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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.

Questo esercizio fa parte del corso

Intermediate Data Visualization with Seaborn

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Istruzioni dell'esercizio

  • 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

esercizio interattivo pratico

Prova questo esercizio completando questo codice di esempio.

# 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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