Data Set Descriptions

2011 Home Sales

Suppose an association of real estate professionals has reported home sales for 2011. The table contains the current sales by region and the inventory for existing homes.

Rows: 104

Columns: 4

Variables:

Sales Price:

The price that the home sold at

Region:

Region of the United States. NE= Northeast, MW= Midwest, S= South, W=West

Home Type:

The type of home described by ownership of the property and land surrounding the property

Inventory:

The amount of money that all the items inside the house are currently valued at

2016 Jockey Data

2016 data for jockeys as North American Thoroughbred Racing Starters.

Rows: 1,444

Columns: 11

Variables:

Jockey Name:

Name of the jockey

Starts:

Number of starts in races by the jockey

1st:

Number of times that the jockey won first place

2nd:

Number of times that the jockey won second place

3rd:

Number of times that the jockey won third place

Total $:

Total amount of money won by the jockey for the year

Per Start $:

Amount of money that the jockey makes per start

Win %:

The percentage of time that the jockey wins the race

Top 3:

The total number of times that the jockey wins first, second, or third

Top 3%:

Percentage of times that the jockey wins first, second, or third from their total number of starts

Racing Year:

Year in which these jockeys’ statistics are applicable

Source

http://www.equibase.com/

2016 Trainer Data

2016 data for trainers as North American Thoroughbred Racing Starters.

Rows: 5,446

Columns: 11

Variables:

Trainer Name:

Name of the trainer

Starts:

Number of starts in races by the trainer

Starters:

The amount of times the trainer was a starter

1st:

Number of times that the trainer won first place

2nd:

Number of times that the trainer won second place

3rd:

Number of times that the trainer won third place

Total $:

Total amount of money won by the trainer for the year

Per Start $:

Amount of money that the trainer makes per start

Win %:

The percentage of time that the trainer wins the race

Top 3%:

Percentage of times that the trainer wins first, second, or third from their total number of starts

Racing Date:

Year in which these trainers’ statistics are applicable

Source

http://www.equibase.com/

2017 Jockey Data

2017 data for jockeys as North American Thoroughbred Racing Starters.

Rows: 1,418

Columns: 11

Variables:

Jockey Name:

Name of the jockey

Starts:

Number of starts in races by the jockey

1st:

Number of times that the jockey won first place

2nd:

Number of times that the jockey won second place

3rd:

Number of times that the jockey won third place

Total $:

Total amount of money won by the jockey for the year

Per Start $:

Amount of money that the jockey makes per start

Win %:

The percentage of time that the jockey wins the race

Top 3:

The total number of times that the jockey wins first, second, or third

Top 3%:

Percentage of times that the jockey wins first, second, or third from their total number of starts

Racing Year:

Year in which these jockeys’ statistics are applicable

Source

http://www.equibase.com/

2017 Trainer Data

2017 data for trainers as North American Thoroughbred Racing Starters.

Rows: 5,266

Columns: 11

Variables:

Trainer Name:

Name of the trainer

Starts:

Number of starts in races by the trainer

Starters:

The amount of times the trainer was a starter

1st:

Number of times that the trainer won first place

2nd:

Number of times that the trainer won second place

3rd:

Number of times that the trainer won third place

Total $:

Total amount of money won by the trainer for the year

Per Start $:

Amount of money that the trainer makes per start

Win %:

The percentage of time that the trainer wins the race

Top 3%:

Percentage of times that the trainer wins first, second, or third from their total number of starts

Racing Date:

Year in which these trainers’ statistics are applicable

Source

http://www.equibase.com/

Amazon Stock Price

Data regarding the price per share of Amazon stock from its initial public offering (IPO) in May 1997 to September 2017.

Rows: 5,121

Columns: 7

Variables:

Date:

Date of observation

Open:

Price per share when the stock market opened on the specified date

High:

The maximum price per share reached on the specified date

Low:

The minimum price per share reached on the specified date

Close:

Price per share when the stock market closed on the specified date

Log Close:

The log transformed value of the close variable

Volume:

The number of shares that changed hands on the specified date

Source

http://www.macrotrends.net/stocks/charts/AMZN/prices/amazon-inc-stock-price-history

License

https://opendatacommons.org/licenses/odbl/1.0/

Beers and Breweries

Information about several canned beers brewed in the U.S. and the breweries where they were brewed.

Rows: 2,397

Columns: 4

Variables:

id:

The ID number of each individual beer

abv:

Alcohol by volume

ibu:

International Bitterness Units

name:

Name of the beer

style:

Style of the beer

ounces:

Volume of beer in the can, in ounces

brewery id:

The ID number of each brewery brewery

name:

Name of the brewery that the specified beer was brewed

city:

City where the brewery is located

state:

State where the brewery is located

Source

https://www.kaggle.com/nickhould/craft-cans

Bill Length

Data compiled by Dr. Thomas W. Schoener on bill size ratios for hundreds of different bird species.

Rows: 410

Columns: 2

Variables:

Species:

Species name

Bill Ratio:

Ratio of the largest to smallest bill in each population

Source

https://www.seattlecentral.edu/qelp/sets/034/034.html

California DDS Expenditures

Data regarding the distribution of expenditures for the California Department of Developmental Services (DDS).

Rows: 1,000

Columns: 6

Variables:

Id:

ID number of the consumer

Age Group:

The age range the consumer falls into(6 pre - defined Age Groups)

Age:

The age of the consumer

Gender:

The gender of the consumer

Expenditures:

The amount of funding allocated to the consumer from the DDS

Ethnicity:

The ethnicity of the consumer

Source

http://www.amstat.org/publications/jse/v22n1/mickel/paradox_data.csv

Campus Crime

Data regarding campus crime.

Rows: 20

Columns: 4

Variables:

Number of Crimes:

The number of crimes as applicable to the school.

Number of Police:

The number of police officers at the school.

Total Enrollment:

Total number of students enrolled at the school.

Private school:

If yes =1 and no=0.

Source

https://ope.ed.gov/campussafety/#/

Cereal Data

Nutritional data for 77 different breakfast cereals.
Note that this is a real data set and contains missing data or cells for some of the variables.

Rows: 77

Columns: 15

Variables:

Name:

Name of cereal

mfr:

Manufacturer of cereal

A:

American Home Food Products;

G:

General Mills

K:

Kelloggs

N:

Nabisco

P:

Post

Q:

Quaker Oats

R:

Ralston

Purinatype:

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

recommendedshelf:

display shelf (1, 2, or 3, counting from the floor)

weight:

weight in ounces of one serving

cups:

number of cups in one serving

Source

https://www.kaggle.com/jeandsantos/breakfast-cereals-data-analysis-and-clustering/data

Carbon Dioxide Emissions

Information regarding the CO2 emissions in thousands of metric tons from nearly every country for the years 1960—2014.

Rows: 54

Columns: 266

Variables:

Year:

The year the CO2 emissions were recorded

Country Name:

The name of the country being measured

Source

http://data.un.org/Data.aspx?q=emissions&d=WDI&f=Indicator_Code%3aEN.ATM.CO2E.PC

Employee Satisfaction

Data regarding the satisfaction of employees at a company.

Rows: 15,000

Columns: 12

Variables:

employee_id:

The ID number associated with the individual employee

satisfaction_level:

How satisfied the employee is in their position (scale of 0 to 1)

last_evaluation_score:

How management rated employee performance during the last evaluation (scale of 0 to 1)

number_of_projects:

The number of projects an employee is currently working on

average_monthly_hours:

The average number of hours the employee works in a month

years_spent_at_company:

The number of years the employee has worked at the company

work_accident:

A binary variable that indicates whether the employee experienced an accident at work

left_company:

A binary variable that indicates whether an employee left the company

promotion_in_last_5_years:

A binary variable that indicates whether an employee received a promotion in the last 5 years

department:

The department that the employee works in

salary:

The level of the employee’ s salary(low, medium, high)

salary_range:

The dollar range for the salary levels

Source

https://www.kaggle.com/ludobenistant/hr-analytics

License

https://creativecommons.org/licenses/by-sa/4.0/legalcode

Exchange-Traded Funds

Data for 50 Exchange-Traded Funds (ETF) and their earning factors.

Rows: 50

Columns: 4

Variables:

ETF:

The ID number for the ETF

Share Price ($):

The cost of one share

Divided Per Share ($):

Payment that the company will give to shareholders for each share they possess

Dividend Yield (%):

The percentage of the share cost that the shareholder receives (dividend per share/ share price)

Factors Affecting HS Completion Rate

2013—2014 U.S. State data regarding high school completion rates, average teacher salary, student-to-teacher ration, and state expenditure per student.

Rows: 50

Columns: 5

Variables:

State:

State in the United States

Completion Rate:

The 4-year ACGR is the number of students who graduate in 4 years with a regular high school diploma divided by the number of students who form the adjusted cohort for the graduating class. This number has been rounded to the nearest whole number.

Average Teacher's Salary ($):

The average salary of teachers in the state for the academic year 2013-2014.

Pupil/Teacher Ratio:

The ratio of total number of students to total number of teachers for the academic year 2013-2014.

Expenditure per Student ($):

The amount of money spent per student during the academic year 2013-2014.

Source

https://nces.ed.gov/ccd/tables/ACGR_RE_and_characteristics_2013-14.asp

Farmland Data

Assorted farmland available for purchase from 2013—2018.

Rows: 496

Columns: 7

Variables:

State:

U.S. state

County:

County where farmland is available

Size of Land:

The amount of land available (in acres)

Sale Price:

Price that the farmland is listed at

Price per Acre (approx.):

The total price of the farmland divided by the number of acres

Land Details:

A description of the available farmland including information such as the quality of the soil and the number of tillable acres

Date:

Month and year that the farmland was available for purchase

Source

https://nces.ed.gov/ccd/tables/ACGR_RE_and_characteristics_2013-14.asp

Finch By Year Data

Averages by year and species for data collected on Darwin's finches on Daphe Major Island.

Rows: 80

Columns: 5

Variables:

Year

Species:

Species of finch, genus is Geospiza

Beak Length:

Beak length, in millimeters

Beak Depth:

Beak depth, in millimeters

Beak Width:

beak width, in millimeters

Finch Data

A sample of data collected on Darwin's finches on Daphe Major Island.

Rows: 100

Columns: 11

Variables:

Band:

Refers to an individual's identity, more specifically, the number on a metal leg band it was given

Species:

Species name

Sex:

Male, female, or unknown. The reason for the "unknown" category is that males start their lives looking like females. After one or more years they molt into a plumage with some black feathering that indicates they are males.

First adult year:

The year after the individual hatched from an egg

Last Year:

The last year of that individual's life

Weight (g):

Weight, in grams

Wing (mm):

Wing length, in millimeters

Tarsus (mm):

Tarsus length (a part of the leg), in millimeters

Beak Length (mm):

Beak length, in millimeters

Beak Depth (mm):

Beak depth, in millimeters

Beak Width (mm):

Beak width, in millimeters

High School Completion and Crime Rate

Data regarding high school completion and crime rates across U.S. states in 2014.

Rows: 50

Columns: 5

Variables:

State:

U.S. state

High School Completion Rate (Adjusted Cohort Graduation Rate):

The 4-year ACGR is the number of students who graduate in 4 years with a regular high school diploma divided by the number of students who form the adjusted cohort for the graduating class.” This number has been rounded to the nearest whole number.

Crime Rate (per 100,000):

Rate of violent and property crimes per 100,000 people

Violent crimes (per 100,000):

Rate of violent crimes (murder, rape, robbery, aggravated assault) per 100,000 people

Property crimes (per 100,000):

Rate of property crimes per 100,000

Source

https://www.ucr.fbi.gov/crime-in-the-u.s/2014; https://nces.ed.gov/ccd/

Housefly Wing Lengths

A data set regarding the distribution of housefly wing lengths.

Rows: 100

Columns: 1

Variables:

Length:

wing length (X.1mm)

Source

https://www.seattlecentral.edu/qelp/sets/057/057.html

Miles Per Gallon

Data on vehicle fuel economy for model years 1984—2019.

Rows: 38,693

Columns: 11

Variables:

city:

city miles per gallon

cylinders:

number of cylinders in engine

displ:

engine displacement in liters

drive:

drive axle type

fuelType:

type of fuel

highway:

highway miles per gallon

make:

manufacturer

model:

model name

trans:

type of transmission

VClass:

vehicle size class

year:

model year

Source

https://www.seattlecentral.edu/qelp/sets/057/057.html

Moneyball

A data set containing selected statistics for Major League Baseball teams 1962—2012.

Rows: 1,232

Columns: 16

Variables:

Team:

The team name abbreviation

League:

The league of the MLB that the team played in

Year:

The year associated with the statistics

RS:

Runs scored

RA:

Runs Allowed

RD:

Run Differential

W:

Number of wins

OBP:

On-base percentage

SLG:

Slugging percentage

BA:

Batting Average

Playoffs:

A binary variable that indicates whether or not a team made the playoffs

RankSeason:

Team ranking at the end of the regular season

RankPlayoffs:

Team ranking at the end of the post-season

G:

Number of games played

OOBP:

Opponent on-base percentage

OSLG:

Opponent slugging percentage

Source

www.baseball-reference.com

Mount Pleasant Real Estate

Information about properties for sale in three subdivisions of Mount Pleasant, South Carolina, in the year 2017.

Rows: 245

Columns: 24

Variables:

ID:

The property ID number

List Price:

The price the owner is selling the property for

Duplex:

Whether the property is a duplex or not

Bedrooms:

The number of bedrooms

Baths – Total:

Total number of bathrooms

Baths – Full:

Number of full bathrooms

Baths – Half:

Number of half bathrooms

Stories:

Number of stories

Subdivision:

The subdivision the property is in

Square Footage:

The estimated floor area inside the house

Year Built:

The year the house was constructed

Acreage:

The size of the lot

New Owned:

Whether the house has been lived in previously

House Style:

The type of property(traditional, condo, ranch, etc.)

Covered Parking Spots:

The number of covered parking spots included with the property

Misc.Exterior:

Miscellaneous exterior features

Has Pool:

Whether the property has a private pool or not

Has Dock:

Whether the property has a private dock or not

Fenced Yard:

Whether the property has a fenced - in yard or not

Screened Porch:

Whether the property has a screened porch or not

Amenities:

Amenities included with the property

Golf Course:

Whether the property is located on a golf course or not

Fireplace:

Whether the property has a fireplace or not

Number of Fireplaces:

The number of fireplaces

OECD Better Life Index 2016

Data gathered by the Organisation for Economic Co-operation and Development (OECD) regarding the economic strength and well-being of its 35 member countries as well as 3 prominent non-member countries (Brazil, Russia, and South Africa).

Rows: 38

Columns: 25

Variables:

country:

Name of the country

percent_of_houses_no_facilities:

Percent of households in the country that lack basic facilities

percent_of_income_spent_on_housing:

Average percent of household income spent on housing

rooms_per_person:

The average number of rooms per person residing in a household

household_net_adj_disposable_income:

The amount a household has to spend after income taxes

household_net_financial_wealth:

The net worth of a household (assets minus liabilities)

percent_labor_market_insecurity:

Expected earnings lost, measured as the percentage of the previous earnings, associated with unemployment.

employment_rate:

Percentage of working age population (15 to 64) that is employed

long_term_unemployment_rate:

Percentage of working age population (15 to 64) that has been unemployed for longer than 27 weeks.

personal_earning_per_year:

The total amount of income earned annually.

quality_of_support:

The quality of the social support network (friends, family, etc.)

percent_of_pop_finish_highschool:

The percentage of the population between the ages of 25 and 64 that holds at least one upper secondary degree

Source

stats.oecd.org

Population Count 2010 and 2016

U.S. census data regarding the population in each state and the population change from 2010—2016.

Rows: 51

Columns: 5

Variables:

Geographic Area:

All 50 states and the Distric of Columbia

April 1, 2010:

Population estimate for each state in 2010

July 1, 2016:

Population estimate for each state in 2016

Number:

Numerical value for the population change from 2010 to 2016 for each state

Percent:

Percent change from 2010 to 2016 for each state

Source

https://www.census.gov/data/tables/2016/demo/popest/state-total.html#ds

San Francisco Salaries 2014

A data set that provides employment information regarding employees in the San Francisco area for the year 2014.

Rows: 22,334

Columns: 13

Variables:

Id:

The ID number assigned to the employee

EmployeeName:

The name of the employee

JobTitle:

The title of the position that the employee holds

BasePay:

The base annual salary (in dollars) that the employee received

OvertimePay:

The amount (in dollars) the employee received in overtime pay

OtherPay:

The amount (in dollars) the employee received in payment from bonuses and other pay

Benefits:

The amount (in dollars) the employee received in the form of companybenefits

TotalPay:

The total amount (in dollars) the employee received throughout theyear not including benefits

TotalPayBenefits:

The total amount (in dollars) the employee receivedthroughout the year including benefits

LogTotalPayBenefits:

The log transformation of the TotalPayBenefits variable

Year:

The year the data was recorded

Agency:

The location the data was gathered from

Status:

Full-time or part-time

Source

https://www.kaggle.com/kaggle/sf-salaries

License

https://creativecommons.org/publicdomain/zero/1.0/legalcode

SAT Scores and Graduating GPA

A data set comparing students’ predicted college GPAs from their SAT scores to their actual college GPAs.

Rows: 30

Columns: 8

Variables:

Student:

The ID Number associated with each student

SAT Verbal:

SAT Score earned on the Verbal portion of the test

SAT Math:

SAT score earned on the Math portion of the test

SAT Total:

Combined score earned on both Verbal and Math portion of the test

College GPA:

Actual college GPA

Predicted GPA:

The college GPA predicted considering the student’s SAT score

Error:

The difference between the actual and predicted GPAs

Error Squared:

The square of this error

Shop Data

This data set considers a sample of shops from a major city and compares the average amount of return the store receives from the number of independent customers from different households.

Rows: 30

Columns: 4

Variables:

Shop (The ID number associated with the individual shops)

Location

Annual Return

Number of Households

SNAP

Data related to the Supplemental Nutrition Assistance Program (SNAP).

Rows: 40

Columns: 3

Variables:

Shop:

Shop ID Number

Location:

Type of location in the city or surrounding area that the shop is located in

Annual Return (Thousands of Dollars):

The profit that the store receives each year

Number of Households (Thousands):

The number of customers that buy from the shop represented by the number of independent households

Stock Comparison Data

Information on the closing prices of four stocks—Amazon, Starbucks, Coca-Cola, and S&P 500—over the years 2000—2017.

Rows: 4,528

Columns: 16

Variables:

date

close:

the closing price of the stock on that day

Price Change:

difference in closing price compared to the day before

Return:

percent change in closing price compared to the day before

Source

https://www.macrotrends.net/stocks/charts

Student Life

Self-reported health and lifestyle data gathered from 30 college freshmen and sophomores.

Rows: 30

Columns: 5

Variables:

Sleep:

Reported hours of sleep on a typical weekday

Studying:

Reported hours of studying on a typical weekday

Calories:

Reported calories consumed on a typical weekday

Exercise:

Reported hours of exercise on a typical weekday

Social Media:

Reported hours spent on social media on a typical weekday

Super Bowl Stats

Information on football team statistics for every Super Bowl played from the years 1967 to 2017.

Rows: 55

Columns: 38

Variables:

Date:

The date the game was played on

SB:

The roman numeral denoting the name and number of the The Big Game

Winner:

The team that won the The Big Game that year

Winner_Pts:

The amount of points the winning team scored in the game

Winner_First Downs:

The number of first downs the winning team earned during the game

Winner_Rush Attempts:

The amount of times the winning team tried to run the footballduring the game

Winner_Rushing Yards:

The number of yards the winning team gained by running the football during the game

Winner_Rushing TDs:

The number of touchdowns the winning team scored by running the football during the game

Winner_Fumbles:

The amount of times the winning team fumbled the football

Winner_Fumbles Lost:

The amount of times the winning team fumbled the football and turned possession over to their opponent

Winner_Pass Attempts:

The amount of times the winning team tried to pass the football during the game

Winner_PassesCompleted:

The amount of times the winning team passed the ball and made a successful catch

Winner_Passing Yards:

The number of yards the winning team gained by passing the football during the game

Winner_Passing TDs:

The number of touchdowns the winning team scored by passing the football during the game

Winner_Interceptions:

The amount of times the winning team intercepted a pass attempt made by their opponent

Winner_Total Yards:

The total number of yards the winning team gained by either rushing or passing the football during the game

Winner_Time ofPossession:

The amount of time the game clock ran when the winning team had possession of the football

Loser:

The team that lost the Super Bowl that year

Loser_Pts:

The amount of points the losing team scored in the game

Loser_First Downs:

The number of first downs the losing team earned during the game

Loser_Rush Attempts:

The amount of times the losing team tried to run the football during the game

Loser_Rushing Yards:

The number of yards the losing team gained by running the football during the game

Loser_Rushing TDs:

The number of touchdowns the losing team scored by running the football during the game

Loser_Fumbles:

The amount of times the losing team fumbled the football

Loser_Fumbles Lost:

The amount of times the losing team fumbled the football and turned possession over to their opponent

Loser_Pass Attempts:

The amount of times the losing team tried to pass the football during the game

Loser_Passes Completed:

The amount of times the losing team passed the ball and made a successful catch

Loser_Passing Yards:

The number of yards the losing team gained by passing the football during the game

Loser_Passing TDs:

The number of touchdowns the losing team scored by passing the football during the game

Loser_Interceptions:

The amount of times the losing team intercepted a pass attempt made by their opponent

Loser_Total Yards:

The total number of yards the losing team gained by either rushing or passing the football during the game

Loser_Time ofPossession:

The amount of time the game clock ran when the losing team had possession of the football

MVP:

The player that was voted the Super Bowl MVP

Stadium:

The stadium the game was played in

City:

The city the game was played in

State:

The state the game was played in

Coin Toss Result:

Whether the coin toss resulted in heads or tails

Coin Toss Winner:

The team that won the coin toss

Source

https://www.pro-football-reference.com/

Tuition

Comparison of tuition rates for 400 colleges and universities for the 2015—2016 school year.

Rows: 400

Columns: 4

Variables:

Name:

Name of college or university with city and state

In-state tuition:

cost to attend institution as a resident of the state the school is located

Out-of-state tuition:

cost to attend institution as a non-resident of the state the school is located

Type:

public (primarily funded by the state government) or private (primarily not funded by the state government)

Source

https://www.collegetuitioncompare.com/

U.S. County Data

A data set containing information regarding nearly every county in the United States for 2010.

Rows: 3,143

Columns: 94

Variables:

fips:

The FIPS county code

name_16:

The name of the county

County:

The county name and the state it is in

Less.Than.High.School:

The percentage of the population 18-years old or older with less than a high school education

At.Least.High.School.Diploma:

The percentage of the population 18-years old or older with at least a high school diploma or GED

At.Least.Bachelor.s.Degree:

The percentage of the population 25-years old or older with at least a Bachelor’s degree

Graduate.Degree:

The percentage of the population 25-years old or older with at least a Master’s degree

School.Enrollment:

School enrollment percentage for the population 3-years old and older

Median.Earnings.2010.dollars:

The median annual income for an individual normalized to the value of a dollar in 2010

White.not.Latino.Population:

The percentage of the county population that identifies as Caucasian with no Latino heritage

African.American.Population:

The percentage of the county population that identifies as African American

Native.American.Population:

The percentage of the county population that identifies as Native American

Asian.American.Population:

The percentage of the county population that identifies as Asian American

Population.some.other.race.or.races:

The percentage of the county population that identifies with another ethnicity or multiples ethnicities

Latino.Population:

The percentage of the county population that identifies as Latino

Children.Under.6.Living.in.Poverty:

The percentage of children under the age of 6 that are living in poverty

Adult.65.and.Older.Living.in.Poverty:

The percentage of adults aged 65 and older that are living in poverty

Total.Population:

The total county population

Source

Kirkegaard, E. O. W. (2017, April 7). Inequality across US counties: an S factor analysis. Retrieved from osf.io/cknjr

U.S. Gas Price

Data set containing the average U.S. gas price (dollars per gallon) from 1991—2015.

Rows: 25

Columns: 4

Variables:

Year:

Year (from 1991-2015)

Average US Gas Price:

Average US gas price throughout the year

2 Period Moving Average:

The average price of gas for a 2-year period. It is taken from dividing the price of gas from the previous year and current year by two.

3 Period Moving Average:

The average price of gas for a 3-year period. It is taken from dividing the price of gas from the previous two years and current year by three.

Source

Source: www.data.bls.gov

U.S. Violent Crime by State

Violent crime rates for every state in the U.S. from 1989—2014.

Rows: 26

Columns: 52

Variables:

Year:

The year the crime rate is associated with

Alabama:

The number of reported offenses (i.e. murder, rape, robbery, and aggravated assault) per 100,000 individuals in Alabama by year

...

Wyoming:

The number of reported offenses (i.e. murder, rape, robbery, and aggravated assault) per 100,000 individuals in Wyoming by year

Source

https://www.ucrdatatool.gov/