Column of lists, convert list to string as a new column

user_3885217 0
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I have a dataframe with a column of lists which can be created with:

import pandas as pd
lists={1:[[1,2,12,6,'ABC']],2:[[1000,4,'z','a']]}
#create test dataframe
df=pd.DataFrame.from_dict(lists,orient='index')
df=df.rename(columns={0:'lists'})

The dataframe df looks like:

                lists
1  [1, 2, 12, 6, ABC]
2     [1000, 4, z, a]

I need to create a new column called 'liststring' which takes every element of each list in lists and creates a string with each element separated by commas. The elements of each list can be int, float, or string. So the result would be:

                lists    liststring
1  [1, 2, 12, 6, ABC]  1,2,12,6,ABC
2     [1000, 4, z, a]    1000,4,z,a

I have tried various things, including from Converting a Panda DF List into a string:

df['liststring']=df.lists.apply(lambda x: ', '.join(str(x)))

but unfortunately the result takes every character and seperates by comma:

                lists                                         liststring
1  [1, 2, 12, 6, ABC]  [, 1, ,,  , 2, ,,  , 1, 2, ,,  , 6, ,,  , ', A...
2     [1000, 4, z, a]  [, 1, 0, 0, 0, ,,  , 4, ,,  , ', z, ', ,,  , '...

Thanks in advance for the help!

pandas list python string
6 Answers

All of these didn't work for me (dealing with text data) what worked for me is this:

    df['liststring'] = df['lists'].apply(lambda x: x[1:-1])
user_107919310

The previous explanations are well and quite straight forward. But let say if you want to convert multiple columns to string separated format. Without going into individual columns you can apply the following function to dataframe and if any column is a list then it will convert to string format.

def list2Str(lst):
    if type(lst) is list: # apply conversion to list columns
        return";".join(lst)
    else:
        return lst

df.apply(lambda x: [list2Str(i) for i in x])

of course, if you want to apply only to certain columns then you can select the subset of columns as follows

df[['col1',...,'col2']].apply(lambda x: [list2Str(i) for i in x])
user_22341610

Since we're returning a series the same length as our input and only using one series as input, pd.transform immediately came to mind. This worked for me:

df['liststring'] = (
    df['lists'] 
    .transform(
        lambda x: ",".join(map(str,x))    
    )
)

This returns

                lists    liststring
1  [1, 2, 12, 6, ABC]  1,2,12,6,ABC
2     [1000, 4, z, a]    1000,4,z,a

Many thanks to others for the map() fix on the join. Others can also cite the performance benefits better than me, but I believe transform is in general more performant than apply(), but I'm not sure about the list comprehension comparison.

user_75954320

Pipe:

import pandas as pd
lists={1:[[1,2,12,6,'ABC']],2:[[1000,4,'z','a']]}
#create test dataframe
(
    pd.DataFrame.from_dict(lists,orient='index', columns=['lists'])
    .assign(liststring=lambda x: x.lists.astype(str).str[1:-1])
)

Output:

                     lists           liststring
    1   [1, 2, 12, 6, ABC]   1, 2, 12, 6, 'ABC'
    2   [1000, 4, z, a]      1000, 4, 'z', 'a'
user_124546260
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