df = pd.DataFrame(np.arange(10).reshape(-1, 5), columns=list('ABCDE'))
print(df)

   A  B  C  D  E
0  0  1  2  3  4
1  5  6  7  8  9

df[['B', 'D']].values

array([[1, 3],
       [6, 8]])

from timeit import timeit
import pandas as pd
import numpy as np
from string import ascii_uppercase as up


def slc_df_2val(df, cols):
    return df[cols].values

def as_matrix(df, cols):
    return df.as_matrix(cols)

def hstack_per_col(df, cols):
    return np.hstack([df[c].values[:, None] for c in cols])

def stack_per_col_T(df, cols):
    return np.stack([df[c].values for c in cols]).reshape(-1, len(cols))

def get_loc_slc_array(df, cols):
    a = [df.columns.get_loc(c) for c in cols]
    return df.values[:, a]

mcol = pd.MultiIndex.from_product([list(up[:10]), list(up[-10:])])

sizes = pd.MultiIndex.from_product(
    [[10, 100, 1000, 10000], [1, 5, 10, 20, 30, 40]],
    names=['n', 'm'])

methods = pd.Index(
    'slc_df_2val as_matrix hstack_per_col stack_per_col_T get_loc_slc_array'.split(),
    name='method')

results = pd.DataFrame(index=sizes, columns=methods)

np.random.seed([3,1415])
for n in sizes.levels[0]:
    df = pd.DataFrame(np.arange(n * 100).reshape(-1, 100), columns=mcol)
    for m in sizes.levels[1]:
        cols = np.random.choice(mcol, m, replace=False)
        for f in methods:
            stmt = '{}(df, cols)'.format(f)
            setup = 'from __main__ import {}, df, cols'.format(f)
            tvalue = timeit(stmt, setup, number=500)
            results.set_value((n, m), f, tvalue)

fig, axes = plt.subplots(2, 2, figsize=(8, 6))
for i, n in enumerate(sizes.levels[0]):
    ax = axes[i // 2, i % 2]
    results.xs(n).plot(lw=2, ax=ax, title='size {}'.format(n))
    ax.legend().remove()

axes[-1, -1].legend(bbox_to_anchor=(1.7, 2.4), fontsize=10)

fig.suptitle('Num Columns Perspective', fontsize=10)

fig.tight_layout()
plt.subplots_adjust(top=.9)

fig, axes = plt.subplots(3, 2, figsize=(8, 9))
for i, m in enumerate(sizes.levels[1]):
    ax = axes[i // 2, i % 2]
    results.xs(m, level=1).plot(lw=2, ax=ax, title='num cols {}'.format(m), rot=45)
    ax.legend().remove()

axes[-1, -1].legend(bbox_to_anchor=(1.7, 4.1), fontsize=10)

fig.suptitle('Array Length Perspective', fontsize=10)

fig.tight_layout()
plt.subplots_adjust(top=.9)