Often you may be interested in finding the max value of one or more columns in a pandas DataFrame. Fortunately you can do this easily in pandas using the max() function.

This tutorial shows several examples of how to use this function.

**Example 1: Find the Max Value of a Single Column**

Suppose we have the following pandas DataFrame:

import pandas as pd import numpy as np #create DataFrame df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'], 'points': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19], 'assists': [5, 7, 7, 8, 5, 7, 6, 9, 9, 5], 'rebounds': [np.nan, 8, 10, 6, 6, 9, 6, 10, 10, 7]}) #view DataFrame df player points assists rebounds 0 A 25 5 NaN 1 B 20 7 8.0 2 C 14 7 10.0 3 D 16 8 6.0 4 E 27 5 6.0 5 F 20 7 9.0 6 G 12 6 6.0 7 H 15 9 10.0 8 I 14 9 10.0 9 J 19 5 7.0

We can find the max value of the column titled “points” by using the following syntax:

df['points'].max() 27

The max() function will also exclude NA’s by default. For example, if we find the max of the “rebounds” column, the first value of “NaN” will simply be excluded from the calculation:

df['rebounds'].max() 10.0

The max of a string column is defined as the highest letter in the alphabet:

df['player'].max() 'J'

**Example 2: Find the Max of Multiple Columns**

We can find the max of multiple columns by using the following syntax:

#find max of points and rebounds columns df[['rebounds', 'points']].max() rebounds 10.0 points 27.0 dtype: float64

**Example 3: Find the Max of All Columns**

We can find also find the max of all numeric columns by using the following syntax:

#find max of all numeric columns in DataFrame df.max() player J points 27 assists 9 rebounds 10 dtype: object

**Example 4: Find Row that Corresponds to Max**

We can find also return the entire row that corresponds to the max value in a certain column. For example, the following syntax returns the entire row that corresponds to the player with the max points:

#return entire row of player with the max points df[df['points']==df['points'].max()] player points assists rebounds 4 E 27 5 6.0

If multiple rows have the same max value, each row will be returned. For example, suppose player D also scored 27 points:

#return entire row of players with the max points df[df['points']==df['points'].max()] player points assists rebounds 3 D 27 8 6.0 4 E 27 5 6.0

*You can find the complete documentation for the max() function here.*