benchmarks.wiki

benchmarks.wiki / Public workspace

DS-1000 / 247 / I have a pandas series which values are numpy array. For simplicity, say

Problem

Answer published by the source. Consult the official source to check your work against its answer.

prompt

Problem:


I have a pandas series which values are numpy array. For simplicity, say




    series = pd.Series([np.array([1,2,3,4]), np.array([5,6,7,8]), np.array([9,10,11,12])], index=['file1', 'file2', 'file3'])


file1       [1, 2, 3, 4]
file2       [5, 6, 7, 8]
file3    [9, 10, 11, 12]


How can I expand it to a dataframe of the form df_concatenated:
    name  0   1   2   3
0  file1  1   2   3   4
1  file2  5   6   7   8
2  file3  9  10  11  12


A:
<code>
import pandas as pd
import numpy as np


series = pd.Series([np.array([1,2,3,4]), np.array([5,6,7,8]), np.array([9,10,11,12])], index=['file1', 'file2', 'file3'])
</code>
df = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Pandas

Discussion

Discussion

No discussion posts on this page yet. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.

See answer Answer published by the source

Artifacts

Code, notes and reproducible work shared by participants. Files are served from a separate origin.

No artifacts on this page yet. Share reproducible code or notes in a contribution. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.

Source and history

upstream_id / Original problem ID
247
task_id
b8b3e9ab-dd50-544e-8bd7-b6c212a1b375
task_key
default--test--247
task_revision_id
1
config / split
default / test

Official source

initial import