How to Calculate Median in Python Pandas

To calculate median in pandas, we use the dataframe’s median() method. In Statistics, the median is the value that splits the data into half. 50% of the data is above this value and 50% of the data is below this value.

Examples-

Let’s create a dataset to work with.

import pandas as pd

data = {'Apple':[89, 89, 90, 110, 125, 84, 131, 123, 123, 140, 145, 145],
       'Orange': [46, 46, 50, 65, 63, 48, 110, 120, 60, 42, 47, 62],
       'Banana': [26, 30, 30, 25, 38, 22, 22, 36, 20, 27, 23, 34 ],
       'Mango': [80, 80, 90, 125, 130, 150, 140, 140, 135, 135, 80, 90]}

index = ['Jan','Feb','Mar','Apr','May','June','Jul','Aug','Sep','Oct','Nov','Dec']
df = pd.DataFrame(data, index=index)
df

1 . Calculate the median of the columns –

You can calculate the median of a single column like this

df['Apple'].median()

#output
123.0

Or you can calculate the median of all numeric columns like this

df.median()

#output
Apple     123.0
Orange     55.0
Banana     26.5
Mango     127.5
dtype: float64

2 . Calculate the median of the rows –

To calculate the median of the rows, we need to set the axis parameter to axis=1 or columns.

df.median(axis=1)

#output
Jan      63.0
Feb      63.0
Mar      70.0
Apr      87.5
May      94.0
June     66.0
Jul     120.5
Aug     121.5
Sep      91.5
Oct      88.5
Nov      63.5
Dec      76.0
dtype: float64