How to Calculate Mean, Median and Mode in Pandas

You can use the following functions to calculate the mean, median, and mode of each numeric column in a pandas DataFrame:

print(df.mean(numeric_only=True))
print(df.median(numeric_only=True))
print(df.mode(numeric_only=True))

The following example shows how to use these functions in practice.

Example: Calculate Mean, Median and Mode in Pandas

Suppose we have the following pandas DataFrame that contains information about points scored by various basketball players in four different games:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
                   'game1': [18, 22, 19, 14, 14, 11, 20, 28],
                   'game2': [5, 7, 7, 9, 12, 9, 9, 4],
                   'game3': [11, 8, 10, 6, 6, 5, 9, 12],
                   'game4': [9, 8, 10, 9, 14, 15, 10, 11]})
                   
#view DataFrame
print(df)

  player  game1  game2  game3  game4
0      A     18      5     11      9
1      B     22      7      8      8
2      C     19      7     10     10
3      D     14      9      6      9
4      E     14     12      6     14
5      F     11      9      5     15
6      G     20      9      9     10
7      H     28      4     12     11

We can use the following syntax to calculate the mean value of each numeric column:

#calculate mean of each numeric column
print(df.mean(numeric_only=True))

game1    18.250
game2     7.750
game3     8.375
game4    10.750
dtype: float64

From the output we can see:

• The mean value in the game1 column is 18.25.
• The mean value in the game2 column is 7.75.
• The mean value in the game3 column is 8.375.
• The mean value in the game4 column is 10.75.

We can then use the following syntax to calculate the median value of each numeric column:

#calculate median of each numeric column
print(df.median(numeric_only=True))

game1    18.5
game2     8.0
game3     8.5
game4    10.0
dtype: float64

From the output we can see:

• The median value in the game1 column is 18.5.
• The median value in the game2 column is 8.
• The median value in the game3 column is 8.5.
• The median value in the game4 column is 10.

We can then use the following syntax to calculate the mode of each numeric column:

#calculate mode of each numeric column
print(df.mode(numeric_only=True))

   game1  game2  game3  game4
0   14.0    9.0    6.0      9
1    NaN    NaN    NaN     10

From the output we can see:

• The mode in the game1 column is 14.
• The mode in the game2 column is 9.
• The mode in the game3 column is 6.
• The mode in the game4 column is 9 and 10

Note that the game4 column had two modes since there were two values that occurred most frequently in that column.

Note: You can also use the describe() function in pandas to generate more descriptive statistics for each column.

Additional Resources

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

How to Calculate the Mean by Group in Pandas
How to Calculate the Median by Group in Pandas
How to Calculate Mode by Group in Pandas