CODEWITHSUNDEEP
pythonpandas
shiv_90
shiv_90

Reputation: 1097

How to select multiple columns (inclusive and exclusive) simultaneously?

I'm working on a data frame that has 246 columns. Specifically, I would like to slice columns 1, 2, 4, 5, 6 and then also select columns 82 to 94, the latter ones being inclusive, all at the same time in one command. I have tried .iloc and .ix, but they return syntax errors.

new_df = df.iloc[:, [1, 2 ,4, 5, 6, 82:94]]

new_df = df.iloc[:, [1, 2, 4, 5, 6, 82:94]]
  File "<ipython-input-6-012945e7610d>", line 1
    new_df = df.iloc[:, [1, 2, 4, 5, 6, 82:94]]
                                          ^
SyntaxError: invalid syntax

Same is returned by .ix too. Is there any other way to do this other than specifying exclusive column indexes (that would be a long command)?

Upvotes: 2

Views: 180

Answers (3)

Nikhil Khandelwal
Nikhil Khandelwal

Reputation: 124

To perform select and slicing operations together you can use numpy.r_, which helps in concatenating n number of array slices along an axis.

new_df = df.iloc[:, numpy.r_[1, 2, 4, 5, 6, 82:94]]

Upvotes: 1

Refael
Refael

Reputation: 7323

new_df = df.iloc[:, [1, 2, 4, 5, 6, list(range(82,94))]]

Upvotes: 1

Andrea
Andrea

Reputation: 3077

I'm afraid you can not mix indexes and slicing like that. A simple workaround is to use range:

new_df = df.iloc[:, [1, 2 ,4, 5, 6, *range(82,94)]]

Upvotes: 1

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