Pandas: dataframe returns nan after applying replace and strip function

Question

I am trying to replace [] values with '' , strip the spaces, and return a clean Dataframe

                   Distance             TGR Grade                 TGR1
0   [342m, 342m, 530m, 342m]         [M, M, RW, RW]            [1, 1, 7, 1]
1   [390m, 390m, 390m, 390m,450]    [M, 7, 6G, X45, X67]       [1, 2, 4, 5, 5]

I have applied several functions but the Dataframe is either returns nan value or it returns the same Dataframe

To from both sides of the values

df[df.columns]=df[df.columns].apply(lambda x:x.str.strip())
df[cols]=df[cols].astype(str).agg(lambda x:x.str.strip("frozenset({''})"),1)
df.replace('\[', '', regex=True)
df.replace('\]', '', regex=True)

but the df still remains the same

Answer 1

Does this answer your question?

df.columns = [''.join(i.split()) for i in df.columns]
df.applymap(lambda x: ''.join(x.strip('\[').strip('\]').split()))

Output:

    Distance                   TGRGrade         TGR1
0   342m,342m,530m,342m        M,M,RW,RW        1,1,7,1
1   390m,390m,390m,390m,450    M,7,6G,X45,X67   1,2,4,5,5

Updated with full code:

from io import StringIO
import pandas as pd

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity='all'

d = '''
"Distance","TGR Grade","TGR1"
"[342m, 342m, 530m, 342m]","[M, M, RW, RW]","[1, 1, 7, 1]"
"[390m, 390m, 390m, 390m,450]","[M, 7, 6G, X45, X67]","[1, 2, 4, 5, 5]"
'''
df = pd.read_csv(StringIO(d))
df
df.columns = [''.join(i.split()) for i in df.columns]
df = df.applymap(lambda x: ''.join(x.strip('\[').strip('\]').split()))
df

Output:

    Distance                     TGR Grade            TGR1
0   [342m, 342m, 530m, 342m]     [M, M, RW, RW]       [1, 1, 7, 1]
1   [390m, 390m, 390m, 390m,450] [M, 7, 6G, X45, X67] [1, 2, 4, 5, 5]

    Distance                     TGRGrade             TGR1
0   342m,342m,530m,342m          M,M,RW,RW            1,1,7,1
1   390m,390m,390m,390m,450      M,7,6G,X45,X67       1,2,4,5,5