R Dataset / Package vcd / Hitters

How To Create a Barplot

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Visual
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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Numerical

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Ratio

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Regression

Submitted by pmagunia on April 22, 2018 - 3:12 PM

Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM
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Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
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Submitted by pmagunia on March 9, 2018 - 1:06 PM
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Attachment Size
dataset-27926.csv 26.41 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the Hitters data set which pertains to Hitters Data. The Hitters data set is found in the vcd R package. Try to load the Hitters data set in R by issuing the following command at the console data("Hitters"). This may load the data into a variable called Hitters. If R says the Hitters data set is not found, you can try installing the package by issuing this command install.packages("vcd") and then attempt to reload the data with library("vcd") followed by data("Hitters"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing Hitters at the command-line which should display the entire dataset.

If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Hitters R data set. The size of this file is about 27,040 bytes.


Hitters Data

Description

This data set is deduced from the Baseball fielding data set: fielding performance basically includes the numbers of Errors, Putouts and Assists made by each player. In order to reduce the number of observations, the was compressed by calculating the mean number of errors, putouts and assists for each team and for only 6 positions (1B, 2B, 3B, C, OF, SS and UT). In addition, each of these three variables was scaled to a common range by dividing each variable by the maximum of the variable.

Usage

data("Hitters")

Format

A data frame with 154 observations and 4 variables.

Positions

factor indicating the field position (1B=first baseman, 2B=second baseman, 3B=third baseman, C=catcher, OF=outfielder, SS=Short Stop, UT=Utility Players).

Putouts

occur when a fielder causes an opposing player to be tagged or forced out.

Assists

are credited to other fielders involved in making that putout.

Errors

count the errors made by a player.

Source

SAS System for Statistical Graphics, First Edition, Page A2.3

References

M. Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.

Examples

data("Hitters")
attach(Hitters)colors <- c("black","red","green","blue","red","black","blue")
pch <- substr(levels(Positions), 1, 1)
ternaryplot(Hitters[,2:4],
  pch = as.character(Positions),
  col = colors[as.numeric(Positions)],
  main = "Baseball Hitters Data")
grid_legend(0.8, 0.9, pch, colors, levels(Positions),
  title = "POSITION(S)")detach(Hitters)

--

Dataset imported from https://www.r-project.org.
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