Python Pandas Map function | Zip | Use of python dictionary for mapping the values of a column
Python Pandas Map function | Zip | Use of python dictionary for mapping the values of a column
Python for Machine Learning - Session # 92
Topic to be covered - How to map dataset column using map function.
The map() function is used to map values of Series according to input correspondence.
Used for substituting each value in a Series with another value, that may be derived from a function, a dict or a Series.
Code Starts Here
===============
import pandas as pd
df = pd.DataFrame()
df['ID'] = [1111,2222,3333,4444,5555]
df['Name'] = ['Venkat','Sridhar','Shaqib','Nitin','Dupesh']
df['City'] = ['Hyderabad','Kolkata','Mumbai','Bangalore','Jaipur']
city_to_state = {'Hyderabad' :'Telangana',
'Kolkata':'West Bengal',
'Jaipur': ' Rajasthan',
'Bangalore': 'Karnataka',
'Mumbai': 'Maharastra'}
df['State'] = df['City'].map(city_to_state)
df1 = pd.read_excel('city-state.xlsx',0)
df2 = pd.read_excel('city-state.xlsx',1)
city_to_state1 = dict(zip(df2.City,df2.State))
df1['State'] = df1['City'].map(city_to_state1)
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