How to save list of arrays in dataframe

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Can someone help me if there is solution how to save list of arrays in Python in dataframe but this input(list of arrays) changes in cycle so that I need to every array store as new dataframe. Here is the example:

If my input seems look like this:

[array([[ 1,  2,  3],
       [1, 2, 3]]), array([[3, 4, 5],
       [ 3,  4,  5]])]

I need output as dataframes like this:

1. column 2. column 3. column
1 2 3
1 2 3
1. column 2. column 3. column
3 4 5
3 4 5

but this is only for first iteration in cycle so when the second iteration start I get new data e.g.

[array([[ 6,  7,  8],
       [6, 7, 8]]), array([[9, 10, 11],
       [ 9,  10,  11]])]

so I need to update my dataframe first array append to first dataframe and the second array to the second dataframe so the updated table should look like this:

1. column 2. column 3. column
1 2 3
1 2 3
6 7 8
6 7 8
1. column 2. column 3. column
3 4 5
3 4 5
9 10 11
9 10 11

Is there any way how to make this ?

pandas dataframe arrays python
1 Answers

simply make an data frame out of the sub array, then append it to your main dataframe:

import pandas as pd
data = [array([[ 1,  2,  3],
       [1, 2, 3]]), array([[3, 4, 5],
       [ 3,  4,  5]])]

df = pd.DataFrame({"A": [], "B": [], "C": []})

for arr in data:
    subdf = pd.DataFrame(arr, ["A","B","C"])
    df = df.append(subdf)

this returns:

A B C
1 2 3
1 2 3
3 4 5
3 4 5
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