Convert Select Columns in Pandas Dataframe to Numpy Array

Question

I would like to convert everything but the first column of a pandas dataframe into a numpy array. For some reason using the columns= parameter of DataFram

Answer 1

The fastest and easiest way is to use .as_matrix(). One short line:

df.iloc[:,[1,2,3]].as_matrix()

Gives:

array([[3, 2, 0.816497],
   [0, 'NaN', 'NaN'],
   [2, 51, 50.0]], dtype=object)

By using indices of the columns, you can use this code for any dataframe with different column names.

Here are the steps for your example:

import pandas as pd
columns = ['viz', 'a1_count', 'a1_mean', 'a1_std']
index = [0,1,2]
vals = {'viz': ['n','n','n'], 'a1_count': [3,0,2], 'a1_mean': [2,'NaN', 51], 'a1_std': [0.816497, 'NaN', 50.000000]}
df = pd.DataFrame(vals, columns=columns, index=index)

Gives:

   viz  a1_count a1_mean    a1_std
0   n         3       2  0.816497
1   n         0     NaN       NaN
2   n         2      51        50

Then:

x1 = df.iloc[:,[1,2,3]].as_matrix()

Gives:

array([[3, 2, 0.816497],
   [0, 'NaN', 'NaN'],
   [2, 51, 50.0]], dtype=object)

Where x1 is numpy.ndarray.