Pandas plots multiple columns on Matplotlib bar chart
In this tutorial, we will look at how to plot multiple columns on a histogram using the method DataFrameof the object .plot()
import pandas as pd
data = [
["Rudra", 23, 156, 70],
["Nayan", 20, 136, 60],
["Alok", 15, 100, 35],
["Prince", 30, 150, 85],
]
df = pd.DataFrame(data, columns=["Name", "Age", "Height(cm)", "Weight(kg)"])
print(df)
Output:
Name Age Height(cm) Weight(kg)
0 Rudra 23 156 70
1 Nayan 20 136 60
2 Alok 15 100 35
3 Prince 30 150 85
We will use DataFrame dfto build a bar chart. We need to plot the age, height, and weight of each person in the DataFrame on a bar chart.
Plot multiple columns of bars for each observation in a single bar chart
import pandas as pd
import matplotlib.pyplot as plt
data = [
["Rudra", 23, 156, 70],
["Nayan", 20, 136, 60],
["Alok", 15, 100, 35],
["Prince", 30, 150, 85],
]
df = pd.DataFrame(data, columns=["Name", "Age", "Height(cm)", "Weight(kg)"])
df.plot(x="Name", y=["Age", "Height(cm)", "Weight(kg)"], kind="bar", figsize=(9, 8))
plt.show()
It uses the method dfof the object to generate a bar chart of , , and for each person in the data frame . We pass a list of all the columns to be plotted in the histogram as the parameter in the method, and a histogram will be generated for . The parameter will vary along the X-axis.plot()dfAgeHeightWeightykind="bar"dfx
Overlay multiple columns of bar charts for each observation in a single bar chart
import pandas as pd
import matplotlib.pyplot as plt
employees = ["Rudra", "Alok", "Prince", "Nayan", "Reman"]
earnings = {
"January": [10, 20, 15, 18, 14],
"February": [20, 13, 10, 18, 15],
"March": [20, 20, 10, 15, 18],
}
df = pd.DataFrame(earnings, index=employees)
df.plot(kind="bar", stacked=True, figsize=(10, 8))
plt.legend(loc="lower left", bbox_to_anchor=(0.8, 1.0))
plt.show()It displays a bar chart by overlaying one column of values on another column for each index in the DataFrame.
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