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We use the add method in Matplotlib matplotlib.pyplot.bar()to generate a bar chart. To stack a bar chart of one dataset on top of another, we add up all the datasets that need to be stacked and bottompass the sum as the argument to bar()the add method.

import matplotlib.pyplot as plt

data1 = [30, 20, 10, 0, 0]
data2 = [20, 20, 20, 20, 0]
data3 = [50, 60, 70, 80, 100]

year = ["2015", "2016", "2017", "2018", "2019"]

fig, ax = plt.subplots(3, 1, figsize=(10, 8))

ax[0].bar(year, data1, color="red")
ax[0].legend(["C++"])
ax[1].bar(year, data2, color="yellow")
ax[1].legend(["JavaScript"])
ax[2].bar(year, data3, color="green")
ax[2].legend(["Python"])

plt.show()

Output:

Here we have three separate bar graphs representing the preferences of employees at a company for a programming language over five years. We will discuss how to overlay a bar graph for one language on top of another and use a single bar graph to examine the overall choice of programming languages ​​over the years.

Overlay bar charts Matplotlib

import numpy as np
import matplotlib.pyplot as plt

data1 = [30, 20, 10, 0, 0]
data2 = [20, 20, 20, 20, 0]
data3 = [50, 60, 70, 80, 100]

year = ["2015", "2016", "2017", "2018", "2019"]

plt.figure(figsize=(9, 7))
plt.bar(year, data3, color="green", label="Python")
plt.bar(year, data2, color="yellow", bottom=np.array(data3), label="JavaScript")
plt.bar(year, data1, color="red", bottom=np.array(data3) + np.array(data2), label="C++")

plt.legend(loc="lower left", bbox_to_anchor=(0.8, 1.0))
plt.show()

Output:

It superimposes one bar chart on top of another. In the figure, we first data3plot as Python data as the basis for the other bar charts, and then plot data2a bar chart of , using data3the bar chart of as data2the basis for the bar chart of . To data2superimpose the bar chart of on data3top of , we set bottom=np.array(data3).

Similarly, data1when we draw the bar chart of , we build on the bar charts of data2and data3. To do this, we data1set when we draw the bar chart of bottom=np.array(data3)+np.array(data2).

Note that we have to use NumPyan array to add bottomthe data for the parameter. If we set it bottom=data3+data2, it will create a list by data3appending the elements of at the end of the list.data2

If we don't want to use NumPyan array, we can use list comprehension to add the corresponding elements of list.

import numpy as np
import matplotlib.pyplot as plt

data1 = [30, 20, 10, 0, 0]
data2 = [20, 20, 20, 20, 0]
data3 = [50, 60, 70, 80, 100]

year = ["2015", "2016", "2017", "2018", "2019"]

plt.figure(figsize=(9, 7))
plt.bar(year, data3, color="green", label="Python")
plt.bar(year, data2, color="yellow", bottom=data3, label="JavaScript")
plt.bar(
    year,
    data1,
    color="red",
    bottom=[sum(data) for data in zip(data2, data3)],
    label="C++",
)

plt.legend(loc="lower left", bbox_to_anchor=(0.8, 1.0))
plt.show()

Output:

How to Overlay Bar Charts Using Matplotlib with Pandasd

We can also Pandasgenerate stacked bar charts in Python using the library in Python.

import pandas as pd
import matplotlib.pyplot as plt

years = ["2015", "2016", "2017", "2018", "2019"]
data = {
    "Python": [50, 60, 70, 80, 100],
    "JavaScript": [20, 20, 20, 20, 0],
    "C++": [30, 20, 10, 0, 0],
}

df = pd.DataFrame(data, index=years)

df.plot(kind="bar", stacked=True, figsize=(10, 8))
plt.legend(loc="lower left", bbox_to_anchor=(0.8, 1.0))
plt.show()

Output:

It generates a stacked bar chart from a Pandas DataFrame where the bars of one column are stacked on top of another column for each index in the DataFrame.