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 1003how to replace values in column pandas
# this will replace "Boston Celtics" with "Omega Warrior"
df.replace(to_replace ="Boston Celtics",
value ="Omega Warrior")pandas conditional replace values in a series
# np.where function works as follows:
import numpy as np
# E.g. 1 - Set column values based on if another column is greater than or equal to 50
df['X'] = np.where(df['Y'] >= 50, 'yes', 'no')
# E.g. 2 - Replace values over 20000 with 0, otherwise keep original value
df['my_value'] = np.where(df.my_value > 20000, 0, df.my_value)replace values in a column by condition python
df.loc[df['employrate'] > 70, 'employrate'] = 7how 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")Change value of all cells by a 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 1003Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
