How to get the last N rows of a pandas DataFrame

Question

I have pandas dataframe df1 and df2  df1 is vanila dataframe  df2 is indexed by  STK ID   amp   RPT Date       gt  gt  gt  df1     STK ID  RPT Date  TClose   sales  discount 0   000568  20060331    3 69   5 975       NaN 1   000568  20060630    9 14  10 143       NaN 2   000568  20060930    9 49  13 854       NaN 3   000568  20061231   15 84  19 262       NaN 4   000568  20070331   17 00   6 803       NaN 5   000568  20070630   26 31  12 940       NaN 6   000568  20070930   39 12  19 977       NaN 7   000568  20071231   45 94  29 269       NaN 8   000568  20080331   38 75  12 668       NaN 9   000568  20080630   30 09  21 102       NaN 10  000568  20080930   26 00  30 769       NaN   gt  gt  gt  df2                  TClose   sales  discount  net sales    cogs STK ID RPT Date                                              000568 20060331    3 69   5 975       NaN      5 975   2 591        20060630    9 14  10 143       NaN     10 143   4 363        20060930    9 49  13 854       NaN     13 854   5 901        20061231   15 84  19 262       NaN     19 262   8 407        20070331   17 00   6 803       NaN      6 803   2 815        20070630   26 31  12 940       NaN     12 940   5 418        20070930   39 12  19 977       NaN     19 977   8 452        20071231   45 94  29 269       NaN     29 269  12 606        20080331   38 75  12 668       NaN     12 668   3 958        20080630   30 09  21 102       NaN     21 102   7 431   I can get the last 3 rows of df2 by    gt  gt  gt  df2 ix -3                    TClose   sales  discount  net sales    cogs STK ID RPT Date                                              000568 20071231   45 94  29 269       NaN     29 269  12 606        20080331   38 75  12 668       NaN     12 668   3 958        20080630   30 09  21 102       NaN     21 102   7 431   while df1 ix -3   give all the rows     gt  gt  gt  df1 ix -3       STK ID  RPT Date  TClose   sales  discount 0   000568  20060331    3 69   5 975       NaN 1   000568  20060630    9 14  10 143       NaN 2   000568  20060930    9 49  13 854       NaN 3   000568  20061231   15 84  19 262       NaN 4   000568  20070331   17 00   6 803       NaN 5   000568  20070630   26 31  12 940       NaN 6   000568  20070930   39 12  19 977       NaN 7   000568  20071231   45 94  29 269       NaN 8   000568  20080331   38 75  12 668       NaN 9   000568  20080630   30 09  21 102       NaN 10  000568  20080930   26 00  30 769       NaN   Why   How to get the last 3 rows of df1  dataframe without index    Pandas 0 10 1

User · Accepted Answer

Don t forget DataFrame tail  e g  df1 tail 10

User · Answer

How to get the last N rows of a pandas DataFrame    If you are slicing by position    getitem    i e   slicing with    works well  and is the most succinct solution I ve found for this problem    pd   version      0 24 2   df   pd DataFrame   A   list  aaabbbbc     B   np arange 1  9    df     A  B 0  a  1 1  a  2 2  a  3 3  b  4 4  b  5 5  b  6 6  b  7 7  c  8     df -3       A  B 5  b  6 6  b  7 7  c  8   This is the same as calling df iloc -3    for instance  iloc internally delegates to   getitem        As an aside  if you want to find the last N rows for each group  use groupby and GroupBy tail   df groupby  A   tail 2      A  B 1  a  2 2  a  3 5  b  6 6  b  7 7  c  8

User · Answer

This is because of using integer indices  ix selects those by label over -3 rather than position  and this is by design  see integer indexing in pandas  gotchas       In newer versions of pandas prefer loc or iloc to remove the ambiguity of ix as position or label   df iloc -3     see the docs   As Wes points out  in this specific case you should just use tail

[python] How to get the last N rows of a pandas DataFrame?

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