remove special characters and string from df columns in python

Question

Currently my column is of object type and I'm trying to convert it to type numeric. But it shows the error because of special characters and string contained in it.

error:

ValueError: Unable to parse string "7`" at position 3298

code:

data['col1']=pd.to_numeric(data.col1)

So, I want to remove the special char and string from the columns that requires only number and col1 being one of it. Any suggested solution?

Rakesh · Accepted Answer · 2019-07-01 07:11:48Z

2

Using str.replace with regex pattern.

Ex:

df = pd.DataFrame({"col1": ["7`", "123", "AS123", "*&%3R4"]})
print(pd.to_numeric(df['col1'].str.replace(r"[^\d]", "")))

Output:

0      7
1    123
2    123
3     34
Name: col1, dtype: int64

answered Jul 1, 2019 at 7:11

Rakesh

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2 Comments

renny Over a year ago

Thanks. can you elaborate on what this "r"[^\d]" does?

Rakesh Over a year ago

replace everything except numbers.

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