How can I remove all non-numeric characters from all the values in a particular column in pandas dataframe?

Question

I have a dataframe which looks like this:

     A       B           C
1   red78   square    big235
2   green   circle    small123
3   blue45  triangle  big657

I need to be able to remove the non-numeric characters from all the rows in column C so that my dataframe looks like:

     A       B           C
1   red78   square    235
2   green   circle    123
3   blue45  triangle  657

I tried using the following but get the error expected string or buffer:

import re
dfOutput.imgID = dfOutput.imgID.apply(re.sub('[^0-9]','', dfOutput.imgID), axis = 0)

What should I do instead?

Code to create dataframe:

dfObject = pd.DataFrame()
dfObject.set_value(1, 'A', 'red78')
dfObject.set_value(1, 'B', 'square')
dfObject.set_value(1, 'C', 'big235')
dfObject.set_value(2, 'A', 'green')
dfObject.set_value(2, 'B', 'circle')
dfObject.set_value(2, 'C', 'small123')
dfObject.set_value(3, 'A', 'blue45')
dfObject.set_value(3, 'B', 'triangle')
dfObject.set_value(3, 'C', 'big657')

Answer 1

Use str.extract and pass a regex pattern to extract just the numeric parts:

In[40]:
dfObject['C'] = dfObject['C'].str.extract('(\d+)', expand=False)
dfObject

Out[40]: 
        A         B    C
1   red78    square  235
2   green    circle  123
3  blue45  triangle  657

If needed you can cast to int:

dfObject['C'] = dfObject['C'].astype(int)

Answer 2

To remove all non-digit characters from strings in a Pandas column you should use str.replace with \D+ or [^0-9]+ patterns:

dfObject['C'] = dfObject['C'].str.replace(r'\D+', '')

Or, since in Python 3, \D is fully Unicode-aware by default and thus does not match non-ASCII digits (like ۱۲۳۴۵۶۷۸۹, see proof) you should consider

dfObject['C'] = dfObject['C'].str.replace(r'[^0-9]+', '')

So,

import re
print ( re.sub( r'\D+', '', '1۱۲۳۴۵۶۷۸۹0') )         # => 1۱۲۳۴۵۶۷۸۹0
print ( re.sub( r'[^0-9]+', '', '1۱۲۳۴۵۶۷۸۹0') )     # => 10

Answer 3

You can use .str.replace with a regex:

dfObject['C'] = dfObject.C.str.replace(r"[a-zA-Z]",'')

output:

        A         B    C
1   red78    square  235
2   green    circle  123
3  blue45  triangle  657