Python equivalent of R c() function, for dataframe column indices?

Question

I would like to select from a pandas dataframe specific columns using column index.

In particular, I would like to select columns index by the column index generate

Answer 1

To answer the actual question,

Python equivalent of R c() function, for dataframe column indices?

I'm using this definition of c()

c = lambda v: v.split(',') if ":" not in v else eval(f'np.r_[{v}]')

Then we can do things like:

df = pd.DataFrame({'x': np.random.randn(1000),
                   'y': np.random.randn(1000)})
# row selection
df.iloc[c('2:4,7:11,21:25')] 

# columns by name
df[c('x,y')] 

# columns by range
df.T[c('12:15,17:25,500:750')]

That's pretty much as close as it gets in terms of R-like syntax.

To the curious mind

Note there is a performance penality in using c() as per above v.s. np.r_. To paraphrase Knuth, let's not optimize prematurely ;-)

%timeit np.r_[2:4, 7:11, 21:25]
27.3 µs ± 786 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)

%timeit c("2:4, 7:11, 21:25")
53.7 µs ± 977 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)