creating new column in pandas based on if and existing column

I have found different answers to this question but none pulling data from existing column.
Let’s say I have DataFrame

purchase=
{'date':['11/03/2021','12/03/2021','14/03/2021','11/03/2021'],
'price':[300, 400,200, 200],
'currency':['eur', 'usd','usd','usd'],
'qty':[200, 300, 400, 500],
'salesmanA':['Jack', 'x', "Mike", 'x'],
'salesmanB':['x', 'John', "x", 'David']}
df=pd.DataFrame(purchase)

I want to set a new column df[‘salessup’] which should be equal to SalesmanA if its value is not ‘x’, and if it’s x to salesmanB
new columns should be like [‘salessup’]=[‘Jack’,’John’,’Mike’,’David’]
thank you in advance.

>Solution :

Try np.where

df['out'] = np.where(df.salesmanA=='x',df.salesmanB,df.salesmanA)
df
Out[450]: 
         date  price currency  qty salesmanA salesmanB    out
0  11/03/2021    300      eur  200      Jack         x   Jack
1  12/03/2021    400      usd  300         x      John   John
2  14/03/2021    200      usd  400      Mike         x   Mike
3  11/03/2021    200      usd  500         x     David  David

Leave a Reply