pandas create a new column based on condition of two columns

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Courageous Cobra answered on May 14, 2020 Popularity 10/10 Helpfulness 4/10

answer pandas create a new column based on condition of two columns

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pandas create a new column based on condition of two columns

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conditions = [
    df['gender'].eq('male') & df['pet1'].eq(df['pet2']),
    df['gender'].eq('female') & df['pet1'].isin(['cat', 'dog'])
]

choices = [5,5]

df['points'] = np.select(conditions, choices, default=0)

print(df)
     gender      pet1      pet2  points
0      male       dog       dog       5
1      male       cat       cat       5
2      male       dog       cat       0
3    female       cat  squirrel       5
4    female       dog       dog       5
5    female  squirrel       cat       0
6  squirrel       dog       cat       0

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Source: stackoverflow.com

Tags: multiple-conditions pandas python two-columns

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Contributed on Dec 01 2020

Courageous Cobra

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Add new column based on condition on some other column in pandas.

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# np.where(condition, value if condition is true, value if condition is false)

df['hasimage'] = np.where(df['photos']!= '[]', True, False)
df.head()

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Source: www.dataquest.io

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Contributed on Aug 08 2021

LawlietL

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pandas create new column conditional on other columns

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# For creating new column with multiple conditions
conditions = [
    (df['Base Column 1'] == 'A') & (df['Base Column 2'] == 'B'),
    (df['Base Column 3'] == 'C')]
choices = ['Conditional Value 1', 'Conditional Value 2']
df['New Column'] = np.select(conditions, choices, default='Conditional Value 1')

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Source: Grepper

Tags: conditional cond

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Contributed on May 14 2020

Talented Toucan

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pandas create new column based on other columns

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import pandas as pd

# Create a sample DataFrame
data = {'A': [1, 2, 3],
        'B': [4, 5, 6]}
df = pd.DataFrame(data)

# Create a new column 'C' by summing values from columns 'A' and 'B'
df['C'] = df['A'] + df['B']

# Print the updated DataFrame
print(df)

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Source: Grepper

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Contributed on Sep 12 2023

YOU.com

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put two columns together in one column in pandas dataframe

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# First dataframe with three columns
dlist=["vx","vy","vz"]
df=pd.DataFrame(columns=dlist)
df["vx"]=df1["v2x"]
df["vy"]=df1["v2y"]
df["vz"]=df1["v2z"]
# second dataframe with three columns
dlist=["vx","vy","vz"]
df0=pd.DataFrame(columns=dlist)
df0["vx"]=df2["v1x"]
df0["vy"]=df2["v1y"]
df0["vz"]=df2["v1z"]
# Here with concat we can create new dataframe with garther both in one
# YOU CAN PUT SOME VALUES IN EACH AND CHECK IT
# WHAT INSIDE THE CONCAT MUST BE A LIST OF DATAFRAME
v = pd.concat([df,df0])

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Source: Grepper

Tags: dataframe data

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Contributed on Aug 05 2022

Itchy Iguana

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pandas create a new column based on condition of two columns

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pandas create a new column based on condition of two columns

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Add new column based on condition on some other column in pandas.

pandas create new column conditional on other columns

pandas create new column based on other columns

put two columns together in one column in pandas dataframe

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