How to sort rows in pandas with a non-standard order

Question

I have a pandas dataframe, say:

df = pd.DataFrame ([['a', 3, 3], ['b', 2, 5], ['c', 4, 9], ['d', 1, 43]], columns = ['col 1' , 'col2', 'col 3'])

or:

  col 1  col2  col 3
0     a     3      3
1     b     2      5
2     c     4      9
3     d     1     43

If I want to sort by col2, I can use df.sort, and that will sort ascending and descending.

However, if I want to sort the rows so that col2 is: [4, 2, 1, 3], how would I do that?

Answer 1

Try this:

sortMap = {4:1, 2:2, 1:3,3:4 }
df["new"] = df2['col2'].map(sortMap)
df.sort_values('new', inplace=True)
df

   col1  col2  col3  new
2    c     4     9    1
1    b     2     5    2
3    d     1    43    3
0    a     3     3    4

alt method to create dict:

ll      = [4, 2, 1, 3] 
sortMap = dict(zip(ll,range(len(ll))))

Answer 2

One way is to convert that column to a Categorical type, which can have an arbitrary ordering.

In [51]: df['col2'] = df['col2'].astype('category', categories=[4, 1, 2, 3], ordered=True)

In [52]: df.sort_values('col2')
Out[52]: 
  col 1 col2  col 3
2     c    4      9
3     d    1     43
1     b    2      5
0     a    3      3