWABEDR	integer	PWABEDR; #f; ()
pwaland	PWALAND	integer	PWALAND; #f; ()
ppersaut	PPERSAUT	integer	PPERSAUT; #f; ()
pbesaut	PBESAUT	integer	PBESAUT; #f; ()
pmotsco	PMOTSCO	integer	PMOTSCO; #f; ()
pvraaut	PVRAAUT	integer	PVRAAUT; #f; ()
paanhang	PAANHANG	integer	PAANHANG; #f; ()
ptractor	PTRACTOR	integer	PTRACTOR; #f; ()
pwerkt	PWERKT	integer	PWERKT; #f; ()
pbrom	PBROM	integer	PBROM; #f; ()
pleven	PLEVEN	integer	PLEVEN; #f; ()
ppersong	PPERSONG	integer	PPERSONG; #f; ()
pgezong	PGEZONG	integer	PGEZONG; #f; ()
pwaoreg	PWAOREG	integer	PWAOREG; #f; ()
pbrand	PBRAND	integer	PBRAND; #f; ()
pzeilpl	PZEILPL	integer	PZEILPL; #f; ()
pplezier	PPLEZIER	integer	PPLEZIER; #f; ()
pfiets	PFIETS	integer	PFIETS; #f; ()
pinboed	PINBOED	integer	PINBOED; #f; ()
pbystand	PBYSTAND	integer	PBYSTAND; #f; ()
awapart	AWAPART	integer	AWAPART; #f; ()
awabedr	AWABEDR	integer	AWABEDR; #f; ()
awaland	AWALAND	integer	AWALAND; #f; ()
apersaut	APERSAUT	integer	APERSAUT; #f; ()
abesaut	ABESAUT	integer	ABESAUT; #f; ()
amotsco	AMOTSCO	integer	AMOTSCO; #f; ()
avraaut	AVRAAUT	integer	AVRAAUT; #f; ()
aaanhang	AAANHANG	integer	AAANHANG; #f; ()
atractor	ATRACTOR	integer	ATRACTOR; #f; ()
awerkt	AWERKT	integer	AWERKT; #f; ()
abrom	ABROM	integer	ABROM; #f; ()
aleven	ALEVEN	integer	ALEVEN; #f; ()
apersong	APERSONG	integer	APERSONG; #f; ()
agezong	AGEZONG	integer	AGEZONG; #f; ()
awaoreg	AWAOREG	integer	AWAOREG; #f; ()
abrand	ABRAND	integer	ABRAND; #f; ()
azeilpl	AZEILPL	integer	AZEILPL; #f; ()
aplezier	APLEZIER	integer	APLEZIER; #f; ()
afiets	AFIETS	integer	AFIETS; #f; ()
ainboed	AINBOED	integer	AINBOED; #f; ()
abystand	ABYSTAND	integer	ABYSTAND; #f; ()
purchase	Purchase	categorical	Purchase; #f; (No Yes)

1.6 carseats🔗ℹ

400 rows × 11 columns. A simulated data set containing sales of child car seats at 400 different stores. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
sales	Sales	real	Unit sales (in thousands) at each location; thousands of units; ()
comp-price	CompPrice	integer	Price charged by competitor at each location; #f; ()
income	Income	integer	Community income level (in thousands of dollars); #f; ()
advertising	Advertising	integer	Local advertising budget for company at each location (in thousands of dollars); #f; ()
population	Population	integer	Population size in region (in thousands); #f; ()
price	Price	integer	Price company charges for car seats at each site; #f; ()
shelve-loc	ShelveLoc	categorical	A factor with levels Bad, Good and Medium indicating the quality of the shelving location for the car seats at each site; #f; (Bad Good Medium)
age	Age	integer	Average age of the local population; #f; ()
education	Education	integer	Education level at each location; #f; ()
urban	Urban	categorical	A factor with levels No and Yes to indicate whether the store is in an urban or rural location; #f; (No Yes)
us	US	categorical	A factor with levels No and Yes to indicate whether the store is in the US or not; #f; (No Yes)

1.7 college🔗ℹ

777 rows × 19 columns. Statistics for a large number of US Colleges from the 1995 issue of US News and World Report. The college names, R row names, become the first column, name. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
name	row names	identifier	College name; #f; ()
private	Private	categorical	A factor with levels No and Yes indicating private or public university; #f; (No Yes)
apps	Apps	integer	Number of applications received; #f; ()
accept	Accept	integer	Number of applications accepted; #f; ()
enroll	Enroll	integer	Number of new students enrolled; #f; ()
top10perc	Top10perc	integer	Pct. new students from top 10% of H.S. class; #f; ()
top25perc	Top25perc	integer	Pct. new students from top 25% of H.S. class; #f; ()
full-time-undergrad	F.Undergrad	integer	Number of fulltime undergraduates; #f; ()
part-time-undergrad	P.Undergrad	integer	Number of parttime undergraduates; #f; ()
outstate	Outstate	integer	Out-of-state tuition; #f; ()
room-board	Room.Board	integer	Room and board costs; #f; ()
books	Books	integer	Estimated book costs; #f; ()
personal	Personal	integer	Estimated personal spending; #f; ()
phd	PhD	integer	Pct. of faculty with Ph.D.'s; #f; ()
terminal	Terminal	integer	Pct. of faculty with terminal degree; #f; ()
sf-ratio	S.F.Ratio	real	Student/faculty ratio; #f; ()
perc-alumni	perc.alumni	integer	Pct. alumni who donate; #f; ()
expend	Expend	integer	Instructional expenditure per student; #f; ()
grad-rate	Grad.Rate	integer	Graduation rate; #f; ()

1.8 credit🔗ℹ

400 rows × 11 columns. A simulated data set containing information on 400 customers. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
income	Income	real	Income in $1,000's; #f; ()
limit	Limit	integer	Credit limit; #f; ()
rating	Rating	integer	Credit rating; #f; ()
cards	Cards	integer	Number of credit cards; #f; ()
age	Age	integer	Age in years; #f; ()
education	Education	integer	Education in years; #f; ()
own	Own	categorical	A factor with levels No and Yes indicating whether the individual owns a home; #f; (No Yes)
student	Student	categorical	A factor with levels No and Yes indicating whether the individual is a student; #f; (No Yes)
married	Married	categorical	A factor with levels No and Yes indicating whether the individual is married; #f; (No Yes)
region	Region	categorical	A factor with levels East, South, and West indicating the individual's geographical location; #f; (East South West)
balance	Balance	integer	Average credit card balance in $.; #f; ()

1.9 default🔗ℹ

10000 rows × 4 columns. A simulated data set containing information on ten thousand customers. The aim here is to predict which customers will default on their credit card debt. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
default	default	categorical	A factor with levels No and Yes indicating whether the customer defaulted on their debt; #f; (No Yes)
student	student	categorical	A factor with levels No and Yes indicating whether the customer is a student; #f; (No Yes)
balance	balance	real	The average balance that the customer has remaining on their credit card after making their monthly payment; #f; ()
income	income	real	Income of customer; #f; ()

1.10 fund🔗ℹ

50 rows × 2000 columns. A simulated data set containing the returns for 2,000 hedge fund managers. Wide form: one row per month (50), one column per manager (2,000). names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column		Original		Type		Description / unit / levels
manager1 … manager2000		Manager1 … Manager2000		real		Manager1 … Manager2000; #f; ()

1.11 hitters🔗ℹ

322 rows × 21 columns. Major League Baseball Data from the 1986 and 1987 seasons. The player names, R row names, become the first column, player, with their leading hyphen kept. The 59 missing salaries are retained. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
player	row names	identifier	Player name; #f; ()
at-bat	AtBat	integer	Number of times at bat in 1986; #f; ()
hits	Hits	integer	Number of hits in 1986; #f; ()
hm-run	HmRun	integer	Number of home runs in 1986; #f; ()
runs	Runs	integer	Number of runs in 1986; #f; ()
rbi	RBI	integer	Number of runs batted in in 1986; #f; ()
walks	Walks	integer	Number of walks in 1986; #f; ()
years	Years	integer	Number of years in the major leagues; #f; ()
career-at-bat	CAtBat	integer	Number of times at bat during his career; #f; ()
career-hits	CHits	integer	Number of hits during his career; #f; ()
career-hm-run	CHmRun	integer	Number of home runs during his career; #f; ()
career-runs	CRuns	integer	Number of runs during his career; #f; ()
career-rbi	CRBI	integer	Number of runs batted in during his career; #f; ()
career-walks	CWalks	integer	Number of walks during his career; #f; ()
league	League	categorical	A factor with levels A and N indicating player's league at the end of 1986; #f; (A N)
division	Division	categorical	A factor with levels E and W indicating player's division at the end of 1986; #f; (E W)
put-outs	PutOuts	integer	Number of put outs in 1986; #f; ()
assists	Assists	integer	Number of assists in 1986; #f; ()
errors	Errors	integer	Number of errors in 1986; #f; ()
salary	Salary	real	1987 annual salary on opening day in thousands of dollars; thousands of dollars; ()
new-league	NewLeague	categorical	A factor with levels A and N indicating player's league at the beginning of 1987; #f; (A N)

1.12 khan🔗ℹ

83 rows × 2310 columns. The data consists of a number of tissue samples corresponding to four distinct types of small round blue cell tumors. For each tissue sample, 2308 gene expression measurements are available. Wide form of the Khan list: the 63 xtrain rows then the 20 xtest rows, told apart by split; y is ytrain or ytest, the tumour class 1-4; gene-1 to gene-2308 are the expression values, original names their column numbers. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
split	xtrain or xtest	categorical	Training or test sample; #f; (train test)
y	ytrain or ytest	integer	Tumour class, 1-4; #f; ()
gene-1 … gene-2308	1 … 2308	real	1 … 2308; #f; ()

1.13 nci60🔗ℹ

64 rows × 6831 columns. NCI microarray data. The data contains expression levels on 6830 genes from 64 cancer cell lines. Cancer type is also recorded. Wide form of the NCI60 list: label is labs, the cancer type (categorical, sorted levels); gene-1 to gene-6830 are the columns of data, original names their column names. The labels are for checking clusters, not a target. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
label	labs	categorical	Cancer type of the cell line; #f; (BREAST CNS COLON K562A-repro K562B-repro LEUKEMIA MCF7A-repro MCF7D-repro MELANOMA NSCLC OVARIAN PROSTATE RENAL UNKNOWN)
gene-1 … gene-6830	1 … 6830	real	1 … 6830; #f; ()

1.14 nyse🔗ℹ

6051 rows × 6 columns. Data consisting of the Dow Jones returns, log trading volume, and log volatility for the New York Stock Exchange over a 20 year period. date stays an ISO 8601 string; day-of-week is categorical, weekdays in order; train, an R logical, is 1 for the first 4,281 days and 0 after. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
date	date	string	Date; #f; ()
day-of-week	day_of_week	categorical	Day of the week; #f; (mon tues wed thur fri)
dj-return	DJ_return	real	Return for Dow Jones Industrial Average; #f; ()
log-volume	log_volume	real	Log of trading volume; #f; ()
log-volatility	log_volatility	real	Log of volatility; #f; ()
train	train	integer	For the first 4,281 observations, this is set to TRUE; #f; ()

1.15 oj🔗ℹ

1070 rows × 18 columns. The data contains 1070 purchases where the customer either purchased Citrus Hill or Minute Maid Orange Juice. A number of characteristics of the customer and product are recorded. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
purchase	Purchase	categorical	A factor with levels CH and MM indicating whether the customer purchased Citrus Hill or Minute Maid Orange Juice; #f; (CH MM)
week-of-purchase	WeekofPurchase	integer	Week of purchase; #f; ()
store-id	StoreID	integer	Store ID; #f; ()
price-ch	PriceCH	real	Price charged for CH; #f; ()
price-mm	PriceMM	real	Price charged for MM; #f; ()
disc-ch	DiscCH	real	Discount offered for CH; #f; ()
disc-mm	DiscMM	real	Discount offered for MM; #f; ()
special-ch	SpecialCH	integer	Indicator of special on CH; #f; ()
special-mm	SpecialMM	integer	Indicator of special on MM; #f; ()
loyal-ch	LoyalCH	real	Customer brand loyalty for CH; #f; ()
sale-price-mm	SalePriceMM	real	Sale price for MM; #f; ()
sale-price-ch	SalePriceCH	real	Sale price for CH; #f; ()
price-diff	PriceDiff	real	Sale price of MM less sale price of CH; #f; ()
store7	Store7	categorical	A factor with levels No and Yes indicating whether the sale is at Store 7; #f; (No Yes)
pct-disc-mm	PctDiscMM	real	Percentage discount for MM; #f; ()
pct-disc-ch	PctDiscCH	real	Percentage discount for CH; #f; ()
list-price-diff	ListPriceDiff	real	List price of MM less list price of CH; #f; ()
store	STORE	integer	Which of 5 possible stores the sale occured at; #f; ()

1.16 ozone🔗ℹ

111 rows × 4 columns. Ozone data from New York. The 111 complete days of airquality without month and day. Two cells differ: wind on 1973-07-01 (4 vs 4.1) and ozone on 1973-09-01 (95.9999999999999 vs 96).

Halvorsen, K. B. (2019). ElemStatLearn: Data Sets, Functions and Examples from the Book "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman. R package version 2015.6.26.2. Book: Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning, Second Edition. Springer. https://hastie.su.domains/ElemStatLearn/. Original sources in the bundled upstream documentation.

ElemStatLearn 2015.6.26.2; GPL-2.0-or-later

Column	Original	Type	Description / unit / levels
ozone	ozone	real	Daily ozone concentration; ppb; ()
radiation	radiation	integer	Solar radiation; langleys; ()
temperature	temperature	integer	Daily maximum temperature; degrees Fahrenheit; ()
wind	wind	real	Wind speed; mph; ()

1.17 portfolio🔗ℹ

100 rows × 2 columns. A simple simulated data set containing 100 returns for each of two assets, X and Y. The data is used to estimate the optimal fraction to invest in each asset to minimize investment risk of the combined portfolio. One can then use the Bootstrap to estimate the standard error of this estimate. names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
x	X	real	Returns for Asset X; #f; ()
y	Y	real	Returns for Asset Y; #f; ()

1.18 prostate🔗ℹ

97 rows × 10 columns. Data to examine the correlation between the level of prostate-specific antigen and a number of clinical measures in men who were about to receive a radical prostatectomy. split is R’s logical train: the 67 training and 30 test observations of the book’s §3.2.1. lweight for subject 32 has the second-edition correction.

Halvorsen, K. B. (2019). ElemStatLearn: Data Sets, Functions and Examples from the Book "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman. R package version 2015.6.26.2. Book: Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning, Second Edition. Springer. https://hastie.su.domains/ElemStatLearn/. Original sources in the bundled upstream documentation.

ElemStatLearn 2015.6.26.2; GPL-2.0-or-later

Column	Original	Type	Description / unit / levels
lcavol	lcavol	real	log cancer volume; #f; ()
lweight	lweight	real	log prostate weight; #f; ()
age	age	integer	Age; years; ()
lbph	lbph	real	log of the amount of benign prostatic hyperplasia; #f; ()
svi	svi	integer	seminal vesicle invasion; #f; ()
lcp	lcp	real	log of capsular penetration; #f; ()
gleason	gleason	integer	Gleason score; #f; ()
pgg45	pgg45	integer	percent of Gleason score 4 or 5; #f; ()
lpsa	lpsa	real	Log of prostate-specific antigen, the response; #f; ()
split	train	categorical	train: the 67 training observations; test: the 30 test observations; #f; (train test)

1.19 publication🔗ℹ

244 rows × 9 columns. Publication times for 244 clinical trials funded by the National Heart, Lung, and Blood Institute. Survival data: time to publication with status 1 = published. mech, an R character column, is categorical with sorted levels. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
posres	posres	integer	Did the trial produce a positive (significant) result? 1=Yes, 0=No.; #f; ()
multi	multi	integer	Did the trial involve multiple centers? 1=Yes, 0=No.; #f; ()
clinend	clinend	integer	Did the trial focus on a clinical endpoint? 1=Yes, 0=No.; #f; ()
mech	mech	categorical	Funding mechanism within National Institute of Health: a qualitative variable.; #f; (Contract K01 K23 P01 P50 R01 R18 R21 R24, K24 R42 R44 RC2 U01 U54)
sampsize	sampsize	integer	Sample size for the trial.; #f; ()
budget	budget	real	Budget of the trial, in millions of dollars.; #f; ()
impact	impact	real	Impact of the trial; this is related to the number of publications.; #f; ()
time	time	real	Time to publication, in months.; months; ()
status	status	integer	Whether or not the trial was published at time: 1=Published, 0=Not yet published.; #f; ()

1.20 sa-heart🔗ℹ

462 rows × 10 columns. A retrospective sample of males in a heart-disease high-risk region of the Western Cape, South Africa. famhist is R’s factor, levels in metadata.

Halvorsen, K. B. (2019). ElemStatLearn: Data Sets, Functions and Examples from the Book "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman. R package version 2015.6.26.2. Book: Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning, Second Edition. Springer. https://hastie.su.domains/ElemStatLearn/. Original sources in the bundled upstream documentation.

ElemStatLearn 2015.6.26.2; GPL-2.0-or-later

Column	Original	Type	Description / unit / levels
sbp	sbp	integer	systolic blood pressure; #f; ()
tobacco	tobacco	real	Cumulative tobacco; kg; ()
ldl	ldl	real	low density lipoprotein cholesterol; #f; ()
adiposity	adiposity	real	Adiposity; #f; ()
famhist	famhist	categorical	Family history of heart disease; #f; (Absent Present)
typea	typea	integer	type-A behavior; #f; ()
obesity	obesity	real	Obesity; #f; ()
alcohol	alcohol	real	current alcohol consumption; #f; ()
age	age	integer	age at onset; #f; ()
chd	chd	integer	Coronary heart disease, the response; #f; ()

1.21 smarket🔗ℹ

1250 rows × 9 columns. Daily percentage returns for the S&P 500 stock index between 2001 and 2005. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
year	Year	integer	The year that the observation was recorded; #f; ()
lag1	Lag1	real	Percentage return for previous day; #f; ()
lag2	Lag2	real	Percentage return for 2 days previous; #f; ()
lag3	Lag3	real	Percentage return for 3 days previous; #f; ()
lag4	Lag4	real	Percentage return for 4 days previous; #f; ()
lag5	Lag5	real	Percentage return for 5 days previous; #f; ()
volume	Volume	real	Volume of shares traded (number of daily shares traded in billions); #f; ()
today	Today	real	Percentage return for today; #f; ()
direction	Direction	categorical	A factor with levels Down and Up indicating whether the market had a positive or negative return on a given day; #f; (Down Up)

1.22 vowel🔗ℹ

990 rows × 12 columns. Speaker independent recognition of the eleven steady state vowels of British English using a specified training set of lpc derived log area ratios. The 528 vowel.train rows, then the 462 vowel.test rows, told apart by split; x1 to x10 are R’s x.1 to x.10.

Halvorsen, K. B. (2019). ElemStatLearn: Data Sets, Functions and Examples from the Book "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman. R package version 2015.6.26.2. Book: Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning, Second Edition. Springer. https://hastie.su.domains/ElemStatLearn/. Original sources in the bundled upstream documentation.

ElemStatLearn 2015.6.26.2; GPL-2.0-or-later

Column	Original	Type	Description / unit / levels
y	y	integer	Vowel class, 1-11; #f; ()
x1 … x10	x.1 … x.10	real	Log area parameter from linear predictive analysis of the frame; #f; ()
split	vowel.train or vowel.test	categorical	train: the 528 vowel.train rows (8 speakers); test: the 462 vowel.test rows (7 other speakers); #f; (train test)

1.23 wage🔗ℹ

3000 rows × 11 columns. Wage and other data for a group of 3000 male workers in the Mid-Atlantic region. The numeric row names are not kept. region keeps all nine R levels though only 2. Middle Atlantic occurs. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
year	year	integer	Year that wage information was recorded; #f; ()
age	age	integer	Age of worker; #f; ()
maritl	maritl	categorical	A factor with levels 1. Never Married 2. Married 3. Widowed 4. Divorced and 5. Separated indicating marital status; #f; (1. Never Married 2. Married 3. Widowed 4. Divorced 5. Separated)
race	race	categorical	A factor with levels 1. White 2. Black 3. Asian and 4. Other indicating race; #f; (1. White 2. Black 3. Asian 4. Other)
education	education	categorical	A factor with levels 1. < HS Grad 2. HS Grad 3. Some College 4. College Grad and 5. Advanced Degree indicating education level; #f; (1. < HS Grad 2. HS Grad 3. Some College 4. College Grad 5. Advanced Degree)
region	region	categorical	Region of the country (mid-atlantic only); #f; (1. New England 2. Middle Atlantic 3. East North Central 4. West North Central 5. South Atlantic 6. East South Central 7. West South Central 8. Mountain 9. Pacific)
jobclass	jobclass	categorical	A factor with levels 1. Industrial and 2. Information indicating type of job; #f; (1. Industrial 2. Information)
health	health	categorical	A factor with levels 1. <=Good and 2. >=Very Good indicating health level of worker; #f; (1. <=Good 2. >=Very Good)
health-ins	health_ins	categorical	A factor with levels 1. Yes and 2. No indicating whether worker has health insurance; #f; (1. Yes 2. No)
logwage	logwage	real	Log of workers wage; #f; ()
wage	wage	real	Workers raw wage; thousands of dollars; ()

1.24 weekly🔗ℹ

1089 rows × 9 columns. Weekly percentage returns for the S&P 500 stock index between 1990 and 2010. R factors rendered as labels with levels in metadata; names normalized to kebab-case.

James, G., Witten, D., Hastie, T. and Tibshirani, R. (2022). ISLR2: Introduction to Statistical Learning, Second Edition. R package version 1.3-2. Book: An Introduction to Statistical Learning with Applications in R, Second Edition (2021), Springer, https://www.statlearning.com. Original sources in the bundled upstream documentation.

ISLR2 1.3-2; GPL-2.0-only

Column	Original	Type	Description / unit / levels
year	Year	integer	The year that the observation was recorded; #f; ()
lag1	Lag1	real	Percentage return for previous week; #f; ()
lag2	Lag2	real	Percentage return for 2 weeks previous; #f; ()
lag3	Lag3	real	Percentage return for 3 weeks previous; #f; ()
lag4	Lag4	real	Percentage return for 4 weeks previous; #f; ()
lag5	Lag5	real	Percentage return for 5 weeks previous; #f; ()
volume	Volume	real	Volume of shares traded (average number of daily shares traded in billions); #f; ()
today	Today	real	Percentage return for this week; #f; ()
direction	Direction	categorical	A factor with levels Down and Up indicating whether the market had a positive or negative return on a given week; #f; (Down Up)

1.1	auto
1.2	bikeshare
1.3	boston
1.4	brain-cancer
1.5	caravan
1.6	carseats
1.7	college
1.8	credit
1.9	default
1.10	fund
1.11	hitters
1.12	khan
1.13	nci60
1.14	nyse
1.15	oj
1.16	ozone
1.17	portfolio
1.18	prostate
1.19	publication
1.20	sa-heart
1.21	smarket
1.22	vowel
1.23	wage
1.24	weekly

1 datasets-islr🔗ℹ

1.1 auto🔗ℹ

1.2 bikeshare🔗ℹ

1.3 boston🔗ℹ

1.4 brain-cancer🔗ℹ

1.5 caravan🔗ℹ

1.6 carseats🔗ℹ

1.7 college🔗ℹ

1.8 credit🔗ℹ

1.9 default🔗ℹ

1.10 fund🔗ℹ

1.11 hitters🔗ℹ

1.12 khan🔗ℹ

1.13 nci60🔗ℹ

1.14 nyse🔗ℹ

1.15 oj🔗ℹ

1.16 ozone🔗ℹ

1.17 portfolio🔗ℹ

1.18 prostate🔗ℹ

1.19 publication🔗ℹ

1.20 sa-heart🔗ℹ

1.21 smarket🔗ℹ

1.22 vowel🔗ℹ

1.23 wage🔗ℹ

1.24 weekly🔗ℹ