Add numpy array as column to Pandas data frame

Question

I have a Pandas data frame object of shape  X Y  that looks like this     1  2  3    4  5  6    7  8  9     and a numpy sparse matrix  CSC  of shape  X Z  that looks something like this    0  1  0    0  0  1    1  0  0     How can I add the content from the matrix to the data frame in a new named column such that the data frame will end up like this     1  2  3   0  1  0     4  5  6   0  0  1     7  8  9   1  0  0      Notice the data frame now has shape  X  Y 1  and rows from the matrix are elements in the data frame

User · Answer

You can add and retrieve a numpy array from dataframe using this:

import numpy as np
import pandas as pd

df = pd.DataFrame({'b':range(10)}) # target dataframe
a = np.random.normal(size=(10,2)) # numpy array
df['a']=a.tolist() # save array
np.array(df['a'].tolist()) # retrieve array

This builds on the previous answer that confused me because of the sparse part and this works well for a non-sparse numpy arrray.

User · Answer

Consider using a higher dimensional datastructure  a Panel   rather than storing an array in your column   In  11   p   pd Panel   df   df   csc   csc    In  12   p df Out 12       0  1  2 0  1  2  3 1  4  5  6 2  7  8  9  In  13   p csc Out 13       0  1  2 0  0  1  0 1  0  0  1 2  1  0  0   Look at cross-sections etc  etc  etc   In  14   p xs 0  Out 14       csc  df 0    0   1 1    1   2 2    0   3   See the docs for more on Panels

User · Answer

df   pd DataFrame np arange 1 10  reshape 3 3   df  newcol     pd Series your 2d numpy array

User · Answer

import numpy as np import pandas as pd import scipy sparse as sparse  df   pd DataFrame np arange 1 10  reshape 3 3   arr   sparse coo matrix   1 1 1     0 1 2    1 2 0     shape  3 3   df  newcol     arr toarray   tolist   print df    yields     0  1  2     newcol 0  1  2  3   0  1  0  1  4  5  6   0  0  1  2  7  8  9   1  0  0

User · Answer

Here is other example   import numpy as np import pandas as pd      This just creates a list of touples  and each element of the touple is an array    a      np random randint 1 10 10   np array  0 1 2 3 4 5 6 7 8 9     for i in  range 0 10         Panda DataFrame will allocate each of the arrays   contained as a touple  element   as column    df   pd DataFrame data  a columns   random num   sequential num      The secret in general is to allocate the data in the form a      array 11  array 12     array 1n       array m1 array m2     array mn    and panda DataFrame will order the data in n columns of arrays  Of course   arrays of arrays could be used instead of touples  in that case the form would be   a      array 11  array 12     array 1n       array m1 array m2     array mn      This is the output if you print df  from the code above                          random num                  sequential num 0   7  9  2  2  5  3  5  3  1  4    0  1  2  3  4  5  6  7  8  9  1   8  7  9  8  1  2  2  6  6  3    0  1  2  3  4  5  6  7  8  9  2   3  4  1  2  2  1  4  2  6  1    0  1  2  3  4  5  6  7  8  9  3   3  1  1  1  6  2  8  6  7  9    0  1  2  3  4  5  6  7  8  9  4   4  2  8  5  4  1  2  2  3  3    0  1  2  3  4  5  6  7  8  9  5   3  2  7  4  1  5  1  4  6  3    0  1  2  3  4  5  6  7  8  9  6   5  7  3  9  7  8  4  1  3  1    0  1  2  3  4  5  6  7  8  9  7   7  4  7  6  2  6  3  2  5  6    0  1  2  3  4  5  6  7  8  9  8   3  1  6  3  2  1  5  2  2  9    0  1  2  3  4  5  6  7  8  9  9   7  2  3  9  5  5  8  6  9  8    0  1  2  3  4  5  6  7  8  9    Other variation of the example above   b      i  text   14  5    np array  0 1 2 3 4 5 6 7 8 9     for i in  range 0 10    df   pd DataFrame data b columns   Number   Text   2Elemnt array   10Element array      Output of df      Number  Text 2Elemnt array                 10Element array 0       0  text        14  5    0  1  2  3  4  5  6  7  8  9  1       1  text        14  5    0  1  2  3  4  5  6  7  8  9  2       2  text        14  5    0  1  2  3  4  5  6  7  8  9  3       3  text        14  5    0  1  2  3  4  5  6  7  8  9  4       4  text        14  5    0  1  2  3  4  5  6  7  8  9  5       5  text        14  5    0  1  2  3  4  5  6  7  8  9  6       6  text        14  5    0  1  2  3  4  5  6  7  8  9  7       7  text        14  5    0  1  2  3  4  5  6  7  8  9  8       8  text        14  5    0  1  2  3  4  5  6  7  8  9  9       9  text        14  5    0  1  2  3  4  5  6  7  8  9    If you want to add other columns of arrays  then   df  3Element array      1 2 3     1 2 3     1 2 3     1 2 3     1 2 3     1 2 3     1 2 3     1 2 3     1 2 3     1 2 3      The final output of df will be      Number  Text 2Elemnt array                 10Element array 3Element array 0       0  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  1       1  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  2       2  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  3       3  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  4       4  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  5       5  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  6       6  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  7       7  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  8       8  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3  9       9  text        14  5    0  1  2  3  4  5  6  7  8  9        1  2  3

[python] Add numpy array as column to Pandas data frame

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