How to delete a certain value in a cell in columns of csv using pandas

Question

I need help with deleting "None" along with extra comma in language columns that have one or more language

Here is the existing csv:

f = pd.DataFrame({'Movie': ['name1','name2','name3','name4'],
                  'Year': ['1905', '1905','1906','1907'],
                  'Id': ['tt0283985', 'tt0283986','tt0284043','tt3402904'],
                  'language':['Mandarin,None','None,Cantonese','Mandarin,None,Cantonese','None,Cantonese']})

Where f now looks like:

   Movie  Year         Id   language
0  name1  1905  tt0283985  Mandarin,None
1  name2  1905  tt0283986  None,Cantonese
2  name3  1906  tt0284043  Mandarin,None,Cantonese
3  name4  1907  tt3402904  None,Cantonese

And the result should be like this:

   Movie  Year         Id             language
0  name1  1905  tt0283985            Mandarian
1  name2  1905  tt0283986            Cantonese
2  name3  1906  tt0284043            Mandarin,Cantonese
3  name4  1907  tt3402904            Cantonese

There are also other columns that have only 'None' values in language column, so I can't just use the replace function in excel, and there's also a problem of extra "," after doing that. So I may need help with a new way using pandas or something. Thanks in advance!

Srinivas Reddy Thatiparthy · Accepted Answer · 2022-03-29 05:14:39Z

2

You could achieve it this way,

f["language"] = f.apply(
    lambda x: ",".join(filter(lambda y: y != "None", x.language.split(","))), axis=1
)

Or much better

f["language"] = f.apply(
    lambda x: ",".join([y for y in x.language.split(",") if y != "None"]), axis=1
)

edited Mar 29, 2022 at 5:14

answered Mar 29, 2022 at 5:06

Srinivas Reddy Thatiparthy

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Comments

le_camerone · Accepted Answer · 2022-03-29 05:03:12Z

2

You could just remove all the None values as follows:

df['language'] = df['language'].str.replace('None,', '')

and then wherever the language column is empty, you could insert a 'None' value using regex.

df['language'] = df['language'].replace(r'^\s*$', 'None', regex=True)

edited Mar 29, 2022 at 5:03

answered Mar 29, 2022 at 4:55

le_camerone

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1 Comment

Charles Yuan Over a year ago

That helps, and I add: df['language'] = df['language'].str.replace('None,', '') so it replace all None. Thanks!

im_vutu · Accepted Answer · 2022-03-29 05:03:59Z

2

You can use replace method to remove 'None' and ','

for i in range(len(f)):
f.loc[i,"language"].replace('None','')
f.loc[i,"language"].replace(',','')
print(f)

answered Mar 29, 2022 at 5:03

im_vutu

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