how to extract numbers from a string that starts with numbers in a column using python

Question

I am new to Python and I have a dataframe for which I want to extract the numbers from the beginning of string. For example:

import numpy as np
import pandas as pd
Test = {'Text': ['/CY1000 HZ 23 Street Arizona','/3456 BZ 33 Rue Avenue France','/2222 6th Street Madrid', np.nan],
    'Price': [22000,25000,27000,35000]}
df = pd.DataFrame(Test,columns= ['Text', 'Price'])

and I want to put 1000,3456,2222,NaN on to another column and have the rest of the text in another column to have

Test = {'Text': ['/CY1000 HZ 23 Street Arizona','/3456 BZ 33 Rue Avenue France','/2222 6th Street Madrid', np.nan],
        'Text1': ['1000','3456','2222',np.nan],
    'Price': [22000,25000,27000,35000],
     'Text2': [ 'HZ 23 Street Arizona', 'BZ 33 Rue Avenue France','6th Street Madrid', 'Nan']}
df = pd.DataFrame(Test,columns= ['Text', 'Text1','Text2','Price'])

Thanks in advance

Answer 1

This would get you the digits:

^(?:[^0-9]+)?([0-9]+)

And your desired data would be inside \\1

https://regex101.com/r/i4YfeV/1

Answer 2

You this code to extract number from string.

    import re
    Test = {'Text': ['/CY1000 HZ 23 Street Arizona','/3456 BZ 33 Rue Avenue France','/2222 6th Street Madrid'],
        'Price': [22000,25000,27000,35000]}
    print(Test['Text'])
    temp = re.findall(r'^(?:[^0-9]+)?([0-9]+)', Test['Text'][0]) 
    print(temp)
    temp1 = re.findall(r'^(?:[^0-9]+)?([0-9]+)', Test['Text'][1]) 
    print(temp1)

Output will be :

[1000]
[3456]

Answer 3

Test = {'Text': ['/CY1000 HZ 23 Street Arizona','/3456 BZ 33 Rue Avenue France','/2222 6th Street Madrid', np.nan],
    'Price': [22000,25000,27000,35000]}
df = pd.DataFrame(Test,columns= ['Text', 'Price'])

vals= []
for x in df.Text:
    if x is np.nan:
        x=""
    num = re.findall(r'\d+',x)
    if len(num)>0:
        vals.append(num[0])
    else:
        vals.append(np.nan)

print(vals)

df['Text1'] = vals
print(df)

Output:

['1000', '3456', '2222', nan]
                            Text  Price Text1
0   /CY1000 HZ 23 Street Arizona  22000  1000
1  /3456 BZ 33 Rue Avenue France  25000  3456
2        /2222 6th Street Madrid  27000  2222
3                            NaN  35000   NaN

[EDIT] If for regex expression you can use this:

'/?([A-Z]+)?([0-9]+){1}'

and the match will be in group 2 ie /2.

[EDIT2] If for regex expression you can use this to extract only address(Based on comment):

'/?([A-Z]+)?([0-9]+){1} ([0-9A-Za-z ]+)'

and the match will be in group 3 ie /3.