I have a python dataframe that looks like the following:
This dataframe has been sorted in descending order by 'transaction_count'
. I want to create another column in that dataframe called 'rank'
that contains the count of occurrences of cust_ID
. My desired output would look something like the following:
For cust_ID = 1234
with transaction_count = 4
, the rank would be 1, for the next appearance of cust_ID = 1234
, the rank would be 2 and so on.
I tried the following among other things:
df['rank'] = df["cust_ID"].value_counts() df.head(10)
But the rank column gets created as all NaN values
Any suggestions on how to approach this would be greatly appreciated!
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Answer
df['rank'] = df.groupby('cust_ID').cumcount() + 1 print(df['rank'])
Output
0 1 1 2 2 1 3 1 4 2 5 3 Name: rank, dtype: int64