Maximum of DataFrame over an Axis in Pandas

Maximum of DataFrame over an Axis

To find the maximum of the values over the requested axis in a DataFrame in Pandas, call max() method on this DataFrame. DataFrame.max() method returns a Series with values containing the maximum values over specified axis.

In this tutorial, we will learn the syntax of DataFrame.max() method, and how to use this method to find the maximum of values over a specified axis of DataFrame.

Syntax

The syntax of pandas DataFrame.max() method is

DataFrame.max(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)

where

Parameter	Value	Description
axis	{index (0), columns (1)}	Axis for the function to be applied on.
skipna	bool, default True	Exclude NA/null values when computing the result.
level	int or level name, default None	If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.
numeric_only	bool, default None	Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.
**kwargs		Additional keyword arguments to be passed to the function.

Return Value

• Series or
• DataFrame (if level specified)

Examples

Maximum in Columns of DataFrame

By default, maximum is calculated for columns in a DataFrame.

In the following program, we take a DataFrame two columns containing numerical data, and find the maximum in columns, or we can say over index axis of this DataFrame.

Example.py

import pandas as pd

df = pd.DataFrame({'a': [7, 4], 'b': [3, 2]})
result = df.max()
print(result)

Output

a    7
b    3
dtype: int64

Maximum in Rows of DataFrame

To compute the maximum values in rows of DataFrame, pass axis=1 in call to DataFrame.max() method.

Example.py

import pandas as pd

df = pd.DataFrame({'a': [7, 4], 'b': [3, 2]})
result = df.max(axis=1)
print(result)

Output

0    7
1    4
dtype: int64

Do not skip NA while finding Maximum

By default, NA values like None, np.nan, etc are ignored. But if we would like consider those values as well, pass skipna=False to DataFrame.max() method.

Example.py

import pandas as pd

df = pd.DataFrame({'a': [7, None], 'b': [3, 2]})
result = df.max(skipna=False)
print(result)

Output

a    NaN
b    3.0
dtype: float64

If any of the values is NA along the specified axis, then NaN would be considered as maximum value.

Conclusion

In this Pandas Tutorial, we learned how to find the maximum of values over specified axis in a DataFrame using pandas DataFrame.max() method.