Reputation: 71
I wonder how to count accumulative unique values by groups in python?
Below is the dataframe example:
Group | Year | Type |
---|---|---|
A | 1998 | red |
A | 1998 | blue |
A | 2002 | red |
A | 2005 | blue |
A | 2008 | blue |
A | 2008 | yello |
B | 1998 | red |
B | 2001 | red |
B | 2003 | red |
C | 1996 | red |
C | 2002 | orange |
C | 2002 | red |
C | 2012 | blue |
C | 2012 | yello |
I need to create a new column by Column "Group". The value of this new column should be the accumulative unique values of Column "Type", accumulating by Column "Year".
Below is the dataframe I want. For example: (1)For Group A and in year 1998, I want to count the unique value of Type in year 1998, and there are two unique values of Type: red and blue. (2)For Group A and in year 2002, I want to count the unique value of Type in year 1998 and 2002, and there are also two unique values of Type: red and blue. (3)For Group A and in year 2008, I want to count the unique value of Type in year 1998, 2002, 2005, and 2008, and there are also four unique values of Type: red, blue, and yellow.
Group | Year | Type | Want |
---|---|---|---|
A | 1998 | red | 2 |
A | 1998 | blue | 2 |
A | 2002 | red | 2 |
A | 2005 | blue | 2 |
A | 2008 | blue | 3 |
A | 2008 | yello | 3 |
B | 1998 | red | 1 |
B | 2001 | red | 1 |
B | 2003 | red | 1 |
C | 1996 | red | 1 |
C | 2002 | orange | 2 |
C | 2002 | red | 2 |
C | 2012 | blue | 4 |
C | 2012 | yello | 4 |
One more thing about this dataframe: not all groups have values in the same years. For example, group A has two values in year 1998 and 2008, one value in year 2002 and 2005. Group B has values in year 1998, 2001, and 2003.
I wonder how to address this problem. Your great help means a lot to me. Thanks!
Upvotes: 1
Views: 67
Reputation: 862641
Use custom lambda function with factorize
in GroupBy.transform
:
f = lambda x: pd.factorize(x)[0]
df['Want1'] = df.groupby('Group', sort=False)['Type'].transform(f) + 1
print (df)
Group Year Type Want1
0 A 1998 red 1
1 A 2002 red 1
2 A 2005 blue 2
3 A 2008 blue 2
4 A 2009 yello 3
5 B 1998 red 1
6 B 2001 red 1
7 B 2003 red 1
8 C 1996 red 1
9 C 2002 orange 2
10 C 2008 blue 3
11 C 2012 yello 4
Upvotes: 1