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Pandas is a powerful python library that provides a wide range of data analysis tools. To calculate the median of a set of values in Pandas, you can use the median() function. This function takes a numeric column as a parameter and returns the median value of that column. You can also use the describe() function to calculate more descriptive statistics, such as the mean and standard deviation. By following these simple steps, you can easily calculate the median of a column in Pandas.
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