在同一脚本中绘制多个图时，Seaborn 会附加图例

Question

I am new to Seaborn. When plotting multiple plots in the same script, the first plot is correct, but for the rest, the legends are appended which skew the plots.

My code

sns.set()
cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)
ax = sns.scatterplot(x="Clicks", y="Impressions",
                     hue="Language2", size="CTR",
                     palette=cmap, sizes=(10, 200),
                     data=df)
ax.get_figure().savefig('Test plot.png')

sns.set()
cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)
ax0 = sns.scatterplot(x="Impressions", y="Clicks",
                      hue="Word2", size="Transactions",
                      palette=cmap, sizes=(10, 200),
                      data=df)
ax0.get_figure().savefig('Test plot 2.png')

sns.set()
cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)
ax1 = sns.scatterplot(x="CTR", y="CostPerTransaction",
                      hue="Language2", size="Transactions",
                      palette=cmap, sizes=(10, 200),
                      data=df)
ax1.get_figure().savefig('Test plot 3.png')

I am not sure if I should use sns.set() each time. I've renamed each ax but the issue persists.

Also, maybe you could suggest how I could improve my plots.

Thank you for your suggestions.

Answer 1

I am not certain if this will fix your problem. But in general I have a strong preference for using the explicit object oriented approach whenever creating more than one plot in matplotlib/seaborn (matplotlib is the underlying library, seaborn is just wrapping it to make certain applications quicker). This means getting rid of the ax.get_figure().savefig parts. I found this tutorial really useful in understanding the object oriented matplotlib approach compared to the implicit state approach.

Your code in this method would look like this:

import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)
fig1, ax1 = plt.subplots()
sns.scatterplot(x="Clicks", y="Impressions",
                     hue="Language2", size="CTR",
                     palette=cmap, sizes=(10, 200),
                     data=df,
                     ax=ax1)
# This may help with your axes labels spilling off the figure:
fig1.tight_layout()
fig1.savefig('Test plot.png')


#  the sns.set is not needed each time
fig2, ax2 = plt.subplots()
# cmap is the same, so we don't need to define that again
sns.scatterplot(x="Impressions", y="Clicks",
                      hue="Word2", size="Transactions",
                      palette=cmap, sizes=(10, 200),
                      data=df,
                      ax=ax2)
fig2.savefig('Test plot 2.png')

fig3, ax3 = plt.subplots()
sns.scatterplot(x="CTR", y="CostPerTransaction",
                      hue="Language2", size="Transactions",
                      palette=cmap, sizes=(10, 200),
                      data=df,
                      ax=ax3)
fig3.savefig('Test plot 3.png')