Conditional operation on one column of Pandas DF based on value of another column

Question

I have the pandas dataframe below with 2 columns.

df = pd.DataFrame({'quantity':[15, 30, 35, 20], 'sign':[1,1,2,1]})

I want to apply a conditional statement and multiply the quantity value in each row by -1 if the corresponding sign value in that row is equal to 2. I don't want to create a new column. I just want to apply this to the quantity column.

I have tried using .loc and .apply(lamda x:) , but I must not be applying them correctly. Any help is appreciated.

Answer 1

Use DataFrame.loc with mask by Series.eq for equality and multiple by scalar:

df = pd.DataFrame({'quantity':[15, 30, 35, 20], 'sign':[1,1,2,1]})

df.loc[df['sign'].eq(2), 'quantity'] *=  - 1
print (df)
   quantity  sign
0        15     1
1        30     1
2       -35     2
3        20     1