How to define multiple column values and call using .map function?

Question

Using the code below I need to place the values ("Right Data, Incorrect Data...) into a column "Assessment" when the if condition satisfies based on x and y values. But I am getting the below error

AttributeError: 'DataFrame' object has no attribute 'map'

def variable(x,y):
    x = df['Volume']
    y = df['Turnover']
    if df[(x==0) & (y==0)]:
        return 'Right Data'
    if df[(x>0) & (y>0)]:
        return 'Right Data'
    if df[(x<0) & (y<0)]:
        return 'Right Data'
    if df[(x>0) & (y<0)]:
        return 'Incorrect Data'
    if df[(x<0) & (y>0)]:
        return 'Incorrect Data'
    if df[(x!=0) & (y==0)]:
        return 'Incorrect Data'
    if df[(x==0) & (y!=0)]:
        return 'Incorrect Data'
    if df[(x==0) & (y.isnull())]:
        return 'Missing Data'
    if df[(x=='Nan') & (y!=0)]:
        return 'Missing Data'
test = df[['Volume','Turnover']]
test2 = test.map(variable)
df['Assessment'] = test2

use test.applymap(variable) pandas.pydata.org/pandas-docs/stable/generated/… — Piotrek
– Piotrek, Commented Aug 1, 2018 at 8:54
it is giving below TypeError: ("variable() missing 1 required positional argument: 'y'", 'occurred at index Volume') — Harsha
– Harsha, Commented Aug 1, 2018 at 8:59
yes I did the way you suggested I got the above mentioned error after doing that, I am not sure how to call both x and y using the map function? — Harsha
– Harsha, Commented Aug 1, 2018 at 9:02
if it is only one column variable X then we can do it the way you suggested, but in this case I need to check 2 columns simultaneously and then change the values in new column when both columns satisfies the condition — Harsha
– Harsha, Commented Aug 1, 2018 at 9:15

Piotrek · Accepted Answer · 2018-08-01 09:07:16Z

0

You can try using lambda for this:

df['Assessment'] = df.apply(lambda x: variable(x['Volume'], x['Turnover']), axis=1)

Source:

python pandas- apply function with two arguments to columns

answered Aug 1, 2018 at 9:07

Piotrek

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