How to delete the last row of data of a pandas dataframe

Question

I think this should be simple  but I tried a few ideas and none of them worked   last row   len DF  DF   DF drop DF index last row      lt -- fail    I tried using negative indices but that also lead to errors  I must still be misunderstanding something basic

User · Answer

Just use indexing df iloc  -1     That s why iloc exists  You can also use head or tail

User · Answer

For more complex DataFrames that have a Multi-Index  say  quot Stock quot  and  quot Date quot   and one wants to remove the last row for each Stock not just the last row of the last Stock  then the solution reads    To remove last n rows df   df groupby level  Stock   apply lambda x  x head -1   reset index 0  drop True     To remove first n rows df   df groupby level  Stock   apply lambda x  x tail -1   reset index 0  drop True   As the groupby   is adding an additional level to the Multi-Index we just drop it at the end using reset index    The resulting df keeps the same type of Multi-Index as before the operation

User · Answer

Surprised nobody brought this one up     To remove last n rows df head -n     To remove first n rows df tail -n    Running a speed test on a DataFrame of 1000 rows shows that slicing and head tail are  6 times faster than using drop    gt  gt  gt   timeit df  -1  125   s    132 ns per loop  mean    std  dev  of 7 runs  10000 loops each    gt  gt  gt   timeit df head -1  129   s    1 18   s per loop  mean    std  dev  of 7 runs  10000 loops each    gt  gt  gt   timeit df drop df tail 1  index  751   s    20 4   s per loop  mean    std  dev  of 7 runs  1000 loops each

User · Answer

stats   pd read csv  C   py  programs  second pandas  ex csv     The Output of stats          A            B          C 0   0 120064    0 785538    0 465853 1   0 431655    0 436866    0 640136 2   0 445904    0 311565    0 934073 3   0 981609    0 695210    0 911697 4   0 008632    0 629269    0 226454 5   0 577577    0 467475    0 510031 6   0 580909    0 232846    0 271254 7   0 696596    0 362825    0 556433 8   0 738912    0 932779    0 029723 9   0 834706    0 002989    0 333436   just use skipfooter 1     skipfooter   int  default 0      Number of lines at bottom of file to skip   stats 2   pd read csv  C   py  programs  second pandas  ex csv   skipfooter 1  engine  python     Output of stats 2         A          B            C 0   0 120064    0 785538    0 465853 1   0 431655    0 436866    0 640136 2   0 445904    0 311565    0 934073 3   0 981609    0 695210    0 911697 4   0 008632    0 629269    0 226454 5   0 577577    0 467475    0 510031 6   0 580909    0 232846    0 271254 7   0 696596    0 362825    0 556433 8   0 738912    0 932779    0 029723

User · Answer

drop returns a new array so that is why it choked in the og post  I had a similar requirement to rename some column headers and deleted some rows due to an ill formed csv file converted to Dataframe  so after reading this post I used   newList   pd DataFrame newList  newList columns     Area    Price   print newList    newList   newList drop 0    newList   newList drop len newList   newList   newList 1 -1  print newList    and it worked great  as you can see with the two commented out lines above I tried the drop    method and it work but not as kool and readable as using  n -n   hope that helps someone  thanks

User · Answer

DF  -n    where n is the last number of rows to drop    To drop the last row    DF   DF  -1

User · Answer

Since index positioning in Python is 0-based  there won t actually be an element in index at the location corresponding to len DF   You need that to be last row   len DF  - 1   In  49   dfrm Out 49              A         B         C 0  0 120064  0 785538  0 465853 1  0 431655  0 436866  0 640136 2  0 445904  0 311565  0 934073 3  0 981609  0 695210  0 911697 4  0 008632  0 629269  0 226454 5  0 577577  0 467475  0 510031 6  0 580909  0 232846  0 271254 7  0 696596  0 362825  0 556433 8  0 738912  0 932779  0 029723 9  0 834706  0 002989  0 333436   10 rows x 3 columns   In  50   dfrm drop dfrm index len dfrm -1   Out 50              A         B         C 0  0 120064  0 785538  0 465853 1  0 431655  0 436866  0 640136 2  0 445904  0 311565  0 934073 3  0 981609  0 695210  0 911697 4  0 008632  0 629269  0 226454 5  0 577577  0 467475  0 510031 6  0 580909  0 232846  0 271254 7  0 696596  0 362825  0 556433 8  0 738912  0 932779  0 029723   9 rows x 3 columns    However  it s much simpler to just write DF  -1

User · Answer

To drop last n rows   df drop df tail n  index inplace True    drop last n rows   By the same vein  you can drop first n rows   df drop df head n  index inplace True    drop first n rows

[python] How to delete the last row of data of a pandas dataframe

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