如何在条件中使用列的滞后值填充 Pandas 中的另一列

Question

I have a table like below:

I want to create another column(Check2) with below logic:

• If Check1 ==0 then Check2 = A
• Else Check2 = Check2(lagged value) - B(lagged) - C(lagged)

Expected Output should be like below -

I have written below code but its taking very long time(in hours) for 50000 records, please help

for i in range(len(df)): 
            if df.loc[i,'Check1'] == 0:
                df.loc[i,'Check2'] = df.loc[i,'Volume']
            else:
                df.loc[i,'Check2'] = df.loc[i-1,'Check2'] - df.loc[i-1,'B'] -df.loc[i-1,'C']

Answer 1

You are searching for: .shift() function. It does what you want