Exploring Data - Data Science at the Command Line - page 102

Note that with the -f option, we can specify the function to apply to the data.frame
df . In this case, it is the same as -e cor(df) .
You can even create a stem plot (Tukey, 1977) using Rio :
$ < data/iris.csv Rio -e 'stem(df$sepal_length)'
The decimal point is 1 digit(s) to the left of the |
42 | 0
44 | 0000
46 | 000000
48 | 00000000000
50 | 0000000000000000000
52 | 00000
54 | 0000000000000
56 | 00000000000000
58 | 0000000000
60 | 000000000000
62 | 0000000000000
64 | 000000000000
66 | 0000000000
68 | 0000000
70 | 00
72 | 0000
74 | 0
76 | 00000
78 | 0
Creating Visualizations
In this section, we're going to discuss how to create visualizations at the command
line. We'll be looking at two different software packages: Gnuplot and ggplot2 . First,
we'll introduce both packages, and then we'll demonstrate how to create several dif‐
ferent types of visualizations using both of them.
Introducing Gnuplot and feedgnuplot
The first software package to create visualizations that we're discussing in this chapter
is Gnuplot, which has been around since 1986. Despite being rather old, its visualiza‐
tion capabilities are quite extensive. As such, it's impossible to do it justice in one sec‐
tion. There are already good resources available, including Gnuplot in Action by
Janert (2009).
To demonstrate the flexibility (and its archaic notation), consider Example 7-1 , which
is copied from the Gnuplot website .