I'm working on a DataFrame using pandas and I need to add a new column based on some conditions.
My DataFrame is:
discount tax total subtotal productid
3 0 20 13 002
10 3 106 94 003
46.49 6 21 20 004
I need to apply some conditions while adding a new column named as Class to the DataFrame.
Conditions are as follows: IF discount > 20 & total > 100 & tax == 0 then Class should be 1 otherwise it should be 0
Here's how I have tried:
def conditions(s):
if (s['discount'] > 20) and (s['tax'] == 0) and (s['total'] > 100):
return 1
else:
return 0
df_full['Class'] = df_full.apply(conditions, axis=1)
But it returns an error as:
TypeError: ("'>' not supported between instances of 'str' and 'int'", 'occurred at index 18')
How can I solve this issue?
help me, please!
Thanks in advance!
I suggest create boolean mask and cast to int, Trues are 1s and Falses are 0s, also change and to & for bitwise AND:
print (df_full)
discount tax total subtotal productid
0 3.00 0 20 13 002
1 40.00 0 106 94 003
2 46.49 6 21 20 004
You can also check all non numeric values:
print(df_full[pd.to_numeric(df_full['discount'], errors='coerce').isnull()]
#for convert to numeric - non numeric are convert to `NaN`s
df_full['discount'] = pd.to_numeric(df_full['discount'], errors='coerce')
df_full['Class'] = ((df_full['discount'] > 20) &
(df_full['tax'] == 0) &
(df_full['total'] > 100)).astype(int)
print (df_full)
discount tax total subtotal productid Class
0 3.00 0 20 13 002 0
1 40.00 0 106 94 003 1
2 46.49 6 21 20 004 0