PYTHON

comparing two dataframe columns

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

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))

compare multiple columns in pandas

df['Result'] = (df.iloc[:, 1:4].values < df[['E']].values).all(axis=1).astype(int)
print (df)
   A   B   C   D   E  Result
0  V  10   5  18  20       1
1  W   9  18  11  13       0
2  X   8   7  12   5       0
3  Y   7   9   7   8       0
4  Z   6   5   3  90       1

pandas compare two columns of different dataframe

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

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)

pandas compare two columns of different dataframe

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

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')