pandas extract array to columns

user_2587904 0
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How can the array (the length of the array is constant for all elements in the series) be extracted into columns efficiently?

import pandas as pd
d = pd.DataFrame({'foo':\[1,2,3\], 'bar':\[\[1,1,1\], \[2,2,2\], \[3,3,3\]\]})
d][1]][1]

enter image description here

I.e. extract the array of [1,1,1] into a bar_0, bar_1, bar_3 column?

Is there a better way than manually iterating over the indices in the array and calling pandas.apply?

pandas apply numpy arrays python
2 Answers
import pandas as pd

d = pd.DataFrame({"foo": [1, 2, 3], "bar": [[1, 1, 1], [2, 2, 2], [3, 3, 3]]})

d = pd.concat([d, d.pop("bar").apply(pd.Series).add_prefix("bar_")], axis=1)
print(d)

Prints:

   foo  bar_0  bar_1  bar_2
0    1      1      1      1
1    2      2      2      2
2    3      3      3      3
user_100359850

How about this:

>>> d.join(pd.DataFrame(d['bar'].to_list(), columns=['bar_1', 'bar_2', 'bar_3']))
   foo        bar  bar_1  bar_2  bar_3
0    1  [1, 1, 1]      1      1      1
1    2  [2, 2, 2]      2      2      2
2    3  [3, 3, 3]      3      3      3

You convert the bar column to list (nested list), convert it to a dataframe, and join the new dataframe with your initial dataframe.

user_157327550
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