CODEWITHSUNDEEP
pythonpandasseries
Miszka_R
Miszka_R

Reputation: 149

Adding new column to pandas df based on condition

I have the following dataset: 

ID   Asset   Boolean
1     "A"    True  
1     "B"    False  
1     "B"    False   
2     "A"    True
3     "A"    True
3     "A"    True
3     "B"    False
3     "B"    False
4     "A"    True
4     "A"    True
5     "A"    True
5     "B"    False

I want to add another column, which should evaluate to True only if all values in the column Boolean evaluate to True for the same ID. So something like this: 

ID   Asset   Boolean  Check
1     "A"    True     False
1     "B"    False    False
1     "B"    False    False
2     "A"    True     True
3     "A"    True     False
3     "A"    True     False
3     "B"    False    False
3     "B"    False    False
4     "A"    True     True
4     "A"    True     True
5     "A"    True     False
5     "B"    False    False

I want to keep the original dataset for filter options. I could not figure out, how to iterate through the Boolean column taking the ID column into consideration.

Upvotes: 0

Views: 70

Answers (1)

yatu
yatu

Reputation: 88226

You can GroupBy and transform with all:

df['Check'] = df.groupby('ID').Boolean.transform('all')

print(df)

    ID Asset  Boolean  Check
0    1     A     True  False
1    1     B    False  False
2    1     B    False  False
3    2     A     True   True
4    3     A     True  False
5    3     A     True  False
6    3     B    False  False
7    3     B    False  False
8    4     A     True   True
9    4     A     True   True
10   5     A     True  False
11   5     B    False  False

Upvotes: 4

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