努力将值插入新列

Question

我遇到了一个问题。我在我的 csv 文件中创建了一个新列，我正在尝试在列中添加值，但不知道要使用哪些函数。该列名为“Discounted_Price”，我不得不提到福特和雪佛兰的价格有百分之十的折扣。 这是到目前为止的代码：

CarPrices_discount=pd.read_csv('C:\\Users\\Jon\\Desktop\\data science\\car_prices.csv')
CarPrices_discount
CarPrices_discount.insert(15,'Discounted_Price',np.nan)
CarPrices_discount.head()
Ford_Chev=CarPrices_discount[(CarPrices_discount.make=='Ford')|(CarPrices_discount.make=='Chevrolet')]  
#Ford_Chev['Discounted_Price']=Ford_Chev['sellingprice']*0.9
CarPrices_discount.loc[CarPrices_discount.Ford_Chev['Discounted_Price']=Ford_Chev['sellingprice']*0.9

我知道最后一行是错误的，但我不知道如何用 dataframe.loc 插入它。

Answer 1

数据：

>>> import pandas as pd
>>> import numpy as np
>>> CarPrices_discount = pd.DataFrame({"make" : ['Chevrolet', 'a', 'b', 'Ford', 'Chevrolet', 'Ford'],
                                       "sellingprice" : [900, 10,20,20,40,30]})
>>> CarPrices_discount

    make        sellingprice
0   Chevrolet   900
1   a           10
2   b           20
3   Ford        20
4   Chevrolet   40
5   Ford        30


>>> CarPrices_discount['Discounted_Price'] = CarPrices_discount.apply(lambda x:x.sellingprice*0.9 if x.make in ['Ford', 'Chevrolet'] else np.nan, axis=1)
>>> CarPrices_discount
    make        sellingprice    Discounted_Price
0   Chevrolet   900             810.0
1   a           10              NaN
2   b           20              NaN
3   Ford        20              18.0
4   Chevrolet   40              36.0
5   Ford        30              27.0

Answer 2

好的，我找到了某种答案，但它存在很大缺陷：

Ford_Chev=CarPrices_discount[(CarPrices_discount.make=='Ford'(CarPrices_discount.make=='Chevrolet')] print(Ford_Chev) 
  Ford_Chev['Discounted_Price']=Ford_Chev["sellingprice"]*0.9 
  print(Ford_Chev)