Comparing Columns in a Pandas Dataframe

Question

I have a pandas data frame with racing results.

   Place BibNum Time 
0   1     2      5:50 
1   2     4      8:09 
2   3     7      10:27 
3   4     3      11:12 
4   5     1      12:13 
... 
34  1     5      2:03 
35  2     9      4:35 
36  3     7      5:36

What I would like to know is how can I get a count of how many times the BibNum showed up where the Place was 1, 2, 3 etc?

I know that I can do a "value_counts" but that is for how many times it shows up in a single column. I also looked into using numpy "where" but that is using a conditional like greater than or less than.

If you want a matrix: pd.crosstab(df['Place'], df['BibNum']), else df[['Place', 'BibNum']].value_counts() — mozway
– mozway, Commented Jan 11, 2023 at 5:27

eshirvana · Accepted Answer · 2023-01-11 03:06:46Z

1

IIUC , this is what you need:

out = df.groupby(['Place','BibNum']).size()

answered Jan 11, 2023 at 3:06

eshirvana

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