Say I have a dictionary with 10 key-value pairs. Each entry holds a numpy array. However, the length of the array is not the same for all of them.
How can I create a dataframe where each column holds a different entry?
When I try:
import pandas as pd
import numpy as np
from string import ascii_uppercase # from the standard library
# repeatable sample data
np.random.seed(2023)
data = {k: np.random.randn(v) for k, v in zip(ascii_uppercase[:10], range(10, 20))}
df = pd.DataFrame(data)
I get:
ValueError: arrays must all be the same length
Any way to overcome this? I am happy to have Pandas use NaN to pad those columns for the shorter entries.
Desired Result
A B C D E F G H I J
0 0.711674 -1.076522 -1.502178 -1.519748 0.340619 0.051132 0.036537 0.367296 1.056500 -1.186943
1 -0.324485 -0.325682 -1.379593 2.097329 -1.253501 -0.238061 2.431822 -0.576828 -0.733918 -0.540638
2 -1.001871 -1.035498 -0.204455 0.892562 0.370788 -0.208009 0.422599 -0.416005 -0.083968 -0.638495
3 0.236251 -0.426320 0.642125 1.596488 0.455254 0.401304 1.843922 -0.137542 0.127288 0.150411
4 -0.102160 -1.029361 -0.181176 -0.638762 -2.283720 0.183169 -0.221562 1.294987 0.344423 0.919450
5 -1.141293 -0.521774 0.771749 -1.133047 -0.000822 1.235830 0.337117 0.520589 0.685970 0.910146
6 2.654407 -0.422758 0.741523 0.656597 2.398876 -0.291800 -0.557180 -0.194273 0.399908 1.605234
7 1.440605 -0.099244 1.324763 0.595787 -2.583105 0.029992 0.053141 -0.385593 0.893458 0.667165
8 0.098902 -1.380258 0.439287 -0.811120 1.311009 -0.868404 1.053804 -3.065784 0.384793 0.950338
9 -3.121532 0.301903 -0.557873 -0.300535 -1.579478 0.604346 -0.658515 -0.668181 0.641113 0.734329
10 NaN -1.033599 0.927080 1.008391 -0.840683 0.728554 1.844449 0.056965 -0.577314 1.015465
11 NaN NaN -0.600727 -1.087762 -0.165509 1.364820 -0.075514 -0.909368 -0.819947 0.627386
12 NaN NaN NaN -1.787079 -2.068410 1.342694 0.264263 -1.487910 0.746819 1.062655
13 NaN NaN NaN NaN 0.452739 -1.456708 -1.395359 1.169611 1.836805 0.262885
14 NaN NaN NaN NaN NaN 0.969357 0.708416 0.393677 -1.455490 -2.086486
15 NaN NaN NaN NaN NaN NaN 0.762756 0.530569 -0.828721 -1.076369
16 NaN NaN NaN NaN NaN NaN NaN -0.586429 -0.609144 -0.507519
17 NaN NaN NaN NaN NaN NaN NaN NaN -1.071297 -0.274501
18 NaN NaN NaN NaN NaN NaN NaN NaN NaN 1.848811
ベストアンサー1
In Python 3.x:
import pandas as pd
import numpy as np
d = dict( A = np.array([1,2]), B = np.array([1,2,3,4]) )
pd.DataFrame(dict([ (k,pd.Series(v)) for k,v in d.items() ]))
Out[7]:
A B
0 1 1
1 2 2
2 NaN 3
3 NaN 4
In Python 2.x:
replace d.items() with d.iteritems().