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Python | Pandas DataFrame.where()

Travinth Dayalaeaswaran answered on December 3, 2020 Popularity 9/10 Helpfulness 4/10

answer Python | Pandas DataFrame.where()

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Python | Pandas DataFrame.where()

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# importing pandas package
import pandas as pd
  
# making data frame from csv file
data = pd.read_csv("cff.csv")
  
# sorting dataframe
data.sort_values("Team", inplace = True)
  
# making boolean series for a team name
filter = data["Team"]=="cff"
  
# filtering data
data.where(filter, inplace = True)
  
# display
data

Popularity 9/10 Helpfulness 4/10 Language python

Source: www.geeksforgeeks.org

Tags: pandas python

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Contributed on Jul 14 2022

Travinth Dayalaeaswaran

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pandas where

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# replaces values with other where condition is False
DataFrame.where(cond, other=nan, inplace=False, axis=None, level=None, errors='raise', try_cast=False)

import pandas as pd 
df = pd.DataFrame({'values':[1,2,3,4]})

df.where(df['values'] % 2 == 0, -1) # output : [-1, 2, -3, 4]

Popularity 10/10 Helpfulness 5/10 Language python

Source: pandas.pydata.org

Tags: pandas pa

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Contributed on Dec 03 2020

Anxious Axolotl

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pandas where

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-1

In [20]: df
Out[20]:
   A  B  C
0  1  2  1
1  2  3  0
2  3  4  0
3  4  5  1

# Note that df.C is a mask
# Note that this is np.where, not df.where. That is different.
In [21]: df['D'] = np.where(df.C, df.A, df.B)

In [22]: df
Out[22]:
   A  B  C  D
0  1  2  1  1
1  2  3  0  3
2  3  4  0  4
3  4  5  1  4

Popularity 10/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: pandas pa

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Contributed on Jun 01 2021

Important Impala

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Python | Pandas DataFrame.where()

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