pandas dataframe column based on multiple columns code example

Example 1: dataframe groupby multiple columns

grouped_multiple = df.groupby(['Team', 'Pos']).agg({'Age': ['mean', 'min', 'max']})
grouped_multiple.columns = ['age_mean', 'age_min', 'age_max']
grouped_multiple = grouped_multiple.reset_index()
print(grouped_multiple)

Example 2: python pandas selecting multiple columns

# Import pandas package 
import pandas as pd 
  
# Define a dictionary containing employee data 
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'], 
        'Age':[27, 24, 22, 32], 
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'], 
        'Qualification':['Msc', 'MA', 'MCA', 'Phd']} 
  
# Convert the dictionary into DataFrame  
df = pd.DataFrame(data) 
  
# select two columns 
df[['Name', 'Qualification']]