Pandas selecting discontinuous columns from a dataframe

NumPy has a nice module named r_, allowing you to solve it with the modern DataFrame selection interface, iloc:

df.iloc[:, np.r_[0:1, 17:342]]

I believe this is a more elegant solution.

It even support more complex selections:

df.iloc[:, np.r_[0:1, 5, 16, 17:342:2, -5:]]

If you want to concatenate a sub selection of your df columns then use pd.concat:

pd.concat([comb.ix[:,0:1],comb.ix[:,17:342]], axis=1)

So long as the indices match then this will align correctly.

Thanks to @iHightower that you can also sub-select by passing the labels:

pd.concat([df.ix[:,'Col1':'Col5'],df.ix[:,'Col9':'Col15']],a‌​xis=1)

Note that .ix will be deprecated in a future version the following should work:

In [115]:
df = pd.DataFrame(columns=['col' + str(x) for x in range(10)])
df

Out[115]:
Empty DataFrame
Columns: [col0, col1, col2, col3, col4, col5, col6, col7, col8, col9]
Index: []

In [118]:
pd.concat([df.loc[:, 'col2':'col4'], df.loc[:, 'col7':'col8']], axis=1)
​
Out[118]:
Empty DataFrame
Columns: [col2, col3, col4, col7, col8]
Index: []

Or using iloc:

In [127]:
pd.concat([df.iloc[:, df.columns.get_loc('col2'):df.columns.get_loc('col4')], df.iloc[:, df.columns.get_loc('col7'):df.columns.get_loc('col8')]], axis=1)

Out[127]:
Empty DataFrame
Columns: [col2, col3, col7]
Index: []

Note that iloc slicing is open/closed so the end range is not included so you'd have to find the column after the column of interest if you want to include it:

In [128]:
pd.concat([df.iloc[:, df.columns.get_loc('col2'):df.columns.get_loc('col4')+1], df.iloc[:, df.columns.get_loc('col7'):df.columns.get_loc('col8')+1]], axis=1)

Out[128]:
Empty DataFrame
Columns: [col2, col3, col4, col7, col8]
Index: []