CODEWITHSUNDEEP
pythonpandasnltk
still_learning
still_learning

Reputation: 806

Tokenize columns, then combine them

I would like to merge two columns into one as a list of words/tokens. Currently my dataset looks like:

A_Col   B_Col             C_Col
home    my house          I have a new house
paper   research paper    my mobile phone is broken
NaN     NaN               zoe zaczek who
NaN     NaN               two per cent

NaN is a value for empty field.

What I would like to do is the following: keeping column A_Col but merge B_Col and C_Col in order to have something like this:

A_Col   BC_Col            
home    ['my', 'house','I', 'have', 'a', 'new', 'house']
paper   ['research', 'paper', 'my', 'mobile', 'phone', 'is,','broken']
NaN     ['zoe', 'zaczek', 'who']
NaN     ['two', 'per', 'cent']

Looking at the problem, the steps required should be:

For the first two points I am using the following:

df['B_Col'] = df.apply(lambda row: nltk.word_tokenize(row['B_Col']))
df['C_Col'] = df.apply(lambda row: nltk.word_tokenize(row['C_Col']))

For merging the results:

df['BC_Col'] = df['B_Col'] + df['C_Col']

Then I should remove NaN values.

However something does not work in my code as I am not getting the tokenisation for B_Col and C_Col. I hope you can help me to understand my error. Thanks.

Upvotes: 1

Views: 715

Answers (1)

Ayoub ZAROU
Ayoub ZAROU

Reputation: 2417

you could do:

df['BC_Col'] = df['B_Col'].fillna('').str.split() + df['C_Col'].fillna('').str.split()
df

    A_Col   B_Col   C_Col   BC_Col
0   home    my house    I have a new house  [my, house, I, have, a, new, house]
1   paper   research paper  my mobile phone is broken   [research, paper, my, mobile, phone, is, broken]
2   NaN NaN zoe zaczek who  [zoe, zaczek, who]
3   NaN NaN two per cent    [two, per, cent]

Upvotes: 1

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