Add a new column with counter to a df based on an existing column
The data frame I have:
Column A | Column B |
---|---|
A | 1 |
na | 4 |
na | 5 |
na | 6 |
B | 2 |
na | 4 |
na | 6 |
na | 7 |
na | 8 |
C | 6 |
na | 1 |
na | 5 |
I am trying to loop through data frame using Python and create a new column C based on Column A's value. Output should look like this;
Column A | Column B | Column C |
---|---|---|
A | 1 | 1 |
na | 4 | 1 |
na | 5 | 1 |
na | 6 | 1 |
B | 2 | 2 |
na | 4 | 2 |
na | 6 | 2 |
na | 7 | 2 |
na | 8 | 2 |
A | 6 | 3 |
na | 1 | 3 |
na | 5 | 3 |
Basically adding a counter in column C when there is a new value in Column A after NAs(even if the value in Column A is same as the previous value; in this eg. A comes twice but the counter gives 1st A value 1 and when it again comes then it gives it a value 3).
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