Pandas DataFrame DataFrame.boxplot() Function

  1. Syntax of pandas.DataFrame.boxplot():
  2. Example Codes: Generate Boxplot With pandas.DataFrame.boxplot()
  3. Example Codes: Generate Boxplot Grouping Data Based on Column Values With pandas.DataFrame.boxplot()
  4. Set layout Parameter to Change Layout of Boxplots

pandas.DataFrame.boxplot() makes a box-and-whisker plot from DataFrame columns. A box and whisker plot summarizes the minimum, first quartile, median, third quartile, and the maximum value of data.

Syntax of pandas.DataFrame.boxplot():

DataFrame.boxplot(column=None, 
                  by=None, 
                  ax=None, 
                  fontsize=None, 
                  rot=0, 
                  grid=True, 
                  figsize=None, 
                  layout=None, 
                  return_type=None, 
                  backend=None, 
                  **kwargs) 

Parameters

column Column name from which boxplot has to be generated
by Plots different boxplots grouping by columns in different groups.
ax Matplotlib axes to be used by boxplot
grid Boolean. Turn grids on (True) and off(False)
rot Integer. Rotation angle for the label along X-axis
fontsize Font size of labels in Boxplot
layout Parameter used to control or set the layout of Boxplot
return_type Object type to return
backend Backend to use instead of the backend specified in the option plotting.backend.
**kwargs Keyword arguments for the method

Example Codes: Generate Boxplot With pandas.DataFrame.boxplot()

import pandas as pd
import matplotlib.pyplot as plt

fruits=['Apple', 'Papaya', 'Banana', 'Mango','Litchi','Avocado']
prices=[3, 1, 2, 4,4,5]

df = pd.DataFrame({'Fruit':fruits ,
                   'Price': prices})
print(df)

boxplot = df.boxplot(column=['Price'])
boxplot.plot()

plt.show()

Output:

Generate Boxplot with DataFrame boxplot

It generates a boxplot from the prices column of DataFrame. We use matplotlib.pyplot to show the generated plot.

Example Codes: Generate Boxplot Grouping Data Based on Column Values With pandas.DataFrame.boxplot()

import pandas as pd
import numpy as np
import sklearn

dates=['April-10', 'April-10', 'April-11', 'April-11','April-11']
prices=[3, 1, 2, 4,5]

df = pd.DataFrame({'Date':dates ,
                   'Price': prices})
print(df)

boxplot = df.boxplot(column=['Price'],by="Date")
boxplot.plot()

plt.show()

Output:

Generate Boxplot with DataFrame boxplot using groupby

At first, it groups the given DataFrame into different groups based on their value of the Date column and then generates a boxplot for each DataFrame.

We can customize our plot using fontsize, rot, and grid parameters.

import pandas as pd
import matplotlib.pyplot as plt

dates=['April-10', 'April-10', 'April-11', 'April-11','April-11']
prices=[3, 1, 2, 4,5]

df = pd.DataFrame({'Date':dates ,
                   'Price': prices})
print(df)

boxplot = df.boxplot(column=['Price'],by="Date",grid=False, rot=45, fontsize=15)
boxplot.plot()

plt.show()

Output:

Customize boxplot pandas

Here, grid=False turns off the grid, rot=45 rotates the X-axis labels by 45 degrees, and fontsize=15 changes the font size to 15.

Set layout Parameter to Change Layout of Boxplots

import pandas as pd

dates=['April-10', 'April-10', 'April-11', 'April-11','April-11']
prices=[3, 1, 2, 4,5]


df = pd.DataFrame({'Date':dates ,

boxplot = df.boxplot(column=['Price'],by="Date",layout=(2,1),grid=False,fontsize=15)

Output:

Set layout parameter to change the layout of boxplots

Here, the layout parameter changes the layout of the boxplot generated.layout=(2,1) aligns the boxplots in 2 rows and a column.

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