CODEWITHSUNDEEP
pythonpandas
user8560167
user8560167

Reputation:

Remove duplicated letters from pandas column exist only to each other, Python

from this question : Python: Best Way to remove duplicate character from string answer:

''.join(ch for ch, _ in itertools.groupby(string_to_remove)

I know how to remove duplicated letters exists only next to each other, how to apply this solution to column in pandas?

df:

df=pd.DataFrame({'A':['ODOODY','LLHHEELLO'],'B':['NNMminee','DDasdss']})

expected result:

A,B
ODODY,NMine
LHELO,Dasds

tried: df['A'] = df['A'].apply(lambda x: ''.join(ch for ch, _ in itertools.groupby(x['A']))) thanks !

Upvotes: 1

Views: 803

Answers (1)

jezrael
jezrael

Reputation: 862441

Use DataFrame.applymap, if necessary filter columns for remove duplicates:

import itertools
cols = ['A','B']
df[cols] = df[cols].applymap(lambda x: ''.join(ch for ch, _ in itertools.groupby(x)))
#for all columns
#df = df.applymap(lambda x: ''.join(ch for ch, _ in itertools.groupby(x)))
print (df)
       A       B
0  ODODY  NMmine
1  LHELO   Dasds

Solution with DataFrame.apply is possible, but need process each value separately, so aded list comprehension:

df[cols] = df[cols].apply(lambda x: [''.join(ch for ch, _ in itertools.groupby(y)) for y in x])
print (df)
       A       B
0  ODODY  NMmine
1  LHELO   Dasds

Or use Series.apply:

f = lambda x: ''.join(ch for ch, _ in itertools.groupby(x))
df['A'] = df['A'].apply(f)
df['B'] = df['B'].apply(f)

Upvotes: 1

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