R Dataset / Package ISLR / Weekly

How To Create a Barplot

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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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Boxplot

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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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Regression

Stem and Leaf Plots

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Visual Summaries

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Attachment Size
dataset-95529.csv 61.21 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
R Dataset Help

On this Picostat.com statistics page, you will find information about the Weekly data set which pertains to Weekly S&P Stock Market Data. The Weekly data set is found in the ISLR R package. You can load the Weekly data set in R by issuing the following command at the console data("Weekly"). This will load the data into a variable called Weekly. If R says the Weekly data set is not found, you can try installing the package by issuing this command install.packages("ISLR") and then attempt to reload the data. 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 Weekly R data set. The size of this file is about 62,683 bytes.

Documentation

Weekly S&P Stock Market Data

Description

Weekly percentage returns for the S&P 500 stock index between 1990 and 2010.

Usage

Weekly

Format

A data frame with 1089 observations on the following 9 variables.

Year

The year that the observation was recorded

Lag1

Percentage return for previous week

Lag2

Percentage return for 2 weeks previous

Lag3

Percentage return for 3 weeks previous

Lag4

Percentage return for 4 weeks previous

Lag5

Percentage return for 5 weeks previous

Volume

Volume of shares traded (average number of daily shares traded in billions)

Today

Percentage return for this week

Direction

A factor with levels Down and Up indicating whether the market had a positive or negative return on a given week

Source

Raw values of the S&P 500 were obtained from Yahoo Finance and then converted to percentages and lagged.

References

Games, G., Witten, D., Hastie, T., and Tibshirani, R. (2013) An Introduction to Statistical Learning with applications in R, www.StatLearning.com, Springer-Verlag, New York

Examples

summary(Weekly)
lm(Today~Lag1+Lag2,data=Weekly)
--

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

All Public Datasets File Size
Test 394 bytes
Q1 332 bytes
prova_Correlatio 593 bytes
profva
test 332 bytes