CODEWITHSUNDEEP
pythonpandas
hvedrung
hvedrung

Reputation: 467

pack dataframe columns to list in pandas

I need to pack pandas DataFrame columns in one column containing lists. Example:

For

>>>df
    a   b   c
0  81  88   1
1  42   7  23
2   8  37  63
3  18  22  20

make list column:

    list_col
0  [81,88,1]
1  [42,7,23]
2  [8,37,63]
3  [18,22,20]

If I try

df.apply(list,axis=1)

python returns same DataFrame.

In case I try 

>>> df.apply(lambda r:{'list_col':list(r)},axis=1)
    a   b   c
0 NaN NaN NaN
1 NaN NaN NaN
2 NaN NaN NaN
3 NaN NaN NaN

is not working.

Even brute method 

>>> df['list_col'] = ''
>>> for i in df.index:
    df.ix[i,'list_col'] = list(df.ix[i,df.columns[:-1]])

returns error:

Traceback (most recent call last):
  File "<pyshell#45>", line 2, in <module>
    df.ix[i,'list_col'] = list(df.ix[i,df.columns[:-1]])
  File "C:\Anaconda\lib\site-packages\pandas\core\indexing.py", line 88, in __setitem__
    self._setitem_with_indexer(indexer, value)
  File "C:\Anaconda\lib\site-packages\pandas\core\indexing.py", line 158, in _setitem_with_indexer
    len(self.obj[labels[0]]) == len(value) or len(plane_indexer[0]) == len(value)):
TypeError: object of type 'int' has no len()

The only working method I found is:

df['list_col'] = df.apply(lambda r:{df.columns[0]:list(r)}, axis=1)[df.columns[0]]

This gives me what I want but maybe there is more straight way?

Upvotes: 2

Views: 1748

Answers (2)

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210852

Here is a vectorized approach, which is very similar to @Anzel's solution:

In [55]: df
Out[55]:
    a   b   c
0  81  88   1
1  42   7  23
2   8  37  63
3  18  22  20

In [56]: df['list_col'] = df.values.tolist()

In [57]: df
Out[57]:
    a   b   c      list_col
0  81  88   1   [81, 88, 1]
1  42   7  23   [42, 7, 23]
2   8  37  63   [8, 37, 63]
3  18  22  20  [18, 22, 20]

Timing against 4M rows DF:

In [69]: df.shape
Out[69]: (4000000, 3)

In [70]: %timeit list(df.values)
1 loop, best of 3: 2.04 s per loop

In [71]: %timeit df.values.tolist()
1 loop, best of 3: 993 ms per loop

Upvotes: 0

Anzel
Anzel

Reputation: 20553

Just assign the column as a list on df.values will do:

df['list_col'] = list(df.values)

df
    a   b   c      list_col
0  81  88   1   [81, 88, 1]
1  42   7  23   [42, 7, 23]
2   8  37  63   [8, 37, 63]
3  18  22  20  [18, 22, 20]

Upvotes: 3

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