Get the row corresponding to the max in pandas GroupBy [duplicate]

by

Check with sort_values +drop_duplicates

df.sort_values('B').drop_duplicates(['A'],keep='last')
Out[127]: 
   A  B  C
1  1  1  b
3  2  3  d

More Related Contents:

  1. Get statistics for each group (such as count, mean, etc) using pandas GroupBy?
  2. How to access pandas groupby dataframe by key
  3. Group dataframe and get sum AND count?
  4. get first and last values in a groupby
  5. Pandas groupby and aggregation output should include all the original columns (including the ones not aggregated on)
  6. How to get number of groups in a groupby object in pandas?
  7. How can I pivot a dataframe?
  8. How do I Pandas group-by to get sum?
  9. Aggregation in Pandas
  10. Groupby value counts on the dataframe pandas
  11. GroupBy pandas DataFrame and select most common value
  12. Converting a Pandas GroupBy output from Series to DataFrame
  13. Pandas GroupBy.apply method duplicates first group
  14. Python: get a frequency count based on two columns (variables) in pandas dataframe some row appers
  15. Pandas dataframe get first row of each group
  16. Pandas groupby multiple fields then diff
  17. Pandas groupby mean – into a dataframe?
  18. How to loop over grouped Pandas dataframe?
  19. group by pandas dataframe and select latest in each group
  20. How to drop duplicates based on two or more subsets criteria in Pandas data-frame
  21. Pandas get frequency of item occurrences in a column as percentage [duplicate]
  22. Python Pandas How to assign groupby operation results back to columns in parent dataframe?
  23. How can I use cumsum within a group in Pandas?
  24. why does pandas rolling use single dimension ndarray
  25. Add a sequential counter column on groups to a pandas dataframe
  26. pandas divide row value by aggregated sum with a condition set by other cell
  27. How to summarize on different groupby combinations?
  28. how to convert monthly data to quarterly in pandas
  29. Get frequency of item occurrences in a column as percentage [duplicate]
  30. When is it appropriate to use df.value_counts() vs df.groupby(‘…’).count()?

Leave a Comment