Move column by name to front of table in pandas

Question

Here is my df                                Net   Upper   Lower  Mid  Zsore Answer option                                                 More than once a day          0    0 22   -0 12    2    65  Once a day                    0    0 32   -0 19    3    45 Several times a week          2    2 45    1 10    4    78 Once a week                   1    1 63   -0 40    6    65   How can I move a column by name   Mid   to the front of the table  index 0  This is what the result should look like                                Mid   Upper   Lower  Net  Zsore Answer option                                                 More than once a day          2   0 22   -0 12    0     65  Once a day                    3   0 32   -0 19    0     45 Several times a week          4   2 45    1 10    2     78 Once a week                   6   1 63   -0 40    1     65   My current code moves the column by index using df columns tolist   but I d like to shift it by name

User · Answer

Here is a generic set of code that I frequently use to rearrange the position of columns  You may find it useful   cols   df columns tolist   n   int cols index  Mid    cols    cols n     cols  n    cols n 1   df   df cols

User · Answer

We can use ix to reorder by passing a list   In  27     get a list of columns cols   list df    move the column to head of list using index  pop and insert cols insert 0  cols pop cols index  Mid     cols Out 27     Mid    Net    Upper    Lower    Zsore   In  28     use ix to reorder df   df ix    cols  df Out 28                         Mid Net  Upper   Lower  Zsore Answer option                                       More than once a day    2  0   0 22   -0 12      65 Once a day              3  0   0 32   -0 19      45 Several times a week    4  2   2 45    1 10      78 Once a week             6  1   1 63   -0 40      65   Another method is to take a reference to the column and reinsert it at the front   In  39   mid   df  Mid   df drop labels   Mid    axis 1 inplace   True  df insert 0   Mid   mid  df Out 39                         Mid Net  Upper   Lower  Zsore Answer option                                       More than once a day    2  0   0 22   -0 12      65 Once a day              3  0   0 32   -0 19      45 Several times a week    4  2   2 45    1 10      78 Once a week             6  1   1 63   -0 40      65   You can also use loc to achieve the same result as ix will be deprecated in a future version of pandas from 0 20 0 onwards   df   df loc    cols

User · Answer

To reorder the rows of a DataFrame just use a list as follows   df   df   Mid    Net    Upper    Lower    Zsore      This makes it very obvious what was done when reading the code later   Also use   df columns Out 1   Index   Net    Upper    Lower    Mid    Zsore    dtype  object     Then cut and paste to reorder     For a DataFrame with many columns  store the list of columns in a variable and pop the desired column to the front of the list  Here is an example   cols    str col name  for col name in range 1001   data   np random rand 10 1001  df   pd DataFrame data data  columns cols   mv col   cols pop cols index  77    df   df  mv col    cols    Now df columns has   Index   77    0    1    2    3    4    5    6    7    8                      991    992    993    994    995    996    997    998    999    1000          dtype  object   length 1001

User · Answer

The most simplist thing you can try is  df df    Mid      Upper      Lower    Net      Zsore

User · Answer

You can use the df reindex   function in pandas  df is                        Net  Upper   Lower  Mid  Zsore Answer option                                       More than once a day  0   0 22   -0 12     2     65 Once a day            0   0 32   -0 19     3     45 Several times a week  2   2 45    1 10     4     78 Once a week           1   1 63   -0 40     6     65   define an list of column names  cols   df columns tolist   cols Out 13     Net    Upper    Lower    Mid    Zsore     move the column name to wherever you want  cols insert 0  cols pop cols index  Mid     cols Out 16     Mid    Net    Upper    Lower    Zsore     then use df reindex   function to reorder  df   df reindex columns  cols    out put is  df                        Mid  Upper   Lower Net  Zsore Answer option                                       More than once a day    2  0 22   -0 12   0      65 Once a day              3  0 32   -0 19   0      45 Several times a week    4  2 45    1 10   2      78 Once a week             6  1 63   -0 40   1      65

User · Answer

I didn t like how I had to explicitly specify all the other column in the other solutions so this worked best for me  Though it might be slow for large dataframes      df   df set index  Mid   reset index

User · Answer

Maybe I m missing something  but a lot of these answers seem overly complicated   You should be able to just set the columns within a single list   Column to the front   df   df    Mid       col for col in df columns if col     Mid        Or if instead  you want to move it to the back   df   df    col for col in df columns if col     Mid        Mid       Or if you wanted to move more than one column   cols to move     Mid    Zsore   df             df  cols to move     col for col in df columns if col not in cols to move

User · Answer

Here is a very simple answer to this   Don t forget the two       brackets  around columns names Otherwise  it ll give you an error       here you can add below line and it should work  df   df list   Mid   Upper    Lower    Net   Zsore     df                               Mid   Upper   Lower  Net  Zsore Answer option                                                 More than once a day          2   0 22   -0 12    0     65  Once a day                    3   0 32   -0 19    0     45 Several times a week          4   2 45    1 10    2     78 Once a week                   6   1 63   -0 40    1     65

User · Answer

I prefer this solution   col   df pop  Mid   df insert 0  col name  col    It s simpler to read and faster than other suggested answers    def move column inplace df  col  pos       col   df pop col      df insert pos  col name  col      Performance assessment   For this test  the currently last column is moved to the front in each repetition  In-place methods generally perform better  While citynorman s solution can be made in-place  Ed Chum s method based on  loc and sachinnm s method based on reindex cannot    While other methods are generic  citynorman s solution is limited to pos 0  I didn t observe any performance difference between df loc cols  and df cols   which is why I didn t include some other suggestions   I tested with python 3 6 8 and pandas 0 24 2 on a MacBook Pro  Mid 2015    import numpy as np import pandas as pd  n cols   11 df   pd DataFrame np random randn 200000  n cols                     columns range n cols    def move column inplace df  col  pos       col   df pop col      df insert pos  col name  col   def move to front normanius inplace df  col       move column inplace df  col  0      return df  def move to front chum df  col       cols   list df      cols insert 0  cols pop cols index col        return df loc    cols   def move to front chum inplace df  col       col   df col      df drop col name  axis 1  inplace True      df insert 0  col name  col      return df  def move to front elpastor df  col       cols    col      c for c in df columns if c  col       return df cols    or df loc cols   def move to front sachinmm df  col       cols   df columns tolist       cols insert 0  cols pop cols index col        df   df reindex columns cols  copy False      return df  def move to front citynorman inplace df  col         This approach exploits that reset index   moves the index       at the first position of the data frame      df set index col  inplace True      df reset index inplace True      return df  def test method  df       col   np random randint 0  n cols      method df  col   col   np random randint 0  n cols  ret mine   move to front normanius inplace df copy    col  ret chum1   move to front chum df copy    col  ret chum2   move to front chum inplace df copy    col  ret elpas   move to front elpastor df copy    col  ret sach   move to front sachinmm df copy    col  ret city   move to front citynorman inplace df copy    col     Assert equivalence of solutions  assert ret mine equals ret chum1   assert ret mine equals ret chum2   assert ret mine equals ret elpas   assert ret mine equals ret sach   assert ret mine equals ret city     Results     For n cols   11   timeit test move to front normanius inplace  df    1 05 ms    42 4   s per loop  mean    std  dev  of 7 runs  1000 loops each   timeit test move to front citynorman inplace  df    1 68 ms    46 1   s per loop  mean    std  dev  of 7 runs  1000 loops each   timeit test move to front sachinmm  df    3 24 ms    96 5   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front chum  df     3 84 ms    114   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front elpastor  df    3 85 ms    58 3   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front chum inplace  df    9 67 ms    101   s per loop  mean    std  dev  of 7 runs  100 loops each      For n cols   31   timeit test move to front normanius inplace  df    1 26 ms    31 6   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front citynorman inplace  df    1 95 ms    260   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front sachinmm  df    10 7 ms    348   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front chum  df     11 5 ms    869   s per loop  mean    std  dev  of 7 runs  100 loops each  timeit test move to front elpastor  df    11 4 ms    598   s per loop  mean    std  dev  of 7 runs  100 loops each   timeit test move to front chum inplace  df    31 4 ms    1 89 ms per loop  mean    std  dev  of 7 runs  10 loops each

User · Answer

df set index  Mid   reset index    seems to be a pretty easy way about this

[python] Move column by name to front of table in pandas

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