Append python lists to DataFrame columns

Question

I have multiple python lists. But I want to collect each list into Dataframe columns.

new_list=pd.DataFrame([])

for i in range(0,4):
    new_list.append(my_list[i])

Then I get an error message, TypeError: cannot concatenate object of type "<class 'numpy.ndarray'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid.

my_list=([3.50913843e-05,1.64190123e-04, 4.19101449e-04, 4.40226697e-04, 3.11362684e-04],[4.573843e-05,6.795123e-04, 3.219e-04, 1.557897e-04, 3.11362684e-04], [7.0543e-05,1.64190123e-04, 2.154e-04, 4.40226697e-04, 3.11362684e-04])

The outcome I want is

3.50913843e-05     4.573843e-05     7.0543e-05
1.64190123e-04     6.795123e-04     1.64190123e-04
4.19101449e-04     3.219e-04     2.154e-04
4.40226697e-04     1.557897e-04     4.40226697e-04
3.11362684e-04     3.11362684e-04     3.11362684e-04

Any idea what is going wrong and how I could fix it?

can't replicate your error given your example, please update — Yuca
– Yuca, Commented Dec 4, 2018 at 23:18

BENY · Accepted Answer · 2018-12-04 23:20:21Z

6

So using

pd.DataFrame(np.array(my_list).T)
Out[929]: 
          0         1         2
0  0.000035  0.000046  0.000071
1  0.000164  0.000680  0.000164
2  0.000419  0.000322  0.000215
3  0.000440  0.000156  0.000440
4  0.000311  0.000311  0.000311

answered Dec 4, 2018 at 23:20

BENY

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1 Comment

cs95 Over a year ago

list or array makes no difference to the final result.

cs95 · Accepted Answer · 2018-12-04 23:17:58Z

2

You don't have to iteratively build a DataFrame - just pass it in at once. Either, pass a list-of-lists and transpose:

pd.DataFrame(list(my_list)).T

          0         1         2
0  0.000035  0.000046  0.000071
1  0.000164  0.000680  0.000164
2  0.000419  0.000322  0.000215
3  0.000440  0.000156  0.000440
4  0.000311  0.000311  0.000311

Or, inverse-zip, without the transposition.

pd.DataFrame(list(zip(*my_list)))

          0         1         2
0  0.000035  0.000046  0.000071
1  0.000164  0.000680  0.000164
2  0.000419  0.000322  0.000215
3  0.000440  0.000156  0.000440
4  0.000311  0.000311  0.000311

answered Dec 4, 2018 at 23:17

cs95

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