Customizing with matplotlib

Trực quan hóa dữ liệu nâng cao với Seaborn

Chris Moffitt

Instructor

Matplotlib Axes

Most customization available through matplotlib Axes objects
Axes can be passed to seaborn functions

fig, ax = plt.subplots()
sns.histplot(df['Tuition'], ax=ax)
ax.set(xlabel='Tuition 2013-14')

Example axes plot

Further Customizations

The axes object supports many common customizations

fig, ax = plt.subplots()
sns.histplot(df['Tuition'], ax=ax)
ax.set(xlabel="Tuition 2013-14",
       ylabel="Distribution", xlim=(0, 50000), 
title="2013-14 Tuition and Fees Distribution")

Additional axes example

Combining Plots

It is possible to combine and configure multiple plots

fig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2, 
                               sharey=True, figsize=(7,4))

sns.histplot(df['Tuition'], stat='density', ax=ax0)
sns.histplot(df.query('State == "MN"')['Tuition'], stat='density', ax=ax1)

ax1.set(xlabel='Tuition (MN)', xlim=(0, 70000))
ax1.axvline(x=20000, label='My Budget', linestyle='--')
ax1.legend()

Combining Plots

Side by side plots

Let's practice!

Trực quan hóa dữ liệu nâng cao với Seaborn