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.
This exercise is part of the course
Intermediate Data Visualization with Seaborn
Exercise instructions
- Create a crosstab table of
Group
andYEAR
- Create a heatmap of the data using the
BuGn
palette - Disable the
cbar
and increase thelinewidth
to 0.3
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# 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()