Can you make two columns equal if a condition is met

Asked Jul 23 '20 at 12:38

Active Jul 23 '20 at 12:39

Viewed 20 times

df1 = 
Profit, Qualified 
1000, TRUE 
2000, FALSE 
3000, FALSE 
4000, TRUE

Desired output:

df1= 
Profit, Qualified, Qualified Profit 
1000, TRUE, 1000 
2000, FALSE, 0 
3000, FALSE, 0 
4000, TRUE, 4000

Two lines of code i have tried:

df1['Qualified Profit'] = df1['Profit'].where(df1['Qualified'] == "TRUE")

df1['Qualified Profit'] = df1.apply(lambda x: x['Profit'] if x["Qualified"]=="TRUE" else '0', axis=1)

edited Jul 23 '20 at 12:39

Wondercricket

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asked Jul 23 '20 at 12:38

Hedge_hog

Use `df1['Qualified Profit'] = np.where(df1['Qualified'] == "TRUE", df1['Profit'], 0)` – jezrael Jul 23 '20 at 12:40
I have tried this but I get an error 'invalid type comparison' – Hedge_hog Jul 23 '20 at 12:43
ok, so need `df1['Qualified Profit'] = np.where(df1['Qualified'], df1['Profit'], 0)` – jezrael Jul 23 '20 at 12:44
How did it know to pick the 'TRUE' values ? – Hedge_hog Jul 23 '20 at 12:47
If use `df1['Qualified']` here is is same like `df1['Qualified'] == True ` – jezrael Jul 23 '20 at 12:48

Can you make two columns equal if a condition is met

0 Answers0