I would like to reorder the columns in a dataframe, and keep the underlying values in the right columns.
For example this is the dataframe I have
cols = [ ['Three', 'Two'],['A', 'D', 'C', 'B']]
header = pd.MultiIndex.from_product(cols)
df = pd.DataFrame([[1,4,3,2,5,8,7,6]]*4,index=np.arange(1,5),columns=header)
df.loc[:,('One','E')] = 9
df.loc[:,('One','F')] = 10
>>> df
And I would like to change it as follows:
header2 = pd.MultiIndex(levels=[['One', 'Two', 'Three'], ['E', 'F', 'A', 'B', 'C', 'D']],
labels=[[0, 0, 0, 0, 1, 1, 1, 1, 2, 2], [0, 1, 2, 3, 4, 5, 2, 3, 4, 5]])
df2 = pd.DataFrame([[9,10,1,2,3,4,5,6,7,8]]*4,index=np.arange(1,5), columns=header2)
>>>>df2
First, define a categorical ordering on the top level. Then, call sort_index on the first axis with both levels.
v = pd.Categorical(df.columns.get_level_values(0),
categories=['One', 'Two', 'Three'],
ordered=True)
v2 = pd.Categorical(df.columns.get_level_values(1),
categories=['E', 'F', 'C', 'B', 'A', 'D'],
ordered=True)
df.columns = pd.MultiIndex.from_arrays([v, v2])
df = df.sort_index(axis=1, level=[0, 1])
df
One Two Three
E F C B A D C B A D
1 9 10 7 6 5 8 3 2 1 4
2 9 10 7 6 5 8 3 2 1 4
3 9 10 7 6 5 8 3 2 1 4
4 9 10 7 6 5 8 3 2 1 4