Customizing heatmaps
Seaborn supports several types of additional customizations to improve the
output of a heatmap. For this exercise, we will continue to use the Daily Show data
that is stored in the df variable but we will customize the output.
Diese Übung ist Teil des Kurses
Intermediate Data Visualization with Seaborn
Anleitung zur Übung
- Create a crosstab table of
GroupandYEAR - Create a heatmap of the data using the
BuGnpalette - Disable the
cbarand increase thelinewidthto 0.3
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# Create the crosstab DataFrame
pd_crosstab = pd.crosstab(df["Group"], df["____"])
# Plot a heatmap of the table with no color bar and using the BuGn palette
sns.heatmap(pd_crosstab, cbar=____, cmap="____", linewidths=____)
# Rotate tick marks for visibility
plt.yticks(rotation=0)
plt.xticks(rotation=90)
#Show the plot
plt.show()
plt.clf()