python - Select multiple ranges of columns in Pandas DataFrame

Question

I have to read several files some in Excel format and some in CSV format. Some of the files have hundreds of columns.

Is there a way to select several ranges of columns without specifying all the column names or positions? For example something like selecting columns 1 -10, 15, 17 and 50-100:

df = df.ix[1:10, 15, 17, 50:100]

I need to know how to do this both when creating dataframe from Excel files and CSV files and after the data framers created.

question from:https://stackoverflow.com/questions/41256648/select-multiple-ranges-of-columns-in-pandas-dataframe

Answer 1

use np.r_

np.r_[1:10, 15, 17, 50:100]

array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 15, 17, 50, 51, 52, 53, 54, 55,
       56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
       73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

so you can do

df.iloc[:, np.r_[1:10, 15, 17, 50:100]]