CODEWITHSUNDEEP
pythonpandas
noob
noob

Reputation: 3811

Remove spaces from words in python pandas

Hi i have a df which is like this

Product
Prod1
Prod 1
Prod2
Prod 2
Prod 2
Prod 3
Prod3  and so on

I basically want to convert all these Prod1 , Prod2 and Prod3 etc to categorical variables. For doing that I need to remove the blank spaces between Prod and the number, for e.g.removing space between Prod and 1 so that Prod1 , Prod 1 etc. become Prod1 so that there are no duplicate entries for same product

Expected output for above table

Product
Prod1
Prod1
Prod2
Prod2
Prod2
Prod3
Prod3  and so on

All answers of strip and all were mentioned for a sentence only . I want an answer which can be replicable to the entire table and remove empty spaces between all the words in a column

Upvotes: 1

Views: 1369

Answers (4)

Lee Jun Wei
Lee Jun Wei

Reputation: 320

I guess this would be the simplest way!

df['Product'] = df['Product'].str.replace(' ','')

Upvotes: 1

Quang Hoang
Quang Hoang

Reputation: 150785

Let's try str.replace with the following pattern to remove spaces between Prod and digits.

df['Product'] = df.Product.str.replace('(Prod)(\s+)(\d)', r'\1\3')

Output:

            Product
0             Prod1
1             Prod1
2             Prod2
3             Prod2
4             Prod2
5             Prod3
6  Prod3  and so on

Upvotes: 3

dimay
dimay

Reputation: 2804

Try it:

df["Product"] = [i.replace(" ", "") for i in df.Product]

Upvotes: 0

Rakesh
Rakesh

Reputation: 82785

Using str.split().agg("".join)

Ex:

df['Product'] = df['Product'].str.split().agg("".join)
#or
#df['Product'] = df['Product'].str.replace(r"(\s+)", "")
print(df)

Output:

  Product
0   Prod1
1   Prod1
2   Prod2
3   Prod2
4   Prod2
5   Prod3
6   Prod3

Upvotes: 4

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