How to change the order of DataFrame columns?

Question

I have the following DataFrame (df):

import numpy as np import pandas as pd  df = pd.DataFrame(np.random.rand(10, 5)) 

I add more column(s) by assignment:

df['mean'] = df.mean(1) 

How can I move the column mean to the front, i.e. set it as first column leaving the order of the other columns untouched?

Answer 1

You could also do something like this:

df = df[['mean', '0', '1', '2', '3']] 

You can get the list of columns with:

cols = list(df.columns.values) 

The output will produce:

['0', '1', '2', '3', 'mean'] 

...which is then easy to rearrange manually before dropping it into the first function

Answer 2

One easy way would be to reassign the dataframe with a list of the columns, rearranged as needed.

This is what you have now:

In [6]: df Out[6]:           0         1         2         3         4      mean 0  0.445598  0.173835  0.343415  0.682252  0.582616  0.445543 1  0.881592  0.696942  0.702232  0.696724  0.373551  0.670208 2  0.662527  0.955193  0.131016  0.609548  0.804694  0.632596 3  0.260919  0.783467  0.593433  0.033426  0.512019  0.436653 4  0.131842  0.799367  0.182828  0.683330  0.019485  0.363371 5  0.498784  0.873495  0.383811  0.699289  0.480447  0.587165 6  0.388771  0.395757  0.745237  0.628406  0.784473  0.588529 7  0.147986  0.459451  0.310961  0.706435  0.100914  0.345149 8  0.394947  0.863494  0.585030  0.565944  0.356561  0.553195 9  0.689260  0.865243  0.136481  0.386582  0.730399  0.561593  In [7]: cols = df.columns.tolist()  In [8]: cols Out[8]: [0L, 1L, 2L, 3L, 4L, 'mean'] 

Rearrange cols in any way you want. This is how I moved the last element to the first position:

In [12]: cols = cols[-1:] + cols[:-1]  In [13]: cols Out[13]: ['mean', 0L, 1L, 2L, 3L, 4L] 

Then reorder the dataframe like this:

In [16]: df = df[cols]  #    OR    df = df.ix[:, cols]  In [17]: df Out[17]:        mean         0         1         2         3         4 0  0.445543  0.445598  0.173835  0.343415  0.682252  0.582616 1  0.670208  0.881592  0.696942  0.702232  0.696724  0.373551 2  0.632596  0.662527  0.955193  0.131016  0.609548  0.804694 3  0.436653  0.260919  0.783467  0.593433  0.033426  0.512019 4  0.363371  0.131842  0.799367  0.182828  0.683330  0.019485 5  0.587165  0.498784  0.873495  0.383811  0.699289  0.480447 6  0.588529  0.388771  0.395757  0.745237  0.628406  0.784473 7  0.345149  0.147986  0.459451  0.310961  0.706435  0.100914 8  0.553195  0.394947  0.863494  0.585030  0.565944  0.356561 9  0.561593  0.689260  0.865243  0.136481  0.386582  0.730399