You can use the figsize argument to change the figure size of a histogram created in pandas:

import matplotlib.pyplotas plt

#specify figure size (width, height)
fig = plt.figure(figsize=(8,3))
ax = fig.gca()

#create histogram using specified figure size
df['my_column'].hist(ax=ax)

The following example shows how to use the figsize argument in practice.

Example: How to Change Figure Size of Pandas Histogram

Suppose we have the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H',
                              'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P'],
                   'points': [10, 12, 14, 15, 15, 15, 16, 17,
                              19, 19, 24, 24, 28, 30, 34, 34]})

#view first five rows of DataFrame
print(df.head())

  player  points
0      A      10
1      B      12
2      C      14
3      D      15
4      E      15

If we create a histogram for the points variable, pandas will automatically use 6.4 as the width of the figure and 4.8 as the height:

import matplotlib.pyplotas plt

#create histogram for points variable
df['points'].hist(grid=False, edgecolor='black')

However, we can use the figsize argument to change the width and height of the figure:

import matplotlib.pyplotas plt

#specify figure size (width, height)
fig = plt.figure(figsize=(8,3))
ax = fig.gca()

#create histogram using specified figure size
df['points'].hist(grid=False, edgecolor='black', ax=ax)

This particular histogram has a width of 8 and a height of 3.

We can also use the figsize argument to create a figure that has a greater height than width:

import matplotlib.pyplotas plt

#specify figure size (width, height)
fig = plt.figure(figsize=(4,7))
ax = fig.gca()

#create histogram using specified figure size
df['points'].hist(grid=False, edgecolor='black', ax=ax)

This particular histogram has a width of 4 and a height of 7.

The following tutorials explain how to perform other common tasks in pandas: