Top performances in the Decathlon from 1985 to 2006.

Description

The point scoring system for the Decathlon last changed in 1985. Best annual performances of 6800 points and over for a twenty-one year period after the new rules were introduced were downloaded from the excellent Estonian website Decathlon2000. Handtimed performances were not included. Names with accents have been simplified.

Usage

data(Decathlon)

Format

A data frame with 7968 observations on the following 24 variables.

Totalpoints

the total points achieved over all 10 events

DecathleteName

Decathlete's name

Nationality

Decathlete's nationality

m100

Time for the 100 metres (secs)

Longjump

Distance jumped (metres)

Shotput

Distance putting the shot (metres)

Highjump

Height jumped (metres)

m400

Time for the 400 metres (secs)

m110hurdles

Time for the 110 metres hurdles (secs)

Discus

Distance throwing the discus (metres)

Polevault

Height achieved (metres)

Javelin

Distance throwing the javelin (metres)

m1500

Time for the 1500 metres (secs)

yearEvent

Year of performance

P100m

Points for performance in 100 metres

Plj

Points for performance in long jump

Psp

Points for performance in putting the shot

Phj

Points for performance in high jump

P400m

Points for performance in 400 metres

P110h

Points for performance in 110 metres hurdles

Ppv

Points for performance in pole vault

Pdt

Points for performance in discus

Pjt

Points for performance in javelin

P1500

Points for performance in 1500 metres

Source

http://www.decathlon2000.com

Examples

data(Decathlon, package="GDAdata")
summary(Decathlon[, grep("P.*", names(Decathlon))])
library(ggplot2)
ggplot(Decathlon, aes(Plj)) + geom_histogram()
ggplot(Decathlon, aes(P100m, Plj)) + geom_point()

Figures for the trade between England and the East Indies in the 18th century.

Description

The data have been estimated from the graphic in the first edition of Playfair's Commercial and Political Atlas by the website 'Me, myself, and BI'.

Usage

data(EastIndiesTrade)

Format

A data frame with 81 observations on the following 3 variables.

Year

the data go from 1700 to 1780

Exports

Exports from England to the East Indies (millions of pounds)

Imports

Imports to England from the East Indies (millions of pounds)

Source

http://blog.bissantz.com/vis-a-vis

Examples

data(EastIndiesTrade, package="GDAdata")
library(ggplot2)
ggplot(EastIndiesTrade, aes(x=Year, y=Exports-Imports)) + geom_line()

Star data useful for drawing a Hertzsprung-Russell diagram.

Description

Hertzsprung-Russell diagrams plot star luminosity (brightness) against temperature (colour). The first one was drawn just over 100 years ago. The dataset is the Yale Trigonometric Parallax Dataset and this version can be found on the webpage of the Astronomy Department of Case Western Reserve University.

Usage

data(HRstars)

Format

A data frame with 6220 observations on the following 5 variables.

ID

star ID number

V

apparent V magnitude

BV

observed B-V color

Para

observed parallax (in arcsec)

Uncert

uncertainty in parallax (in milliarcsec)

Source

http://burro.astr.cwru.edu/Academics/Astr221/HW/HW5/HW5.html

Examples

data(HRstars, package="GDAdata")
with(HRstars, hist(BV))
with(HRstars, hist(V))

Data from the longjump final in the 1968 Mexico Olympics.

Description

The best longjumps by the 16 finalists in the 1968 Mexico Olympics. Each athlete jumped up to six times, though the winner of the Gold Medal, Bob Beamon, only jumped twice.

Usage

data(MexLJ)

Format

A data frame with 16 observations on the following variable.

Jump

Distance jumped measured in metres

Source

http://en.wikipedia.org/wiki/Athletics_at_the_1968_Summer_Olympics_-_Men's_long_jump

Examples

data(MexLJ, package="GDAdata")
with(MexLJ, summary(Jump))
with(MexLJ, hist(Jump,breaks=seq(7.25,9,0.25)))

World Speed Skiing Competition, Verbier 21st April, 2011

Description

There were separate Speed Skiing competitions for men (79 participants) and women (12 participants).

Usage

data(SpeedSki)

Format

A data frame with 91 observations on the following 8 variables.

Rank

Finishing position by sex

Bib

Start number

FIS.Code

Skier's international skiing ID number

Name

Skier's name

Year

Skier's year of birth

Nation

Skier's nationality

Speed

Speed achieved in km/hr

Sex

Female or Male

Event

Speed Downhill, Speed Downhill Junior or Speed One

no.of.runs

No of runs

Source

http://www.fis-ski.com/de/606/612.html?sector=SS&raceid=262 (men)
http://www.fis-ski.com/de/606/612.html?sector=SS&raceid=263 (women)

Examples

data(SpeedSki, package="GDAdata")
with(SpeedSki, summary(Speed))
library(ggplot2)
ggplot(SpeedSki, aes(Speed)) + geom_histogram(binwidth=5)

Nutritional value of food.

Description

Nutritional value of different foods based on standard serving sizes.

Usage

data(foodnames)

Format

A data frame with 961 observations on the following 9 variables.

Name

name of food (not unique)

Measure

serving description

Fat.grams

grams of fat in a standard serving

Food.energy.calories

calories per serving

Carbohydrates.grams

grams of carbohydrates per serving

Protein.grams

grams of protein per serving

Cholesterol.mg

cholesterol in mg per serving

weight.grams

weight in grams of a standard serving

Saturated.fat.grams

grams of saturated fat per serving

Source

The data are used in A. Izenman (2008), Modern Multivariate Statistical Techniques, Springer
and are available on the accompanying website http://astro.temple.edu/~alan/MMST/

Examples

data(foodnames, package="GDAdata")
summary(foodnames)
library(ggplot2)
ggplot(foodnames, aes(Fat.grams, Saturated.fat.grams)) + geom_point()

The Guardian University League Table 2013

Description

The Guardian newspaper in the UK publishes a ranking of British universities each year and it reported these data in May, 2012 as a guide for 2013.

Usage

data(uniranks)

Format

A data frame with 120 observations on the following 13 variables.

Rank

Rank of the University

Institution

University name

UniGroup

Universities can be a member of one of five groups, 1994 Group, Guild HE, Million+, Russell, University Alliance, or none

HesaCode

University's Higher Education Statistics Agency code

AvTeachScore

Average Teaching Score

NSSTeaching

University's National Student Survey teaching score

NSSOverall

University's NSS overall score

SpendPerStudent

University expenditure per student (depends on subject)

StudentStaffRatio

Student to Staff ratio

CareerProspects

Proportion of graduates in appropriate level employment or full-time study within six months of graduation

ValueAddScore

”Based upon a sophisticated indexing methodology that tracks students from enrolment to graduation, qualifications upon entry are compared with the award that a student receives at the end of their studies.” (Guardian)

EntryTariff

Value dependent on the average points needed to get on the university's courses

NSSFeedback

University's NSS feedback score

Source

http://www.theguardian.com/news/datablog/2012/may/22/university-guide-2013-guardian-data

Examples

data(uniranks, package="GDAdata")
with(uniranks, table(UniGroup))
library(ggplot2)
ggplot(uniranks, aes(x=NSSTeaching, y=NSSFeedback)) + geom_point()
ggplot(uniranks, aes(x=UniGroup, y=SpendPerStudent)) + geom_boxplot()