df[(df['Original Price'] != '0') & (df['Old Original Price'] != '0'), 'Price Difference'].index = df['Original Price'] - df['Old Original Price']
我目前正在嘗試比較資料框的兩列,如果它們的值不是 = 0,它們將創建一個新列并在兩個值之間進行減法
雖然我似乎不斷收到下面提到的錯誤
TypeError: '(Series([], dtype: bool), 'Price Difference')' is an invalid key
uj5u.com熱心網友回復:
你可以試試:
df.loc[((df['Original Price'] != '0') & (df['Old Original Price'] != '0')),'Price_Difference'] = df['Original Price'] - df['Old Original Price']
uj5u.com熱心網友回復:
我需要查看您的資料外觀的示例,以及列的資料型別是什么,但根據您提到的內容,我的建議如下:
df['Price Difference']= df['Original Price']
df.loc[((~df['Original Price'].isin(['0'])) & (~df['Old Original Price'].isin(['0']))), 'Price Difference']= df['Original Price'] - df['Old Original Price']
uj5u.com熱心網友回復:
嘗試這個
df[Price Difference] =df.apply(function,axis=1)
并在方法中撰寫邏輯
function(row):
{
if (row['Original Price'] != '0') & (row['Old Original Price'] !=
'0'):
return row['Original Price'] - row['Old Original Price']
}
轉載請註明出處,本文鏈接:https://www.uj5u.com/net/333954.html
