How to convert list like value in each row into pure value in python dataframe?-CodePudding

I have a dataframe that has a value that looks as belows

colA    desired
[0]       0
[3, 1]    3,1
[3, 1, 2] 3,1,2
[3, 1]    3,1

The type for colA is object. Is there a way to do it? Thanks

CodePudding user response：

without the lambda as that will be slower for larger data sets, you can simply cast the list to a string type then strip unwanted characters.

import pandas as pd
df = pd.DataFrame(data={'colA':[[0], [3,1],[3,1,2],[3,1]]})
df['desired'] = df.colA.astype(str).str.replace('\[|\]|\'', '')
df

Output:

colA            desired
0   [0]         0
1   [3, 1]      3, 1
2   [3, 1, 2]   3, 1, 2
3   [3, 1]      3, 1

CodePudding user response：

Try:

df = pd.DataFrame(data={'colA':[[0], [3,1],[3,1,2],[3,1], [4]]})
df['desired'] = df['colA'].apply(lambda x: ','.join(map(str, x)))

OUTPUT:

        colA desired
0        [0]       0
1     [3, 1]     3,1
2  [3, 1, 2]   3,1,2
3     [3, 1]     3,1
4        [4]       4

If colA is obj:

from ast import literal_eval
df = pd.DataFrame(data={'colA':["[0]", "[3,1]","[3,1,2]","[3,1]", "[4]"]})
df['desired'] = df['colA'].apply(lambda x: ','.join(map(str, literal_eval(x))))

CodePudding user response：

You can use str.replace:

df['desired'] = df['colA'].str.replace(r'[][]', '', regex=True)

Prints:

        colA  desired
0        [0]        0
1     [3, 1]     3, 1
2  [3, 1, 2]  3, 1, 2
3     [3, 1]     3, 1

You can use the regex demo to play with it.