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Pandas compare two columns of different dataframe

Comparing two dataframe columns

comparison_column = np.where(df["col1"] == df["col2"], True, False)

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Source: kite.com

Pandas compare two columns of different dataframe

df1['priceDiff?'] = np.where(df1['Price1'] == df2['Price2'], 0, df1['Price1'] - df2['Price2'])

0

Source: datatofish.com

Pandas compare two columns of different dataframe

df3 = [(df2.type.isin(df1.type)) & (df1.value.between(df2.low,df2.high,inclusive=True))]
df1.join(df3)

0

Source: blog.softhints.com

Pandas compare two columns of different dataframe

df1['enh2'] = pd.Series((df2.type.isin(df1.type)) & (df1.value != df2.low)  | (df1.value + 1 == df2.high))

0

Source: blog.softhints.com

Pandas compare two columns of different dataframe

import numpy as np
df1['low_value'] = np.where(df1.value <= df2.low, 'True', 'False')

0

Source: blog.softhints.com

Pandas compare two columns of different dataframe

import numpy as np
df1['low_high_value'] = np.where((df1.value >= df2.low) & (df1.value <= df2.high), 'True', 'False')

0

Source: blog.softhints.com

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