CODEWITHSUNDEEP
pythonregexpandaspython-re
rooya sh
rooya sh

Reputation: 37

Remove all the characters and numbers except comma

I am trying to remove all the characters from string in the DataFrame column but keep the comma but it still removes everything including the comma.

I know the question has been asked before but I tried many answers and all remove the comma as well.

df[new_text_field_name] = df[new_text_field_name].apply(lambda elem: re.sub(r"(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)|^rt|http.+?", "", str(elem)))

sample text:

'100 % polyester, Paperboard (min. 30% recycled), 100% polypropylene',

the required output:

' polyester, Paperboard , polypropylene',

Upvotes: 1

Views: 1594

Answers (2)

gremur
gremur

Reputation: 1690

Possible solution is the following:

# pip install pandas

import pandas as pd
pd.set_option('display.max_colwidth', 200)

# set test data and create dataframe
data = {"text": ['100 % polyester, Paperboard (min. 30% recycled), 100% polypropylene','Polypropylene plastic', '100 % polyester, Paperboard (min. 30% recycled), 100% polypropylene', 'Bamboo, Clear nitrocellulose lacquer', 'Willow, Stain, Solid wood, Polypropylene plastic, Stainless steel, Steel, Galvanized, Steel, 100% polypropylene', 'Banana fibres, Clear lacquer', 'Polypropylene plastic (min. 20% recycled)']}
df = pd.DataFrame(data)

def cleanup(txt):
    re_pattern = re.compile(r"[^a-z, ()]", re.I)
    return re.sub(re_pattern, "", txt).replace("  ", " ").strip()

df['text_cleaned'] = df['text'].apply(cleanup)
df

Returns

enter image description here

Upvotes: 2

lata singh
lata singh

Reputation: 1

Character.isDigit() and Character.isLetter() functions can be used to identify whether it is number or character.

Upvotes: -1

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