The median() function in pandas is used to obtain the median value of the values of a specified axis of the given DataFrame.
Mathematically, median can be defined as the value of a dataset that lies at the midpoint when all the values in the dataset are sorted in ascending or descending order.
The median() function takes the syntax shown below:
DataFrame.median(axis=NoDefault.no_default, skipna=True, numeric_only=None, **kwargs)
The median() function takes the following optional parameter values:
axis: This represents the name for the row (designated as 0 or `index') or the column (designated as 1 or columns) axis from which to take the median.skipna: This takes a Boolean value. It determines whether null values are to be excluded or not in the calculation of the median.numeric_only: This takes a Boolean value. It determines whether only float, int, or Boolean columns are included in the calculation.**kwargs: This is an additional keyword argument that can be passed to the function.# A code to illustrate the median() function in Pandas# importing the pandas libraryimport pandas as pd# creating a dataframedf = pd.DataFrame([[1,2,3,4,5],[1,7,5,9,0.5],[3,11,13,14,12]],columns=list('ABCDE'))# printing the dataframeprint(df)# obtaining the median value vertically across rowsprint(df.median())# obtaining the median value horizontally over columnsprint(df.median(axis="columns"))
pandas library.DataFrame df.df.median() function, we obtain the median values running downwards across the rows (axis 0). We print the result to the console.median() function, we obtain the median values running horizontally across columns (axis 1). We print the result to the console.