How to Calculate Median in Python Pandas

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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

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