如何将两列与不同的两个 csv 文件相乘,return 使用 Pandas 生成第一个 csv 文件

How to multiply two columns with different two csv file and return result in first csv file using Pandas

我有两个 CSV 文件,其中第一个 csv 文件包含价格列,第二个 csv 文件包含数量我试图将这两列相乘并将结果保存在第一个 csv 的新列中

First.csv

Code    Description                                Unit    Price
110101  STATIONARY BICYCLE INDOOR USE               SET    120.25
110106  TREADMILL EXERCISE MACHINE, ELEC. AC110V    SET    950.22
110107  TREADMILL EXERCISE MACHINE, ELEC. AC220V    SET    1000 
110110  EXERCISER ROWING INDOOR USE                 SET    450
110120  BARBELL SET                                 SET    100

Second.csv

Code     Quantity
110106  210
110107  220
110110  230
110120  240
110122  250

预期输出是

First.csv

Code    Description                                 Unit   Price    Total
110101  STATIONARY BICYCLE INDOOR USE               SET    120.25   25252.5
110106  TREADMILL EXERCISE MACHINE, ELEC. AC110V    SET    150.22   33048.4
110107  TREADMILL EXERCISE MACHINE, ELEC. AC220V    SET    100      23000
110110  EXERCISER ROWING INDOOR USE                 SET    40       9600
110120  BARBELL SET                                 SET    100      25000

我只能读取文件

import pandas as pd

df = pd.read_csv("QuoteCSV.csv", parse_dates=True)
print(df)
df1=pd.read_csv("itemcode.csv",index_col="Price", parse_dates=True)
print(df1)

已更新:

   import pandas as pd

    a = pd.read_csv("itemcode.csv")
    b = pd.read_csv("QuoteCSV.csv")
    b = b.dropna(axis=1)
    merged = a.merge(b, on='Code')
    merged.to_csv("result.csv", index=False)
    c = pd.read_csv("result.csv")
    c['Total'] = c['Price'] * c['Quantity']

但它没有return任何结果

使用map

First.assign(
    Total=First.Price * First.Code.map(dict(zip(Second.Code, Second.Quantity))))

试试这个作品

df["Total"]=df['Price'].multiply(df1['Quantity'], axis=0)
print(df)