Stacked Bar Charts
Stacked bar charts are useful when we want to compare several categories (two or more) for each value on the x-axis. For example, instead of only looking at the GDP of different countries we may want to look at the amount of contribution of each economic sector to the GDP of a particular country (the data is not real):
import matplotlib.pyplot as plt import numpy as np countries = ['USA', 'China', 'Japan'] primary_sector = np.array([1.4, 4.8, 0.4]) secondary_sector = np.array([11.3, 6.2, 0.8]) tertiary_sector = np.array([14.2, 8.4, 3.2]) # Calling the bar() function multiple times for each category (sector) plt.bar(countries, primary_sector) plt.bar(countries, secondary_sector, bottom=primary_sector) plt.bar(countries, tertiary_sector, bottom=primary_sector + secondary_sector) plt.show()
Similarly to line plots and scatter plots, we called the bar()
function three times to create three bars for each value on the x-axis (country names in our example). In every call countries
are specified as x-axis values in order to create stacked bars. Pay extra attention to the bottom
parameter.
Note
bottom
parameter specifies the y coordinate(s) of the bottom side(s) of the bars. Here is the documentation.
Swipe to start coding
- Use the correct function for creating bar charts.
- Plot the lower bars for
yes_answers
. - Plot the bars for
no_answers
on top of the bars foryes_answers
with specifying the correct keyword argument.
Soluzione
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