pandas groupby sort descending order

Question

pandas groupby will by default sort   But I d like to change the sort order   How can I do this   I m guessing that I can t apply a sort method to the returned groupby object

User · Answer

As of Pandas 0 18 one way to do this is to use the sort index method of the grouped data    Here s an example   np random seed 1  n 10 df   pd DataFrame   mygroups    np random choice   dogs   cats   cows   chickens    size n                        data    np random randint 1000  size n     grouped   df groupby  mygroups   sort False  sum   grouped sort index ascending False  print grouped  data mygroups       dogs      1831 chickens  1446 cats       933   As you can see  the groupby column is sorted descending now  indstead of the default which is ascending

User · Answer

Similar to one of the answers above  but try adding  sort values   to your  groupby   will allow you to change the sort order   If you need to sort on a single column  it would look like this   df groupby  group    id   count   sort values ascending False    ascending False will sort from high to low  the default is to sort from low to high    Careful with some of these aggregations   For example  size   and  count   return different values since  size   counts NaNs       What is the difference between size and count in pandas

User · Answer

This kind of operation is covered under hierarchical indexing  Check out the examples here  When you groupby  you re making new indices  If you also pass a list through  agg    you ll get multiple columns  I was trying to figure this out and found this thread via google    It turns out if you pass a tuple corresponding to the exact column you want sorted on    Try this     generate toy data  ex   pd DataFrame np random randint 1 10 size  100 3    columns   features    AUC    recall       pass a tuple corresponding to which specific col you want sorted  In this case   mean  or  AUC  alone are not unique   ex groupby  features   agg   mean   std    sort values   AUC    mean      This will output a df sorted by the AUC-mean column only

User · Answer

Do your groupby  and use reset index   to make it back into a DataFrame  Then sort    grouped   df groupby  mygroups   sum   reset index   grouped sort values  mygroups   ascending False

User · Answer

You can do a sort values   on the dataframe before you do the groupby  Pandas preserves the ordering in the groupby   In  44   d head 10  Out 44                 name transcript  exon 0  ENST00000456328          2     1 1  ENST00000450305          2     1 2  ENST00000450305          2     2 3  ENST00000450305          2     3 4  ENST00000456328          2     2 5  ENST00000450305          2     4 6  ENST00000450305          2     5 7  ENST00000456328          2     3 8  ENST00000450305          2     6 9  ENST00000488147          1    11  for    a in d head 10  sort values   transcript    exon    groupby   name    transcript     print a                name transcript  exon 1  ENST00000450305          2     1 2  ENST00000450305          2     2 3  ENST00000450305          2     3 5  ENST00000450305          2     4 6  ENST00000450305          2     5 8  ENST00000450305          2     6               name transcript  exon 0  ENST00000456328          2     1 4  ENST00000456328          2     2 7  ENST00000456328          2     3               name transcript  exon 9  ENST00000488147          1    11

User · Answer

Other instance of preserving the order or sort by descending   In  97   import pandas as pd                                                                                                      In  98   df   pd DataFrame   name    A   B   C   A   B   C   A   B   C    Year   2003 2002 2001 2003 2002 2001 2003 2002 2001          Default groupby operation  In  99   for each in df groupby   Year     print each                                                                             2001     Year name 2  2001    C 5  2001    C 8  2001    C   2002     Year name 1  2002    B 4  2002    B 7  2002    B   2003     Year name 0  2003    A 3  2003    A 6  2003    A       order preserved  In  100   for each in df groupby   Year    sort False   print each                                                                 2003     Year name 0  2003    A 3  2003    A 6  2003    A   2002     Year name 1  2002    B 4  2002    B 7  2002    B   2001     Year name 2  2001    C 5  2001    C 8  2001    C   In  106   df groupby   Year    sort False  apply lambda x  x sort values   Year                             Out 106            Year name Year              2003 0  2003    A      3  2003    A      6  2003    A 2002 1  2002    B      4  2002    B      7  2002    B 2001 2  2001    C      5  2001    C      8  2001    C  In  107   df groupby   Year    sort False  apply lambda x  x sort values   Year     reset index drop True  Out 107       Year name 0  2003    A 1  2003    A 2  2003    A 3  2002    B 4  2002    B 5  2002    B 6  2001    C 7  2001    C 8  2001    C

[sorting] pandas groupby sort descending order

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