Python Pandas Column Value Increment Counter for Unique Values

Say I have a series like (assume this is a dataframe with many columns, but I only care about df["Key"] right now) :

Key
----
1234
1234
1234
5678
6789
7890
7890
6789
2345

How do I create a new column called "Counter" that increments matching values in "Key" ?, like the following :

Key     Counter
----    -------
1234       1
1234       2
1234       3
5678       1
6789       1
7890       1
7890       2
6789       2
2345       1

I don’t want a summary of the total count of each unique value…I know that you can get a value of unique counts by doing something like df["Key"].value_counts() or df.groupby('Key').count()

>Solution :

Use pd groupby cumcount:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.groupby.GroupBy.cumcount.html

which maps to 0-n, so optionally add 1 to the result:

out = df.groupby('Key').cumcount() + 1