Pandas.DataFrame: Create a new column, using one column from current df and by looking up one column-CodePudding

Hi I'm a new user for python / Pandas. Please help me with Pandas.DataFrame (and perhaps apply methods). I have two DataFrames, examples as follows. I would like to create a new column df_products['Sales Revenue'] by looking up the unit price of each product, times the df_products['Qty Sold']. How do I do that properly? Thank you.

# Pandas DataFrame example questions

import pandas as pd

products = ({
    'Product': ['A', 'B', 'C', 'D'],
    'Qty Sold': [10, 15, 22, 40]
})

prices =({
    'Product': ['A', 'B', 'C', 'D', 'E', 'F', 'G'],
    'Unit Price': [3.20, 3.40, 2.20, 11.00, 8.05, 9.30, 4.00]
})

df_products = pd.DataFrame(product)

df_prices = pd.DataFrame(prices)

df_products

    **Product** **Qty Sold** **Sales Revenue**(to create) 
0      A             10            =10*3.20
1      B             15            =15*3.40
2      C             22            ........
3      D             40            ........

df_prices
     Product    Unit Price
0        A      3.20
1        B      3.40
2        C      2.20
3        D      11.00
4        E      8.05
5        F      9.30
6        G      4.00

CodePudding user response：

df_products['Sales Revenue'] = df_products['Qty Sold'].mul(df_prices['Unit Price'])

CodePudding user response：

df_merged = df_products.merge(df_prices, on = 'Product')

df_products['Sales Revenue'] = df_merged['Qty Sold'] * df_merged['Unit Price']

I thinks that is not bad way but maybe better is possible.