How to combine multiple columns from a pandas df into a list

Question

How can you combine multiple columns from a dataframe into a list?

Input:

df = pd.DataFrame(np.random.randn(10000, 7), columns=list('ABCDEFG'))

If I wanted to create a list from column A I would perform:

df1 = df['A'].tolist()

But if I wanted to combine numerous columns into this list it wouldn't be efficient write df['A','B','C'...'Z'].tolist()

I have tried to do the following but it just adds the columns headers to a list.

df1 = list(df.columns)[0:8]

Intended input:

   A         B         C         D         E         F         G  
0  0.787576  0.646178 -0.561192 -0.910522  0.647124 -1.388992  0.728360   
1  0.265409 -1.919283 -0.419196 -1.443241 -2.833812 -1.066249  0.553379   
2  0.343384  0.659273 -0.759768  0.355124 -1.974534  0.399317 -0.200278

Intended Output:

[0.787576,  0.646178, -0.561192, -0.910522,  0.647124, -1.388992,  0.728360,   
 0.265409, -1.919283, -0.419196, -1.443241, -2.833812, -1.066249,  0.553379,   
 0.343384,  0.659273, -0.759768,  0.355124, -1.974534,  0.399317, -0.200278]

I don't understand what your expecting the output to look like? — Dan Temkin, Apr 23 '18 at 02:47
You can find how to select a column range in pandas here - https://stackoverflow.com/questions/11285613/selecting-columns-in-a-pandas-dataframe — Dan Temkin, Apr 23 '18 at 02:48
Updated @DanTemkin. I have seen that post and can't see how it would help my question. — , Apr 23 '18 at 03:21

BENY · Answer 1 · 2018-04-23T02:50:32.543

0

You can using to_dict

df = pd.DataFrame(np.random.randn(10, 10), columns=list('ABCDEFGHIJ'))
df.to_dict('l')
Out[1036]: 
{'A': [-0.5611441440595607,
  -0.3785906500723589,
  -0.19480328695097676,
  -0.7472526275034221,
  -2.4232786057647457,
  0.10506614562827334,
  0.4968179288412277,
  1.635737019365132,
  -1.4286421753281746,
  0.4973223222844811],
 'B': [-1.0550082961139444,
  -0.1420067090193365,
  0.30130476834580633,
  1.1271866812852227,
  0.38587456174846285,
  -0.531163142682951,
  -1.1335754634118729,
  0.5975963084356348,
  -0.7361022807495443,
  1.4329395663140427],


 ...}

Or adding values.tolist()

df[list('ABC')].values.tolist()
Out[1041]: 
[[0.09552771302434987, 0.18551596484768904, -0.5902249875268607],
 [-1.5285190712746388, 1.2922627021799646, -0.8347422966138306],
 [-0.4092028716404067, -0.5669107267579823, 0.3627970727410332],
 [-1.3546346273319263, -0.9352316948439341, 1.3568726575880614],
 [-1.3509518030469496, 0.10487182694997808, -0.6902134363370515]]

Edit : np.concatenate(df[list('ABC')].T.values.tolist())

edited Apr 23 '18 at 02:50

answered Apr 23 '18 at 02:38

BENY

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I'd like it to be one list. Not a separate lists for each column. So instead of `[[1,2,3],[1,2,3],[1,2,3]]`. It would be `[1,2,3,1,2,3,1,2,3]` – Apr 23 '18 at 02:45
@Punter345 you can do `np.concatenate(df[list('ABC')].T.values.tolist()) ` check the update as well – BENY Apr 23 '18 at 02:50
Thanks @Wen. This is very useful. I thought there might have been a way that did this without merging and manually typing each column name. It may not be efficient if you have 100 columns. – Apr 23 '18 at 03:26
@Punter345 you can select by position check `.iloc` – BENY Apr 23 '18 at 03:31
@Punter345 you know you can only select one answer as accepted answer right ? – BENY Apr 23 '18 at 04:20

score 0 · Accepted Answer · answered Apr 23 '18 at 02:41

0

Is this what you are looking for

lst = df.values.tolist()
flat_list = [item for x in lst for item in x]
print(flat_list)

answered Apr 23 '18 at 02:41

user2510479

1,528
13
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How to combine multiple columns from a pandas df into a list

2 Answers2