454_Data_Summary
Michael Gilbert
11 July, 2016
Data Summary
This R Programming Challenge is more of a data manipulation exercise than a programming exercise. Here we will use a data file of daily stock prices and volume to exercise some basic needed data skills on the R data frame.
Here are the data exercises:
Read in the data file and check the ‘structure’ of the data. Is the variable
Datea factor, string, or date? What data type should it be?# Read data jpm = read.csv("~/JPM.csv", header = T) # Check date class class(jpm$Date)## [1] "factor"Dateis read as afactorvariable byR.Type cast the variable Date into an R date type named TradeDate. Make sure that TradeDate is attached to your data frame.
jpm$TradeDate = as.Date(jpm$Date, format = "%d-%b-%y")Create a seven character Year-Month string named
YearMonth. Make sure thatYearMonthis attached to your data frame.jpm$YearMonth = substr(jpm$TradeDate, 1, 7)Compute the total trading volume for each YearMonth.
round(by(jpm$Volume, jpm$YearMonth, sum), digits = 2)## jpm$YearMonth: 2014-01 ## [1] 426148286 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-02 ## [1] 347322382 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-03 ## [1] 425954355 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-04 ## [1] 409023463 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-05 ## [1] 315112129 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-06 ## [1] 263715897 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-07 ## [1] 317345809 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-08 ## [1] 241563417 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-09 ## [1] 264948567 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-10 ## [1] 415470600 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-11 ## [1] 211535572 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-12 ## [1] 347657497 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-01 ## [1] 468205871 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-02 ## [1] 319008175 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-03 ## [1] 332554476 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-04 ## [1] 325069427 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-05 ## [1] 267794319 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-06 ## [1] 337237622Compute the average closing price for each YearMonth.
round(by(jpm$Close, jpm$YearMonth, mean), digits = 2)## jpm$YearMonth: 2014-01 ## [1] 57.49 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-02 ## [1] 56.93 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-03 ## [1] 58.87 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-04 ## [1] 57.05 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-05 ## [1] 54.49 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-06 ## [1] 57.12 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-07 ## [1] 57.69 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-08 ## [1] 57.5 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-09 ## [1] 60.21 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-10 ## [1] 58.5 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-11 ## [1] 60.69 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-12 ## [1] 61.48 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-01 ## [1] 57.49 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-02 ## [1] 58.94 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-03 ## [1] 61.04 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-04 ## [1] 62.28 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-05 ## [1] 65.61 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-06 ## [1] 67.88Compute the average daily intraday price spread for each YearMonth. Note that this intraday price spread is computed by the daily high minus the daily low.
jpm$IDPS = (jpm$High - jpm$Low) round(by(jpm$IDPS, jpm$YearMonth, mean), digits = 2)## jpm$YearMonth: 2014-01 ## [1] 0.97 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-02 ## [1] 0.89 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-03 ## [1] 0.96 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-04 ## [1] 0.93 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-05 ## [1] 0.65 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-06 ## [1] 0.69 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-07 ## [1] 0.68 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-08 ## [1] 0.7 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-09 ## [1] 0.73 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-10 ## [1] 1.12 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-11 ## [1] 0.68 ## -------------------------------------------------------- ## jpm$YearMonth: 2014-12 ## [1] 1.08 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-01 ## [1] 1.39 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-02 ## [1] 0.89 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-03 ## [1] 0.9 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-04 ## [1] 0.87 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-05 ## [1] 0.82 ## -------------------------------------------------------- ## jpm$YearMonth: 2015-06 ## [1] 0.8Use {base}
Rgraphics to make this plot.boxplot(jpm$IDPS ~ jpm$YearMonth, las = 2, main = "Boxplots of Intraday Price Spread")
Use {base}
Rgraphics to make this plot.bp = barplot(by(jpm$Close, jpm$YearMonth, mean), las = 2, main = "Average Closing Price", ylim = c(0, 80)) abline(h = mean(jpm$Close), col = "blue", lty = 5)
rm(bp)