I am receiving a dataframe from source which looks like this:
date output
2023-01-25 A
2023-01-25 B
2023-01-25 B
2023-01-25 C
2023-01-25 C
2023-01-25 A
2023-01-25 B
...
2023-01-26 B
2023-01-26 C
2023-01-26 B
2023-01-26 B
2023-01-26 A
2023-01-26 C
2023-01-26 B
...
2023-01-27 C
2023-01-27 A
2023-01-27 A
2023-01-27 C
2023-01-27 B
2023-01-27 B
For my pipeline I need to transform this data.
After using df.groupby('Date').output.value_counts()
I was able to get following result:
Date output
2023-01-25 A 52
B 28
C 42
2023-01-26 A 47
B 32
C 36
2023-01-27 A 23
B 67
C 35
But for my pipeline I need dataframe in following structure:
Date A B C
2023-01-25 52 28 42
2023-01-26 47 32 36
2023-01-27 23 67 35
How can I store all these value counts to its respective column so result looks like above?