pandas replace values in column based on condition
In [41]:
df.loc[df['First Season'] > 1990, 'First Season'] = 1
df
Out[41]:
Team First Season Total Games
0 Dallas Cowboys 1960 894
1 Chicago Bears 1920 1357
2 Green Bay Packers 1921 1339
3 Miami Dolphins 1966 792
4 Baltimore Ravens 1 326
5 San Franciso 49ers 1950 1003replacing values in pandas dataframe
df['coloum'] = df['coloum'].replace(['value_1','valu_2'],'new_value')how to replace values in column pandas
# this will replace "Boston Celtics" with "Omega Warrior"
df.replace(to_replace ="Boston Celtics",
value ="Omega Warrior")replace values of pandas column
df.loc[df['column'] == 'column_value', 'column'] = 'new_column_value'how to replace values in column pandas
# importing pandas as pd
import pandas as pd
# Making data frame from the csv file
df = pd.read_csv("nba.csv")
# this will replace "Boston Celtics" and "Texas" with "Omega Warrior"
df.replace(to_replace =["Boston Celtics", "Texas"],
value ="Omega Warrior")pandas replace values from another dataframe
In [36]:
df['Group'] = df['Group'].map(df1.set_index('Group')['Hotel'])
df
Out[36]:
Date Group Family Bonus
0 2011-06-09 Jamel Laavin 456
1 2011-07-09 Frank Grendy 679
2 2011-09-10 Luxy Fantol 431
3 2011-11-02 Frank Gondow 569Copyright © 2021 Codeinu
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