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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

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Exercise instructions

  • Create a crosstab table of Group and YEAR
  • Create a heatmap of the data using the BuGn palette
  • Disable the cbar and increase the linewidth 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()
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