You can use the median() function to find the median of one or more columns in a pandas DataFrame:

#find median value in specific column
df['column1'].median()

#find median value in several columns
df[['column1', 'column2']].median()

#find median value in every numeric column
df.median()

The following examples show how to use this function in practice with the following pandas DataFrame:

#create DataFrame
df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
                   'points': [25, pd.NA, 15, 14, 19, 23, 25, 29],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],
                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]})

#view DataFrame
df

	player	points	assists	rebounds
0	A	25	5	11
1	B	NA	7	8
2	C	15	7	10
3	D	14	9	6
4	E	19	12	6
5	F	23	9	5
6	G	25	9	9
7	H	29	4	12

Example 1: Find Median of a Single Column

The following code shows how to find the median value of a single column in a pandas DataFrame:

#find median value of points column
df['points'].median()

23.0

The median value in the points column is 23. 

Note that by default, the median() function ignores any missing values when calculating the median.

Example 2: Find Median of Multiple Columns

The following code shows how to find the median value of multiple columns in a pandas DataFrame:

#find median value of points and rebounds columns
df[['points', 'rebounds']].median()

points      23.0
rebounds     8.5
dtype: float64

Example 3: Find Median of All Numeric Columns

The following code shows how to find the median value of all numeric columns in a pandas DataFrame:

#find median value of all numeric columns
df.median()

points      23.0
assists      8.0
rebounds     8.5
dtype: float64