Creating heatmaps
A heatmap is a common matrix plot that can be used to graphically summarize the relationship between two variables. For this exercise, we will start by looking at guests of the Daily Show from 1999 - 2015 and see how the occupations of the guests have changed over time.
The data includes the date of each guest appearance as well as their occupation. For the first exercise,
we need to get the data into the right format for Seaborn's heatmap function to correctly plot the data.
All of the data has already been read into the df variable.
This exercise is part of the course
Intermediate Data Visualization with Seaborn
Exercise instructions
- Use pandas'
crosstab()function to build a table of visits byGroupandYear. - Print the
pd_crosstabDataFrame. - Plot the data using Seaborn's
heatmap().
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a crosstab table of the data
pd_crosstab = pd.____(df["Group"], df["YEAR"])
print(pd_crosstab)
# Plot a heatmap of the table
sns.____(pd_crosstab)
# Rotate tick marks for visibility
plt.yticks(rotation=0)
plt.xticks(rotation=90)
plt.show()