Re-ordering columns in pandas dataframe based on column name

Question

I have a dataframe with over 200 columns  The issue is as they were generated the order is    Q1 3   Q6 1   Q1 2   Q1 1            I need to re-order the columns as follows     Q1 1   Q1 2   Q1 3        Q6 1            Is there some way for me to do this within Python

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Tweet s answer can be passed to BrenBarn s answer above with   data reindex axis sorted data columns  key lambda x  float x 1      axis 1    So for your example  say   vals   randint low 16  high 80  size 25  reshape 5 5  cols     Q1 3    Q6 1    Q1 2    Q9 1    Q10 2   data   DataFrame vals  columns   cols    You get    data      Q1 3    Q6 1    Q1 2    Q9 1    Q10 2 0   73      29      63      51      72 1   61      29      32      68      57 2   36      49      76      18      37 3   63      61      51      30      31 4   36      66      71      24      77   Then do   data reindex axis sorted data columns  key lambda x  float x 1      axis 1    resulting in   data        Q1 2    Q1 3    Q6 1    Q9 1    Q10 2 0    2       0       1       3       4 1    7       5       6       8       9 2    2       0       1       3       4 3    2       0       1       3       4 4    2       0       1       3       4

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One use-case is that you have named  some of  your columns with some prefix  and you want the columns sorted with those prefixes all together and in some particular order  not alphabetical     For example  you might start all of your features with Ft   labels with Lbl   etc  and you want all unprefixed columns first  then all features  then the label  You can do this with the following function  I will note a possible efficiency problem using sum to reduce lists  but this isn t an issue unless you have a LOT of columns  which I do not     def sortedcols df  groups     Ft     Lbl           return df  sum  list filter re compile r  search  list df columns  copy     for r in  lambda l          s          join l         s    i  for i in l     groups

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print df sort index by  Frequency  ascending False    where by is the name of the column if you want to sort the dataset based on column

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df   df reindex sorted df columns   axis 1    This assumes that sorting the column names will give the order you want   If your column names won t sort lexicographically  e g   if you want column Q10 3 to appear after Q9 1   you ll need to sort differently  but that has nothing to do with pandas

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The quickest method is   df sort index axis 1    Be aware that this creates a new instance  Therefore you need to store the result in a new variable   sortedDf df sort index axis 1

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You can also do more succinctly   df sort index axis 1      Make sure you assign the result back    df   df sort index axis 1    Or  do it in-place   df sort index axis 1  inplace True

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For several columns  You can put columns order what you want      A    B    C    lt -this is your columns order df   df   C    B    A      This example shows sorting and slicing columns   d     col1   1  2  3    col2   4  5  6    col3   7  8  9    col4   17  18  19   df   pandas DataFrame d    You get   col1  col2  col3  col4  1     4     7    17  2     5     8    18  3     6     9    19   Then do   df   df   col3    col2    col1      Resulting in   col3  col2  col1 7     4     1 8     5     2 9     6     3

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If you need an arbitrary sequence instead of sorted sequence  you could do   sequence     Q1 1   Q1 2   Q1 3        Q6 1          your dataframe   your dataframe reindex columns sequence    I tested this in 2 7 10 and it worked for me

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Don t forget to add  inplace True  to Wes  answer or set the result to a new DataFrame   df sort index axis 1  inplace True

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The sort method and sorted function allow you to provide a custom function to extract the key used for comparison    gt  gt  gt  ls     Q1 3    Q6 1    Q1 2    gt  gt  gt  sorted ls  key lambda x  float x 1       Q1 2    Q1 3    Q6 1

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You can just do    df sorted df columns       Edit  Shorter is   df sorted df

[python] Re-ordering columns in pandas dataframe based on column name

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