Pandas Plot Multiple Columns on Bar Chart With Matplotlib
- Plot Bar Chart of Multiple Columns for Each Observation in the Single Bar Chart
- Stack Bar Chart of Multiple Columns for Each Observation in the Single Bar Chart
In this tutorial, we will introduce how we can plot multiple columns on a bar chart using the plot() method of the DataFrame object.
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 the DataFrame df to construct bar plots. We need to plot age, height, and weight for each person in the DataFrame on a single bar chart.
Plot Bar Chart of Multiple Columns for Each Observation in the 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()
Output:
It generates a bar chart for Age, Height and Weight for each person in the dataframe df using the plot() method for the df object. We pass a list of all the columns to be plotted in the bar chart as y parameter in the method, and kind="bar" will produce a bar chart for the df. The x parameter will be varied along the X-axis.
Stack Bar Chart of Multiple Columns for Each Observation in the 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()
Output:
It displays the bar chart by stacking one column’s value over the other for each index in the DataFrame.
Suraj Joshi is a backend software engineer at Matrice.ai.
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