How to count accumulative unique values by groups in python?

Question

I wonder how to count accumulative unique values by groups in python?

Below is the dataframe example:

Group	Year	Type
A	1998	red
A	2002	red
A	2005	blue
A	2008	blue
A	2009	yello
B	1998	red
B	2001	red
B	2003	red
C	1996	red
C	2002	orange
C	2008	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: For group A and in Year 1998, the accumulative unique values of "Type" is 1. For group A and in Year 2005, the accumulative unique values of "Type" is 2. For group C and in Year 2012, the accumulative unique values of "Type" is 4.

| Group| Year| Type|Want|
|------|-----|-----|----|
|A|1998|red|1|
|A|2002|red|1|
|A|2005|blue|2|
|A|2008|blue|2|
|A|2009|yello|3|
|B|1998|red|1|
|B|2001|red|1|
|B|2003|red|1|
|C|1996|red|1|
|C|2002|orange|2|
|C|2008|blue|3|
|C|2012|yello|4|

One more thing about this dataframe: not all groups have values in the same years. For example, group A has values in year 1998,2002,2005, and 2008. 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!

Answer 1

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