Sample Datasets

A collection of datasets from multiple sources to be used for demonstrations in data science courses.

Data Dictionary and/or Description

(last updated: 2020/10/08. Contribution by Gabriel Mantini, @gmantini)

A data dictionary (or data description) is provided for some of the datasets in this repo. Click on the dataset of interest in the list below to learn more about the available attributes.

Click to see data dictionary for:

fuel.csv

See this website: https://www.fueleconomy.gov/feg/ws/

Click to see data dictionary for:

BostonHousing.csv

This dataset contains information collected by the US Census Service concerning housing in the area of Boston Massachusetts. It was obtained from the StatLib archive (http://lib.stat.cmu.edu/datasets/boston). The dataset has 506 cases. Source: The data was originally published by Harrison, D. and Rubinfeld, D.L. `Hedonic prices and the demand for clean air`, J. Environ. Economics & Management, vol.5, 81-102, 1978. There are 14 attributes in each case of the dataset. They are:

Variables	Description
CRIM	Crime rate
ZN	Percentage of residential land zoned for lots over 25,000 ft2
INDUS	Percentage of land occupied by non-retail business
CHAS	Does tract bound Charles River (= 1 if tract bounds river, = 0 otherwise)
NOX	Nitric oxide concentration (parts per 10 million)
RM	Average number of rooms per dwelling
AGE	Percentage of owner-occupied units built prior to 1940
DIS	Weighted distances to five Boston employment centers
RAD	Index of accessibility to radial highways
TAX	Full-value property tax rate per $10,000
PTRATIO	Pupil-to-teacher ratio by town
LSTAT	Percentage of lower status of the population
MEDV	Median value of owner-occupied homes in $1000s
CAT.MEDV	Is median value of owner-occupied homes in tract above $30,000 (CAT.MEDV = 1) or not (CAT.MEDV = 0)

Click to see data dictionary for:

Cereals

Source: DATA ANALYSIS FOR STUDENT LEARNING (DASL)

Variables	Description
Name	Name of cereal
mfr	Manufacturer of cereal where A = American Home Food Products; G = General Mills; K = Kelloggs; N = Nabisco; P = Post; Q = Quaker Oats; R = Ralston Purina
type	cold or hot
calories	calories per serving
protein	grams of protein
fat	grams of fat
sodium	milligrams of sodium
fiber	grams of dietary fiber
carbo	grams of complex carbohydrates
sugars	grams of sugars
potass	milligrams of potassium
vitamins	vitamins and minerals - 0, 25, or 100, indicating the typical percentage of FDA recommended
shelf	display shelf (1, 2, or 3, counting from the floor)
weight	weight in ounces of one serving
cups	number of cups in one serving
rating	a rating of the cereals calculated by Consumer Reports

Click to see data dictionary for:

EastWestAirlinesCluster

East-West Airlines is trying to learn more about its customers. Key issues are their flying patterns, earning and use of frequent flyer rewards, and use of the airline credit card. The task is to identify customer segments via clustering. Source: Based upon real business data; company names have been changed.

Variables	Description
ID#	Unique ID
Balance	Number of miles eligible for award travel
Qual_miles	Number of miles counted as qualifying for Topflight status
cc1_miles	Number of miles earned with freq. flyer credit card in the past 12 months:
cc2_miles	Number of miles earned with Rewards credit card in the past 12 months:
cc3_miles	Number of miles earned with Small Business credit card in the past 12 months:
note: miles bins	1 = under 5,000. 2 = 5,000 - 10,000. 3 = 10,001 - 25,000. 4 = 25,001 - 50,000. 5 = over 50,000
Bonus_miles	Number of miles earned from non-flight bonus transactions in the past 12 months
Bonus_trans	Number of non-flight bonus transactions in the past 12 months
Flight_miles_12mo	Number of flight miles in the past 12 months
Flight_trans_12	Number of flight transactions in the past 12 months
Days_since_enroll	Number of days since Enroll_date
Award?	Dummy variable for Last_award (1=not null, 0=null)

Click to see data dictionary for:

ToyotaCorolla

Variables	Description
Id	Record_ID
Model	Model Description
Price	Offer Price in EUROs
Age_08_04	Age in months as in August 2004
Mfg_Month	Manufacturing month (1-12)
Mfg_Year	Manufacturing Year
KM	Accumulated Kilometers on odometer
Fuel_Type	Fuel Type (Petrol, Diesel, CNG)
HP	Horse Power
Met_Color	Metallic Color? (Yes=1, No=0)
Color	Color (Blue, Red, Grey, Silver, Black, etc.)
Automatic	Automatic ( (Yes=1, No=0)
CC	Cylinder Volume in cubic centimeters
Doors	Number of doors
Cylinders	Number of cylinders
Gears	Number of gear positions
Quarterly_Tax	Quarterly road tax in EUROs
Weight	Weight in Kilograms
Mfr_Guarantee	Within Manufacturer's Guarantee period (Yes=1, No=0)
BOVAG_Guarantee	BOVAG (Dutch dealer network) Guarantee (Yes=1, No=0)
Guarantee_Period	Guarantee period in months
ABS	Anti-Lock Brake System (Yes=1, No=0)
Airbag_1	Driver_Airbag (Yes=1, No=0)
Airbag_2	Passenger Airbag (Yes=1, No=0)
Airco	Airconditioning (Yes=1, No=0)
Automatic_airco	Automatic Airconditioning (Yes=1, No=0)
Boardcomputer	Boardcomputer (Yes=1, No=0)
CD_Player	CD Player (Yes=1, No=0)
Central_Lock	Central Lock (Yes=1, No=0)
Powered_Windows	Powered Windows (Yes=1, No=0)
Power_Steering	Power Steering (Yes=1, No=0)
Radio	Radio (Yes=1, No=0)
Mistlamps	Mistlamps (Yes=1, No=0)
Sport_Model	Sport Model (Yes=1, No=0)
Backseat_Divider	Backseat Divider (Yes=1, No=0)
Metallic_Rim	Metallic Rim (Yes=1, No=0)
Radio_cassette	Radio Cassette (Yes=1, No=0)
Parking_Assistant	Parking assistance system (Yes=1, No=0)
Tow_Bar	Tow Bar (Yes=1, No=0)

Click to see data dictionary for:

Auto

Gas mileage, horsepower, and other information for 392 vehicles.

Variables	Description
mpg	miles per gallon
cylinders	Number of cylinders between 4 and 8
displacement	Engine displacement (cu. inches)
horsepower	Engine horsepower
weight	Vehicle weight (lbs.)
acceleration	Time to accelerate from 0 to 60 mph (sec.)
year	Model year (modulo 100)
origin	Origin of car (1. American, 2. European, 3. Japanese)
name	Vehicle name

Click to see data dictionary for:

allbacks

The allbacks data frame gives measurements on the volume and weight of 15 books, some of which are softback (pb) and some which are hardback (hb). Area of the hardback covers is also included.

Variables	Description
volume	book volumes in cubic centimeters
area	hard board cover areas in square centimeters
weight	book weights in grams
cover	a factor with levels hb hardback, pb paperback

Click to see data dictionary for:

UniversalBank

Variables	Description
ID	Customer ID
Age	Customer's age in completed years
Experience	#years of professional experience
Income	Annual income of the customer ($000)
ZIPCode	Home Address ZIP code
Family	Family size of the customer
CCAvg	Avg. spending on credit cards per month ($000)
Education	Education Level. 1: Undergrad; 2: Graduate; 3: Advanced/Professional
Mortgage	Value of house mortgage if any. ($000)
Personal Loan	Did this customer accept the personal loan offered in the last campaign?
Securities Account	Does the customer have a securities account with the bank?
CD Account	Does the customer have a certificate of deposit (CD) account with the bank?
Online	Does the customer use internet banking facilities?
CreditCard	Does the customer use a credit card issued by UniversalBank?

Click to see data dictionary for:

Utilities

Variables	Description
Company	Company name
Fixed_charge	Fixed-charge coverage ratio (income/debt)
RoR	Percent rate of return on capital
Cost	Cost per KW capacity in place
Load_factor	Annual load factor
Demand_growth	Percent demand growth
Sales	Sales (KWH use per year)
Nuclear	Nuclear Percent nuclear
Fuel_Cost	Fuel_Cost Total fuel costs (cents per KWH)

Click to see data dictionary for:

West Roxbury

Variables	Description
TOTAL VALUE	Total assessed value for property, in thousands of USD
TAX	Tax bill amount based on total assessed value multiplied by the tax rate
LOT SQFT	Total lot size of parcel in square feet
YR BUILT	Year property was built
GROSS AREA	Gross floor area
LIVING AREA	Total living area for residential properties (ft2)
FLOORS	Number of floors
ROOMS	Total number of rooms
BEDROOMS	Total number of bedrooms
FULL BATH	Total number of full baths
HALF BATH	Total number of half baths
KITCHEN	Total number of kitchens
FIREPLACE	Total number of fireplaces
REMODEL	When house was remodeled (Recent/Old/None)

Click to see data dictionary for:

WorldCupMatches

World Cup Matches dataset shows all the results from the matches contested as part of the different editions of the tournament. You can also complement this dataset with the information in `worldcup.csv` that includes statistics for every player that participated in FIFA 2010 worldcup.

Variables	Description
Year	The year in which the match was played
Datetime	The Date on which the match was played along with a 24 hour format time
Stage	The stage at which the match was played
Stadium	Stadium name where the match was held
City	The city name, where the match was played
Home Team Name	Home team country name
Home Team Goals	Total goals scored by the home team by the end of the match
Away Team Goals	Total goals scored by the away team by the end of the match
Away Team Name	Away team country name
Win conditions	Special win condition (if any)
Attendance	Total crowd present at the satdium
Half-time Home Goals	Goals scored by the home team until half time
Half-time Away Goals	Goals scored by the away team until half time
Referee	Name of the first refree
Assistant 1	Name of the first assistant referee (linesman)
Assistant 2	Name of the second assistant referee (linesman)
RoundID	Unique ID of the Round
MatchID	Unique ID of the match
Home Team Initials	Home team country's three letter initials
Away Team Initials	Away team country's three letter initials

Click to see data dictionary for:

NBAchampionsdata and NBArunnerupsdata

Game-by-game team totals for the championship team and runner-up team from every finals game between 1980 and 2018. The 1980 NBA Finals was the first Finals series since the NBA added the three point line.

Variables	Description
Year	Year of competition
Team	Team name
Game	Game of Best-of-7 series
Win	Boolean of win or loss, with win represented as 1
Home	Boolean of Home or Away, with Home represented as 1
MP	Minutes Played
FG	Field Goals (includes both 2-point field goals and 3-point field goals)
FGA	Field Goal Attempts (includes both 2-point field goal attempts and 3-point field goal attempts)
FGP	Field Goal Percentage; the formula is FG / FGA
TP	Time of Possession in minutes
TPA	3-point Field Goal Attempts
TPP	3-point Field Goal Percentage
FT	Free Throws
FTA	Free Throw Attempts
FTP	Free Throw Percentage
ORB	Offensive Rebounds
DRB	Defensive Rebounds
TRB	Total Rebounds
AST	Assists
STL	Steals
BLK	Blocks
TOV	Turnovers
PF	Personal Fouls
PTS	Points

Click to see data dictionary for:

IMDB_movies

Information of 1000 of the most popular movies on IMDB in the last 10 years. The data fields included are: Title, Genre, Description, Director, Actors, Year, Runtime, Rating, Votes, Revenue, Metascore (score of the movie on the _metacritic_ website)

Variables	Description
Rank	IMDb Ranking
Title	Title Name
Genre	Category of Movie
Description	Plot Description
Director	Director Name
Actors	Actor Names
Year	Year Released
Runtime (Minutes)	Duration in minutes
Rating	IMDb Rating
Votes	Number of votes received
Revenue (Millions)	Total Movie Sales
Metascore	Metascore Rating

Click to see data dictionary for:

netflixShows

Understanding the rating distributions of a variety of Netflix shows. Information for 1000 shows is provided including viewer ratings, Motion Picture Association of America film rating system that rates a film's suitability for certain audiences based on its content, release year, and others.

Variables	Description
title	Name of Show
rating	TV Parental Guidelines Rating
ratingLevel	Description of rating content
ratingDescription	Numerical correlation to rating from 10 to 110
release year	Year of show premiere
user rating score	Average rating
user rating size	Sample size of rating

Click to see data dictionary for:

harvardMIT

In 2012, the Massachusetts Institute of Technology (MIT) and Harvard University launched open online courses on edX, a non-profit learning platform co-founded by the two institutions. Data contains information on 290 Harvard and MIT online courses, 250 thousand certifications, 4.5 million participants, and 28 million participant hours on the edX platform since 2012.

Variables	Description
Institution	HarvardX or MITx
Course Number	Course Number Identifier
Launch Date	Date of Release
Course Title	Name of Course
Instructors	Instructor Names
Course Subject	Name of Course
Year	Year 1-4
Honor Code Certificates	Description of Certificate
Participants (Course Content Accessed)	Number of total participants that accessed course content
Audited (> 50% Course Content Accessed)	Number of participants with > 50% Course Content Accessed
Certified	Number of certified completions
% Audited	Percentage audited of total participants
% Certified	Percentage certified of total participants
% Certified of > 50% Course Content Accessed	Percentage certified of the audited amount
% Played Video	Percent of partcipants that played video
% Posted in Forum	Percent of participants that posted in the forums
% Grade Higher Than Zero	Percentage of partcipants that ended with a grade higher than zero
Total Course Hours (Thousands)	Total course hours of participation
Median Hours for Certification	Median hours to complete the course to the point of certification by
Median Age	Average age of a participant
% Male	Percentage of participants that are male
% Female	Percentage of participants that are female
% Bachelor's Degree or Higher	Percentage of participants with a bachelor degree or higher

Click to see data dictionary for:

starbucks

Starbucks is an American coffee chain founded in Seattle. It serves both beverages and food. This dataset includes the nutritional information for Starbucks' food and drink menu items. All nutritional information for drinks are for a 12oz serving size.

Variables	Description
Beverage_category	Type of beverage
Beverage	Beverage name
Beverage_prep	Preparation of beverage, i.e. Soymilk, 2% milk, Venti, Short Nonfat Milk, Solo, Doppio
Calories	Number of calories per serving
Total Fat (g)	Total grams of fat per serving
Trans Fat (g)	Total grams of trans fat per serving
Saturated Fat (g)	Total grams of saturated fat per serving
Sodium (mg)	Total milligrams of sodium per serving
Total Carbohydrates (g)	Total grams of carbs per serving
Cholesterol (mg)	Total milligrams of cholestrol per serving
Dietary Fibre (g)	Total grams of fiber per serving
Sugars (g)	Total grams of sugar per serving
Protein (g)	Total grams of protein per serving
Vitamin A (% DV)	Percentage Vitamin A of standard daily value per serving
Vitamin C (% DV)	Percentage Vitamin C of standard daily value per serving
Calcium (% DV)	Percentage Calcium of standard daily value per serving
Iron (% DV)	Percentage Iron of standard daily value per serving
Caffeine (mg)	Total milligrams of Caffeine per serving

Click to see data dictionary for:

macmenu

This dataset provides a nutrition analysis of every menu item on the US McDonald's menu, including breakfast, beef burgers, chicken and fish sandwiches, fries, salads, soda, coffee and tea, milkshakes, and desserts.

Variables	Description
Category	Categorization of item: Breakfast, Beef & Pork, Chicken & Fish, Beverages, Desserts, Salads, Snacks & Sides, Coffee & Tea, Smoothies & Shakes
Item	Item name from menu
Serving Size	Size of one serving
Calories	Number of calories per serving
Calories from Fat	Number of calories per serving coming from fat
Total Fat	Total grams of fat per serving
Total Fat (% Daily Value)	Percentage fat of standard daily value per serving
Saturated Fat	Total grams of saturated fat per serving
Saturated Fat (% Daily Value)	Percentage saturated fat of standard daily value per serving
Trans Fat	Total grams of trans fat per serving
Cholesterol	Total milligrams of cholestrol per serving
Cholesterol (% Daily Value)	Percenetage cholestrol of standard daily value per serving
Sodium (mg)	Total milligrams of sodium per serving
Sodium (% Daily Value)	Percentage sodium of standard daily value per serving
Carbohydrates	Total grams of carbs per serving
Carbohydrates (% Daily Value)	Percentage carbs of standard daily value per serving
Dietary Fibre (g)	Total grams of fiber per serving
Dietary Fiber (% Daily Value)	Percentage fiber of standard daily value per serving
Sugars (g)	Total grams of sugar per serving
Protein (g)	Total grams of protein per serving
Vitamin A (% DV)	Percentage Vitamin A of standard daily value per serving
Vitamin C (% DV)	Percentage Vitamin C of standard daily value per serving
Calcium (% DV)	Percentage Calcium of standard daily value per serving
Iron (% DV)	Percentage Iron of standard daily value per serving

Click to see data dictionary for:

BreadBasket

The dataset contains more than 6000 transactions from a bakery. Data set containing 15010 observations and more than 6000 transactions from a bakery. The data set contains the following columns: date, time, transaction ID, and item bought.

Variables	Description
Date	Date of transaction
Time	Time of transaction
Transaction	Transaction ID number, in which one transaction is a unique number
Item	Item purchased

Click to see data dictionary for:

disney_movies_total_gross

- Additional dataset to consider: `disney-characters.csv` with Disney characters by hero or villain type.

Information for 579 movies is provided including release date, genre, and total gross.

Variables	Description
movie_title	Name of Movie
release_date	Date of release in Month DD, YYYY
genre	Type of Movie
MPAA_rating	MPAA_rating: G, PG, PG-13, R, NC-17
total_gross	Total gross profit of the movie
inflation_adjusted_gross	Total gross profit of the movie adjusted for inflation

Click to see data dictionary for:

ICUAdmissions

Data from a sample of 200 patients following admission to an adult intensive care unit (ICU)

Variables	Description
ID
Status	Patient status: 0=lived or 1=died
Age	Age in years
Sex	0=male or 1=female
Race	1=white, 2=black, or 3=other
Service	0=medical or 1=surgical
Cancer	Is cancer involved? 0=no or 1=yes
Renal	Is chronic renal failure involved? 0=no or 1=yes
Infection	Is infection involved? 0=no or 1=yes
CPR	Patient gets CPR prior to admission? 0=no or 1=yes
Systolic	Systolic blood pressure (in mm of Hg)
HeartRate	Pulse rate (beats per minute)
Previous	Previous admission to ICU within 6 months? 0=no or 1=yes
Type	Admission type: 0=elective or 1=emergency
Fracture	Fractured bone involved? 0=no or 1=yes
PO2	(Partial oxygen level from blood gases under 60? 0=no or 1=yes
PH	pH from blood gas under 7.25? 0=no or 1=yes
PCO2	Partial carbon dioxide level from blood gas over 45? 0=no or 1=yes
Bicarbonate	Bicarbonate from blood gas under 18? 0=no or 1=yes
Creatinine	Creatinine from blood gas over 2.0? 0=no or 1=yes
Consciousness	Level: 0=conscious, 1=deep stupor, or 2=coma

Click to see data dictionary for:

cost-of-living-2018.csv

Variables	Description
City	Name of City
Cost of Living Index	Cost of Living Index is a relative indicator of consumer goods prices, including groceries, restaurants, transportation and utilities. Does not include accommodation expenses such as rent or mortgage. If a city has a Cost of Living Index of 120, it means Numbeo estimates it is 20% more expensive than New York (excluding rent).
Rent Index	Estimation of prices of renting apartments in the city compared to New York City. If Rent index is 80, Numbeo estimates that price of rents in that city is on an average 20% less than the price in New York.
Cost of Living Plus Rent Index	Estimation of consumer goods prices including rent comparing to New York City
Groceries Index	Estimation of grocery prices in the city compared to New York City
Restaurant Price Index	Comparison of prices of meals and drinks in restaurants and bars compared to NYC
Local Purchasing Power Index	Shows relative purchasing power in buying goods and services in a given city for the average wage in that city. If domestic purchasing power is 40, this means that the inhabitants of that city with the average salary can afford to buy on an average 60% less goods and services than New York City residents with an average salary.

Click to see data dictionary for:

all_billboard_summer_hits

Songs that were part of the Billboard Summer Hits list from 1958 to 2017. Dataset includes music features as provided by the Spotify API, including the "acousticness" and "danceability" of the song, and measurements of valence, tempo, among other audio features. A description of the features can be found at

Variables	Description
danceability	Danceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable.
energy	Energy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy.
key	The estimated overall key of the track. Integers map to pitches using standard Pitch Class notation . E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1.
loudness	The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typical range between -60 and 0 db.
mode	Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1 and minor is 0.
speechiness	Speechiness detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values below 0.33 most likely represent music and other non-speech-like tracks.
acousticness	A confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic.
instrumentalness	Predicts whether a track contains no vocals. “Ooh” and “aah” sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly “vocal”. The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0.
liveness	Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live.
valence	A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).
tempo	The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration.
track_uri	spotify track uri
duration_ms	The duration of the track in milliseconds.
time_signature	An estimated overall time signature of a track. The time signature (meter) is a notational convention to specify how many beats are in each bar (or measure).
key_mode	mode of key
playlist_name	name of playlist
playlist_img	image of playlsit url
track_name	name of track
artist_name	name of artist
album_name	name of album
album_img	image of album url
year	year of release

Click to see data dictionary for:

statewords

This is the data behind the FiveThirtyEight story [_"What America's Governors Are Talking About"_](https://fivethirtyeight.com/features/what-americas-governors-are-talking-about/). Full description of all variables is included in . It contains every one-word phrase that was mentioned in at least 10 speeches and every two- or three-word phrase that was mentioned in at least five speeches after a list of stop-words was removed and the word "healthcare" was replaced with "health care" so that they were not counted as distinct phrases.

Variables	Description
phrase	one, two, or three-word phrase
category	thematic categories for n-grams hand-coded by FiveThirtyEight staff: economy/fiscal issues, education, health care, energy/environment, crime/justice, mental health/substance abuse
d_speeches	number of Democratic speeches containing the n-gram
r_speeches	number of Republican speeches containing the n-gram
total	total number of speeches containing the n-gram
percent_of_d_speeches	percent of the 23 Democratic speeches containing the phrase
percent_of_r_speeches	percent of the 27 Republican speeches containing the phrase
chi2	chi^2 statistic
pval	p-value for chi^2 test

Click to see data dictionary for:

spacex

SpaceX launch data including date, booster version, payload mass, customer, and mission outcome. If you use this dataset, please update it to include the latest information on launches .

Variables	Description
Flight Number	Flight number
Date	Date of launch
Time (UTC)	Time of launch in Coordinated Universal Time
Booster Version	Booster version used
Launch Site	Launch site of flight
Payload	Name of spaceship
Payload Mass (kg)	Weight of payload in kg
Orbit	Orbit classification
Customer	Customer of flight
Mission Outcome	Description of mission outcome
Landing Outcome	Description of landing outcome

Click to see data dictionary for:

Airfares

Variables	Description
S_CODE	Starting airport's code
S_CITY	Starting city
E_CODE	Ending airport's code
E_CITY	Ending city
COUPON	Average number of coupons (a one-coupon flight is a nonstop flight, a two-coupon flight is a one-stop flight, etc.) for that route
NEW	Number of new carriers entering that route between Q3-96 and Q2-97
VACATION	Whether (Yes) or not (No) a vacation route
SW	Whether (Yes) or not (No) Southwest Airlines serves that route
HI	Herfindahl index: measure of market concentration
S_INCOME	Starting city's average personal income
E_INCOME	Ending city's average personal income
S_POP	Starting city's population
E_POP	Ending city's population
SLOT	Whether or not either endpoint airport is slot-controlled (this is a measure of airport congestion)
GATE	Whether or not either endpoint airport has gate constraints (this is another measure of airport congestion)
DISTANCE	Distance between two endpoint airports in miles
PAX	Number of passengers on that route during period of data collection
FARE	Average fare on that route

Click to see data dictionary for:

eBayAuctions

Variables	Description
Category	Category of the auctioned item.
currency	Currency
sellerRating	a rating by eBay, as a function of the number of "good" and "bad" transactions the seller had on eBay
Duration	Number of days the auction lasted (set by seller at auction start)
endDay	Day of week that the auction closed
ClosePrice	Price item sold at (converted into USD)
OpenPrice	Initial price set by the seller (converted into USD)
Competitive?	Whether the auction had a single bid (0) or more (1)

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presidentialElections

Democratic share of the presidential vote, 1932-2016, in each state and the District of Columbia.

Variables	Description
state	Name of state
demVote	percent of the vote for president won by the Democratic candidate
year	integer year in YYYY format
south	TRUE if state is one of the 11 states of the former Confederacy

Click to see data dictionary for:

ufc

Upper Flat Creek forest cruise tree data. These are a subset of the tree measurement data from the Upper Flat Creek unit of the University of Idaho Experimental Forest, which was measured in 1991. The inventory was based on variable radius plots with 6.43 sq. m. per ha. BAF (Basal Area Factor).The forest stand was 121.5 ha. This version of the data omits errors, trees with missing heights, and uncommon species. The four species are Douglas-fir, grand fir, western red cedar, and western larch.

Variables	Description
plot	plot label
tree	tree label
species	species kbd with levels DF, GF , WC, WL
dbh.cm	tree diameter at 1.37m from the ground, measured in centimetres
height.m	tree height measured in meters

Click to see data dictionary for:

trees

These are a subset of the von Guttenberg data, a set of measurements on Norway spruce (Picea abies [L.] Karst) in several different locations and site categories.

Variables	Description
ID	A factor identifying the tree by location, site, and tree number.
Age	The age at which the tree was measured.
Vol	The bole volume of the tree, in cubic dm.

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water

Can Southern California's water supply in future years be predicted from past data? One factor affecting water availability is stream runoff. If runoff could be predicted, engineers, planners and policy makers could do their jobs more efficiently. Multiple linear regression models have been used in this regard This dataset contains 43 years worth of precipitation measurements taken at six sites in the Owens Valley ( labeled APMAM, APSAB, APSLAKE, OPBPC, OPRC, and OPSLAKE), and stream runoff volume at a site near Bishop, California.

Variables	Description
Year	collection year
APMAM	Snowfall in inches measurement site
APSLAKE	Snowfall in inches measurement site
APSAB	Snowfall in inches measurement site
OPBPC	Snowfall in inches measurement site
OPRC	Snowfall in inches measurement site
OPSLAKE	Snowfall in inches measurement site
BSAAM	Stream runoff near Bishop, CA, in acre-feet

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WorldCities

A data frame with 23,018 observations on the following 10 variables.

Variables	Description
code	The ISO (?) city code
name	Name of the city
latitude	location in degrees
longitude	location in degrees
country	Two letter country code
countryRegion	A numerical region
population	Population
regionCode	ISO (?) Code
region	Name of the region
date	Date estimate made

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worldcup

Data on players from the 2010 World Cup

Variables	Description
Position	a factor with levels Defender Forward Goalkeeper Midfielder
Time	Time played in minutes
Shots	Number of shots attempted
Passes	Number of passes made
Tackles	Number of tackles made
Saves	Number of saves made

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vehicles

Variables	Description
id	Unique EPA identifier
make	Manufacturer
model	Model name
year	Model year
class	EPA vehicles size class, http://www.fueleconomy.gov/feg/ws/wsData.shtml#VClass
trans	Transmission
drive	Drive Train
cyl	Number of cylinders
displ	Engine displacement, in litres
fuel	Fuel type
hwy	Highway fuel economy, in mpg
cty	City fuel economy, in mpg

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Credit

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.

Variables	Description
ID	Identification
Income	Income in $10,000's
Limit	Credit limit
Rating	Credit rating
Cards	Number of credit cards
Age	Age in years
Education	Number of years in education
Gender	A factor with levels Male and Female
Student	A factor with levels No and Yes indicating whether the individual was a student
Married	A factor with levels No and Yes indicating whether the individual was married
Ethnicity	A factor with levels African American, Asian, and Caucasian indicating the individual's ethnicity
Balance	Average credit card balance in $

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AllCountries

Data on the countries of the world. Most data from 2008 to avoid many missing values in more recent years. Data collected from worldbank.org.

Variables	Description
Country	Name of the country
Code	Three letter country code
LandArea	Size in sq. kilometers
Population	Population in millions
Energy	Energy usage (kilotons of oil)
Rural	Percentage of population living in rural areas
Military	Percentage of government expenditures directed toward the military
Health	Percentage of government expenditures directed towards healthcare
HIV	Percentage of the population with HIV
Internet	Percentage of the population with access to the internet
Developed	Categories for kilowatt hours per capita, 1= under 2500, 2 = 2500 to 5000, 3 = over 5000
BirthRate	Births per 1000 people
ElderlyPop	Percentage of the population at least 65 years old
LifeExpectancy	Average life expectancy (years)
CO2	CO2 emissions (metric tons per capita)
GDP	Gross Domestic Prodcut (per capita)
Cell	Cell phone subscriptions (per 100 people)
Electricity	Electric power consumption (kWh per capita)

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CommuteAtlanta

Commute times and distance for a sample of 500 people in Atlanta. Data were extracted respondents in the Atlanta metropolitan area. They include only cases where the respondent worked somewhere other than home. Sample chosen using DataFerret at http://www.thedataweb.org/index.html

Variables	Description
City	Atlanta
Age	Age of the respondent (in years)
Distance	Commute distance (in miles)
Time	Commute time (in minutes)
Sex	F or M

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CommuteStLouis

Commute times and distance for a sample of 500 people in St. Louis. Data were extracted respondents in the St. Louis metropolitan area. They include only cases where the respondent worked somewhere other than home. Sample chosen using DataFerret at http://www.thedataweb.org/index.html

Variables	Description
City	St. Louis
Age	Age of the respondent (in years)
Distance	Commute distance (in miles)
Time	Commute time (in minutes)
Sex	F or M

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FloridaLakes

Water quality for a sample of lakes in Florida

Variables	Description
ID	An identifying number for each lake
Lake	Name of the lake
Alkalinity	Concentration of calcium carbonate (in mg/L)
pH	Acidity
Calcium	Amount of calcium in water
Chlorophyll	Amount of chlorophyll in water
AvgMercury	Average mercury level for a sample of fish (large mouth bass) from each lake
NumSamples	Number of fish sampled at each lake
MinMercury	Minimum mercury level in a sampled fish
MaxMercury	Maximum mercury level in a sampled fish
ThreeYrStdMercury	Adjusted mercury level to account for the age of the fish
AgeData	Mean age of fish in each sample

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HollywoodMovies

Information for 136 movies released from Hollywood in 2011.

Variables	Description
Movie	Title of movie
LeadStudio	Studio that released the movie
RottenTomatoes	Rotten Tomatoes rating (reviewers)
AudienceScore	Audience rating (via Rotten Tomatoes)
Story	General theme - one of 21 themes
Genre	Type of Movie: Action, Adventure, Animation, Comedy, Drama, Fantasy, Horror, Romance, or Thriller
TheatersOpenWeek	Number of screens for opening weekend
BOAverageOpenWeek	Average box office income per theater - opening weekend
DomesticGross	Gross income for domestic viewers (in millions)
ForeignGross	Gross income for foreign viewers (in millions)
WorldGross	Gross income for all viewers (in millions)
Budget	Production budget (in millions)
Profitability	WorldGross/Budget
OpeningWeekend	Opening weekend gross (in millions)

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MiamiHeat

Game log data for all the Miami Heat basketball team in 2010-11. Information from online boxscores for all 82 regular season games played by the Miami Heat during the 2010-11 regular season.

Variables	Description
Game	ID number for each game
Date	Data the game was played
Location	Away or Home
Opp	Opponent team
Win	Game result: L or W
FG	Field goals made
FGA	Field goals attempted
FG3	Three-point field goals made
FG3A	Three-point field goals attempted
FT	Free throws made
FTA	Free throws attempted
Rebounds	Total rebounds
OffReb	Offensive rebounds
Assists	Number of assists
Steals	Number of steals
Blocks	Number of shots blocked
Turnovers	Number of turnovers
Fouls	Number of fouls
Points	Number of points scored
OppFG	Opponent's field goals made
OppFGA	Opponent's Field goals attempted
OppFG3	Opponent's Three-point field goals made
OppFG3A	Opponent's Three-point field goals attempted
OppFT	Opponent's Free throws made
OppFTA	Opponent's Free throws attempted
OppOffReb	Opponent's Offensive rebounds
OppRebounds	Opponent's Total rebounds
OppAssists	Opponent's assists
OppSteals	Opponent's steals
OppBlocks	Opponent's shot blocked
OppTurnovers	Opponent's turnovers
OppFouls	Opponent's fouls
OppPoints	Opponent's points scored

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NutritionStudy

Variables related to nutrition and health for 315 individuals.

Variables	Description
ID	ID number for each subject in this sample
Age	Subject's age (in years)
Smoke	a factor with levels No Yes
Quetelet	Weight/(Height^2)
Vitamin	Vitamin use: 1 = Regulary, 2 = Occasionally, or 3 = No
Calories	Number of calories consumer per day
Fat	Grams of fat consumed per day
Fiber	Grams of fiber consumed per day
Alcohol	Number of alcoholic drinks consumed per week
Cholesterol	Cholesterol consumed (mg per day)
BetaDiet	Dietary beta-carotene consumed (mcg per day)
RetinolDiet	Dietary retinol consumed (mcg per day)
BetaPlasma	Plasma beta-carotene (ng/ml)
RetinolPlasma	Plasma retinol (ng/ml)
Gender	Coded as Female or Male
VitaminUse	Coded as No Occasional Regular
PriorSmoke	Smoking status: 1 = Never, 2 = Former, or 3 = Current

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RestaurantTips

Tip data from the First Crush Bistro in Potsdam, NY. Restaurant bills were collected over a two week period that was believed to provide a good sample of customers. Data recorded from 157 bills with 7 variables.

Variables	Description
Bill	Size of the bill (in dollars)
Tip	Size of the tip (in dollars)
Credit	Paid with a credit card? n or y
Guests	Number of people in the group
Day	Day of the week: m=Monday, t = Tuesday, w = Wednesday, th = Thursday, or f = Friday
Server	Code for waiter/waitress: A, B, or C
PctTip	Tip as a percentage of the bill

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SleepStudy

Data from a study of sleep patterns for college students. Obtained from sample of students who did skills tests to measure cognitive function, completed a survery that asked many questions about attitudes and habits, and kept a sleep diary to record time and quality of sleep over a two week period.

Variables	Description
Gender	1 = male, 0 = female
ClassYear	Year in school, 1 = first year, ..., 4 = senior
LarkOwl	Early riser of night owl? Lark, Neither, or Owl
NumEarlyClass	Number of classes per week before 9am
EarlyClass	Indicator for any early classes
GPA	Grade point average (0-4 scale)
ClassesMissed	Number of classes missed in a semester
CognitionZscore	Z-score on a test of cognitive skills
PoorSleepQuality	Measure of sleep quality (higher values are poorer sleep)
DepressionScore	Measure of degree of depression
AnxietyScore	Measure of amount of anxiety
StressScore	Measure amount of stress
DepressionStatus	Coded depression score: normal, moderate, or severe
AnxietyStatus	Coded anxiety score: normal, moderate, or severe
Stress	Coded stress score: normal or high
DASScore	Combined score for depression, anxiety and stress
Happiness	Measure of degree of happiness
AlcoholUse	Self-reported: Abstain, Light, Moderate, or Heavy
Drinks	Number of alcoholic drinks per week
WeekdayBed	Average wqeekday bedtime (24.0 = midnight)
WeekdayRise	Average weekday rise time (8.0 = 8am)
WeekdaySleep	Average hours of sleep on weekdays
WeekendBed	Average weekend bedtime (24.0 = midnight)
WeekendRise	Average weekend rise time (8.0 = 8am)
WeekendSleep	Average weekend bedtime (24.0 = midnight)
AverageSleep	Average hours of sleep for all days
AllNighter	Had an all-nighter this semester? 1 = yes, 0 = no

See more details at https://cran.r-project.org/web/packages/Lock5Data/index.html

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HomesForSale

Data on homes for sale in four states, selected from zillow.com in 2010.

Variables	Description
State	Location of the home: CA NJ NY PA
Price	Asking price (in $1,000's)
Size	Area of all rooms (in 1,000's sq. ft.)
Beds	Number of bedrooms
Baths	Number of bathrooms