Pandas Series: plot.hist() function

Last update on September 15 2022 12:54:42 (UTC/GMT +8 hours)

Series-plot.hist() function

A histogram is a representation of the distribution of data. This function groups the values of all given Series in the DataFrame into bins and draws all bins in one matplotlib.axes.Axes. This is useful when the DataFrame’s Series are in a similar scale.

The plot.hist() function is used to draw one histogram of the DataFrame’s columns.

Syntax:

Series.plot.hist(self, by=None, bins=10, **kwargs)

Parameters:

Name	Description	Type/Default Value	Required / Optional
by	Column in the DataFrame to group by.	str or sequence	Optional
bins	Number of histogram bins to be used.	int, default 10	Required
**kwds	Additional keyword arguments are documented in DataFrame.plot()		Optional

Returns: class:matplotlib.AxesSubplot Return a histogram plot.

Example - When we draw a dice 8000 times, we expect to get each value around 2000 times. But when we draw two dices and sum the result, the distribution is going to be quite different. A histogram illustrates those distributions:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame(
     np.random.randint(1, 8, 8000),
     columns = ['one'])
df['two'] = df['one'] + np.random.randint(1, 8, 8000)
ax = df.plot.hist(bins=12, alpha=0.5)

Output:

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