September 2017
Beginner to intermediate
560 pages
25h 18m
English
book
R Data Analysis Cookbook, Second Edition - Second Edition
by Kuntal Ganguly, Davor Lozić, Mzabalazo Z. Ngwenya, Andrew Bauman, Shanthi Viswanathan, Viswa Viswanathan
Content preview from R Data Analysis Cookbook, Second Edition - Second Edition
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Getting ready
Read the data from the file and create factors. We also attach the data to save on keystrokes as follows. Download the GGally and ggplot2 package, if you have not already done so:
> library(ggplot2) > library(GGally) > bike <- read.csv("daily-bike-rentals.csv") > bike$season <- factor(bike$season, levels = c(1,2,3,4), labels = c("Spring", "Summer", "Fall", "Winter")) > bike$weathersit <- factor(bike$weathersit, levels = c(1,2,3), labels = c("Clear", "Misty/cloudy", "Light snow")) > bike$windspeed.fac <- cut(bike$windspeed, breaks=3, labels=c("Low", "Medium", "High")) > bike$weekday <- factor(bike$weekday, levels = c(0:6), labels = c("Sun", "Mon", "Tue", "Wed", "Thur", "Fri", "Sat")) > attach(bike)
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.