Plotting in Python

Table of Contents

• Matplotlib
  • Bar charts
• Seaborn
• Saving figures

Matplotlib

Bar charts

Official documentation: here

Example 1:

plt.rcdefaults()
fig, ax = plt.subplots(figsize=(8, 6))
ax.barh(states, amount) # if horizontal bar
ax.invert_yaxis() # labels read top-to-bottom
ax.yaxis.set_ticks(np.arange(min(state), max(state)+1, 1))
plt.ylabel('State')
plt.xlabel('Amount')
plt.show();

Example 2:

df.plot

Seaborn

Sometimes we have multiple groups in the data and we would like to generate a plot for each of the groups. First we import the data set:

psg = pd.read_stata('dta_files/perc_suicide_gun.dta')

And then we can plot using the seaborn package

import seaborn as sns
g = sns.FacetGrid(psg, col="statename", hue='law_year', col_wrap=3, height=4)
g = (g.map(plt.scatter, "year", "perc_gun", edgecolor="w").add_legend()) # "year" would be on the x axis and "perc_gun" would be on the y axis
for ax in g.axes.flat:
    ax.set_ylim([0,1])  # set the range for the y axis
    ax.xaxis.set_major_locator(plt.AutoLocator())
    _ = plt.setp(ax.get_xticklabels(), visible=True) # in order to keep track of which group we are referring to
    _ = plt.setp(ax.get_yticklabels(), visible=True)
plt.show() # show the figure inline
g.savefig("perc_suicide_gun.jpg") # save the results as a figure

Part of the results are as below:

Note that the hue=’law_year, ‘ section can introduce a different color for the data points that we would like to highlight - this is not shown above.

Saving figures

To insert the figures into an academic paper, we need them to not have a lot of white space around the figures. For this, bbox_inches='tight' is helpful.

g.savefig("perc_suicide_gun.jpg", bbox_inches='tight') # save the results as a figure