How to combine the Output of Regex Findall in Pandas

Question

I'm exploring regex with pandas in a jupyter notebook. My goal is to extract housenumberadditions from an addressline, using a set of regex patterns.

I'm building upon this post: https://gist.github.com/christiaanwesterbeek/c574beaf73adcfd74997 and I use this for input from a .csv:

Afleveradres
Dorpstraat 2
Dorpstr. 2
Dorpstraat 2
Laan 1933 2
18 Septemberplein 12
Kerkstraat 42-f3
Kerk straat 2b
42nd street, 1337a
1e Constantijn Huigensstraat 9b
Maas-Waalweg 15
De Dompelaar 1 B
Kümmersbrucker Straße 2
Friedrichstädter Straße 42-46
Höhenstraße 5A  
Saturnusstraat 60-75
Saturnusstraat 60 - 75
Plein \'40-\'45 10
Plein 1945 1
Steenkade t/o 56
Steenkade a/b Twee Gezusters
1, rue de l\'eglise
Herestraat 49 BOX1043
Maas-Waalweg 15 15

My goal is to extract the streetnames, housenumbers & housenumberadditions.

So far I basically use:

# get data
file_base_name = 'examples'
dfa = pd.read_csv(''+file_base_name+'.csv', sep=';')

#get number
dfa['num'] = dfa['Afleveradres'].str.extract(r"([,\s]+\d+)\s*")
dfa['num'] = dfa['num'].str.strip()

# split leftover values into street & addition
dfa['tmp']=dfa.Afleveradres.str.replace(r"([,\s]+\d+)\s*", ';')

# new data frame with split value columns 
new = dfa["tmp"].str.split(";", n = 1, expand = True) 
# making separate first name column from new data frame 
dfa["str"]= new[0] 

# making separate last name column from new data frame 
dfa["add"]= new[1] 
dfa.drop(['tmp'], axis=1, inplace=True)

which results in: listing streenames, numbers & addition:

;Afleveradres;str;add;num
0;Dorpstraat 2;Dorpstraat;;2
1;Dorpstr. 2;Dorpstr.;;2
2;Dorpstraat 2;Dorpstraat;;2
3;Laan 1933 2;Laan;2;1933
4;18 Septemberplein 12;18 Septemberplein;;12
5;Kerkstraat 42-f3;Kerkstraat;-f3;42
6;Kerk straat 2b;Kerk straat;b;2
7;42nd street, 1337a;42nd street;a;, 1337
8;1e Constantijn Huigensstraat 9b;1e Constantijn Huigensstraat;b;9
9;Maas-Waalweg 15;Maas-Waalweg;;15
10;De Dompelaar 1 B;De Dompelaar;B;1

So far so good, for now. Next, I'd like to correct for housenumber ranges, like '42-46' and '60 - 65'.

A re.findall returns expected values:

import re

def rem(str):
    pattern = r'[,@\'?\.$%_]'
    if re.match(pattern, str):
        tmp = 'Y'
    else:
        tmp = 'N'
    return tmp

def extract_numrange(row):
    r = ''+row['Afleveradres']
    num_range1 = re.findall(r'([,\s]+\d+\-+\d+)\s*|([,\s]+\d+\s+\-+\s+\d+)\s*',r)

    return num_range1
    # return rem(num_range1)

dfa['excep'] = dfa.apply(extract_numrange, axis=1)
dfa

output re.findall

15  Friedrichstädter Straße 42-46   Friedrichstädter Straße -46 42  [( 42-46, )]
16  Höhenstraße 5A  Höhenstraße A   5   []
17  Saturnusstraat 60-75    Saturnusstraat  -75 60  [( 60-75, )]
18  Saturnusstraat 60 - 75  Saturnusstraat  -;  60  [(, 60 - 75)]

But how do I clean this output, from [( 42-46, )] and [(, 60 - 75)] into something like 42-46 and 60 - 75 in a new column?

Or are there better approaches for my question?

Answer 1

The problem comes from the fact there are two capturing groups. You need to re-vamp the pattern to use only a single capturing group, or get rid of the group altogether.

Your pattern is of the (Group1)\s*|(Group2)\s* type. As you see, all you need is to re-group the parts into (Group1|Group2)\s*.

So, the quickest fix is

([,\s]+\d+\-+\d+|[,\s]+\d+\s+\-+\s+\d+)\s*

See the regex demo.

However, I think you do not need the whitespaces on both ends. Then, move those patterns you do not want to capture out of the grouping:

[,\s]+(\d+\-+\d+|\d+\s+\-+\s+\d+)\s*
^^^^^^

See this regex demo.

Probably, you may reduce this even further to

[,\s](\d+(?:-+|\s+-+\s+)\d+)

See this regex demo, the (?:-+|\s+-+\s+) is a non-capturing group that won't result in additional tuple item.