Calculate Mean, Median, Mode with Pandas

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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 function in pandas to generate more descriptive statistics for each column.