comparison_column = np.where(df["col1"] == df["col2"], True, False)
df1['enh2'] = pd.Series((df2.type.isin(df1.type)) & (df1.value != df2.low) | (df1.value + 1 == df2.high))
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
df1['priceDiff?'] = np.where(df1['Price1'] == df2['Price2'], 0, df1['Price1'] - df2['Price2'])
df3 = [(df2.type.isin(df1.type)) & (df1.value.between(df2.low,df2.high,inclusive=True))]
df1.join(df3)
import numpy as np
df1['low_value'] = np.where(df1.value <= df2.low, 'True', 'False')
import numpy as np
df1['low_high_value'] = np.where((df1.value >= df2.low) & (df1.value <= df2.high), 'True', 'False')