Assume you have a dataframe,
one two three 0 12 13 5 1 10 6 4 2 16 18 20 3 11 15 58
The result for storing the minimum value in new row and column is −
Add new column to store min value one two three min_value 0 12 13 5 5 1 10 6 4 4 2 16 18 20 16 3 11 15 58 11 Add new row to store min value one two three min_value 0 12 13 5 5 1 10 6 4 4 2 16 18 20 16 3 11 15 58 11 4 10 6 4 4
Solution
To solve this, we will follow the steps given below −
Define a dataframe
Calculate the minimum value in each column and store it as new column using the following step,
df['min_value'] = df.min(axis=1)
Find the minimum value in each row and store it as new row using the below step,
df.loc[len(df)] = df.min(axis=0)
Example
Let us see the following implementation to get a better understanding,
import pandas as pd
import numpy as np
data = [[12,13,5],[10,6,4],[16,18,20],[11,15,58]]
df = pd.DataFrame(data,columns=('one','two','three'))
print("Add new column to store min value")
df['min_value'] = df.min(axis=1)
print(df)
print("Add new row to store min value")
df.loc[len(df)] = df.min(axis=0)
print(df)Output
Add new column to store min value one two three min_value 0 12 13 5 5 1 10 6 4 4 2 16 18 20 16 3 11 15 58 11 Add new row to store min value one two three min_value 0 12 13 5 5 1 10 6 4 4 2 16 18 20 16 3 11 15 58 11 4 10 6 4 4