Plotting

Learn how to plot DataFrames using the pyplot API from Matplotlib.

We'll cover the following

Chapter Goals:

  • Learn how to plot DataFrames using the pyplot API

A. Basics

The main function used for plotting DataFrames is plot. This function is used in tandem with the show function from the pyplot API, to produce plot visualizations. We import the pyplot API with the line:
import matplotlib.pyplot as plt

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# predefined df
print('{}\n'.format(df))
df.plot(kind='line',x='yearID',y='HR')
plt.show()

After calling df.plot, which creates our line plot, we then use plt.show to open a separate window containing the visualization of the plot. You can also use plt.savefig to save the plot to a PNG or PDF file.

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# predefined df
print('{}\n'.format(df))
df.plot(kind='line',x='yearID',y='HR')
plt.show()
plt.savefig('output/legend.png')  # save to PNG file

The plot we created has no title or y-axis label. We can manually set the plot's title and axis labels using the pyplot API.

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# predefined df
print('{}\n'.format(df))
df.plot(kind='line',x='yearID',y='HR')
plt.title('HR vs. Year')
plt.xlabel('Year')
plt.ylabel('HR Count')
plt.show()

We use the title function to set the title of our plot, and the xlabel and ylabel functions to set the axis labels.

B. Other plots

In addition to basic line plots, we can create other plots like histograms or boxplots by setting the kind keyword argument in plot.

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# predefined df
print('{}\n'.format(df))
df.plot(kind='bar',y='HR')
plt.ylabel('Frequency')
plt.show()
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# predefined df
print('{}\n'.format(df))
df.plot(kind='box',y='HR')
plt.show()

There are numerous different kinds of plots we can create by setting the kind keyword argument. A list of the accepted values for kind can be found in the documentation for plot.

C. Multiple features

We can also plot multiple features on the same graph. This can be extremely useful when we want visualizations to compare different features.

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# predefined df
print('{}\n'.format(df))
# gca stands for 'get current axis'
ax = plt.gca()
df.plot(kind='line',x='yearID',y='H',ax=ax)
df.plot(kind='line',x='yearID',y='BB', color='red', ax=ax)
plt.show()
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# predefined df
print('{}\n'.format(df))
df.plot(kind='box')
plt.show()

These are a line plot and boxplot showing both hits (H) and walks (BB). Note that the circles in the boxplot represent outlier values.

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