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 DataFrame to matrix   is not working   df     viz  a1 count  a1 mean     a1 std 0   n         3        2   0 816497 1   n         0      NaN        NaN  2   n         2       51  50 000000   I tried X df as matrix columns  df 1     but this yields an array of all NaNs

User · Answer

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

User · Answer

The best way for converting to Numpy Array is using   to numpy self  dtype None  copy False    It is new in version 0 24 0 Refrence  You can also use   array  Refrence  Pandas  as matrix deprecated since version 0 23 0

User · Answer

The columns parameter accepts a collection of column names   You re passing a list containing a dataframe with two rows    gt  gt  gt   df 1       viz  a1 count  a1 mean  a1 std 1   n         0      NaN     NaN 2   n         2       51      50   gt  gt  gt  df as matrix columns  df 1     array    nan   nan            nan   nan            nan   nan      Instead  pass the column names you want    gt  gt  gt  df columns 1   Index   a1 count    a1 mean    a1 std    dtype  object    gt  gt  gt  df as matrix columns df columns 1    array     3           2           0 816497             0                nan         nan             2          51          50

User · Answer

Hope this easy one liner helps  cols as np   df df columns 1    to numpy

User · Answer

the easy way is the  values  property df iloc   1   values  a df iloc   1   b df iloc   1   values  print type df   print type a   print type b     so  you can get type   lt class  pandas core frame DataFrame  gt   lt class  pandas core frame DataFrame  gt   lt class  numpy ndarray  gt

User · Answer

Please use the Pandas to numpy   method  Below is an example--   gt  gt  gt  import pandas as pd  gt  gt  gt  df   pd DataFrame   A   1  2    B   3  4    C   5  6     gt  gt  gt  df      A  B  C  0  1  3  5  1  2  4  6  gt  gt  gt  s array   df   A    B    C    to numpy    gt  gt  gt  s array  array   1  3  5       2  4  6       gt  gt  gt  t array   df   B    C    to numpy     gt  gt  gt  print  t array     3 5    4 6     Hope this helps  You can select any number of columns using   columns     col1    col2    col3   df1   df columns    Then apply to numpy   method

[python] Convert Select Columns in Pandas Dataframe to Numpy Array

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

Gives:

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

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