fetch row where column is equal to a value pandas
df.loc[df['column_name'] == 'value']fetch row where column is equal to a value pandas
df.loc[df['column_name'] == 'value']new dataframe based on certain row conditions
filterinfDataframe = dfObj[(dfObj['Sale'] > 30) & (dfObj['Sale'] < 33) ]new dataframe based on certain row conditions
# Create variable with TRUE if nationality is USA
american = df['nationality'] == "USA"
# Create variable with TRUE if age is greater than 50
elderly = df['age'] > 50
# Select all cases where nationality is USA and age is greater than 50
df[american & elderly]pandas select rows by condition in list
dataframe[dataframe['Stream'].isin(options)]python pandas dataframe conditional subset
In [722]: df[(df['C']==1) | df['B']]
Out[722]:
A B C
0 1 True 1
2 2 False 1
3 2 True 2
4 3 True 1
In [723]: df.query('C==1 or B==True')
Out[723]:
A B C
0 1 True 1
2 2 False 1
3 2 True 2
4 3 True 1
In [724]: df[df.eval('C==1 or B==True')]
Out[724]:
A B C
0 1 True 1
2 2 False 1
3 2 True 2
4 3 True 1Copyright © 2021 Codeinu
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