Python Pandas replicate rows in dataframe

Question

If the data look like   Store Dept Date Weekly Sales IsHoliday 1 1 2010-02-05 24924 5 FALSE 1 1 2010-02-12 46039 49 TRUE 1 1 2010-02-19 41595 55 FALSE 1 1 2010-02-26 19403 54 FALSE 1 1 2010-03-05 21827 9 FALSE 1 1 2010-03-12 21043 39 FALSE 1 1 2010-03-19 22136 64 FALSE 1 1 2010-03-26 26229 21 FALSE 1 1 2010-04-02 57258 43 FALSE   And I wanna duplicate rows with IsHoliday equal to TRUE  I can do   is hol   df  IsHoliday      True df try   df is hol  df df append df try 10    But is there a better way to do this as I need to duplicate holiday rows by 5 times  and I have to append 5 times if using above way

User · Accepted Answer

You can put df try inside a list and then do what you have in mind    gt  gt  gt  df append  df try  5 ignore index True       Store  Dept       Date  Weekly Sales IsHoliday 0       1     1 2010-02-05      24924 50     False 1       1     1 2010-02-12      46039 49      True 2       1     1 2010-02-19      41595 55     False 3       1     1 2010-02-26      19403 54     False 4       1     1 2010-03-05      21827 90     False 5       1     1 2010-03-12      21043 39     False 6       1     1 2010-03-19      22136 64     False 7       1     1 2010-03-26      26229 21     False 8       1     1 2010-04-02      57258 43     False 9       1     1 2010-02-12      46039 49      True 10      1     1 2010-02-12      46039 49      True 11      1     1 2010-02-12      46039 49      True 12      1     1 2010-02-12      46039 49      True 13      1     1 2010-02-12      46039 49      True

User · Answer

Other way is using concat   function   import pandas as pd  In  603   df   pd DataFrame   col1  list  abc    col2  range 3   index   range 3    In  604   df Out 604      col1  col2 0    a     0 1    b     1 2    c     2  In  605   pd concat  df  3  ignore index True    Ignores the index Out 605      col1  col2 0    a     0 1    b     1 2    c     2 3    a     0 4    b     1 5    c     2 6    a     0 7    b     1 8    c     2  In  606   pd concat  df  3  Out 606      col1  col2 0    a     0 1    b     1 2    c     2 0    a     0 1    b     1 2    c     2 0    a     0 1    b     1 2    c     2

User · Answer

Appending and concatenating is usually slow in Pandas so I recommend just making a new list of the rows and turning that into a dataframe  unless appending a single row or concatenating a few dataframes     import pandas as pd  df   pd DataFrame    1 1  2010-02-05  24924 5 False    1 1  2010-02-12  46039 49 True    1 1  2010-02-19  41595 55 False    1 1  2010-02-26  19403 54 False    1 1  2010-03-05  21827 9 False    1 1  2010-03-12  21043 39 False    1 1  2010-03-19  22136 64 False    1 1  2010-03-26  26229 21 False    1 1  2010-04-02  57258 43 False     columns   Store   Dept   Date   Weekly Sales   IsHoliday     temp df      for row in df itertuples index False       if row IsHoliday          temp df extend  list row   5      else          temp df append list row    df   pd DataFrame temp df  columns df columns

User · Answer

This is an old question  but since it still comes up at the top of my results in Google  here s another way   import pandas as pd import numpy as np  df   pd DataFrame   col1  list  abc    col2  range 3   index   range 3     Say you want to replicate the rows where col1  b     reps    3 if val   b  else 1 for val in df col1  df loc np repeat df index values  reps     You could replace the 3 if val   b  else 1 in the list interpretation with another function that could return 3 if val   b  or 4 if val   c  and so on  so it s pretty flexible

User · Answer

df   df try for i in range 4      df   df append df try     Here  we have df try times 5  df   df append df     Here  we have df try times 10

[python] Python Pandas replicate rows in dataframe

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