Reputation: 43
Imagine I have a few values like
test_val1 = 'E 18TH ST AND A AVE'
test_val2 = 'E 31ST ST AND A AVE'
I want to find the 18th, 31st, etc., and replace it with 18/31 - basically removing the suffix but keep the entire string as such.
Expected value
test_val1 = 'E 18 ST AND A AVE'
test_val2 = 'E 31 ST AND A AVE'
Please note that I do not want to remove the "St" which corresponds to 'street', so a blind replacement is not possible.
My approach was to use below (for 'th' at the moment), but it doesn't work since the function cannot keep the value/text in memory to return it.
import regex as re
test_val1.replace('\d{1,}TH', '\d{1,}', regex=True)
I have a column full of these values, so a solution that I can run/apply on a Pnadas column would be really helpful.
Upvotes: 3
Views: 824
Reputation: 11351
For the following sample dataframe
df = pd.DataFrame({"Test": ['E 18TH ST AND A AVE', 'E 31ST ST AND A AVE']})
Test
0 E 18TH ST AND A AVE
1 E 31ST ST AND A AVE
this
df.Test = df.Test.str.replace(r'(\d+)(TH|ST)', lambda m: m.group(1), regex=True)
produces
Test
0 E 18 ST AND A AVE
1 E 31 ST AND A AVE
Is that what you are looking for? Check out the docs for more details.
The lambda
function is used as a repl
function ("replace") whose returns replace the pattern matches in the strings. Per definition it gets as argument the respective match object and has to return a string, usually derived from the match object, but it could be totally unrelated. The function here returns the content of the 1. capture group via the match object method group
: The (\d+)
-part.
Upvotes: 2
Reputation: 43
Take a sample value
test_val = 'E 32ND ST AND A AVE'
I wrapped it in a quick function
import regex as re
def street_suffix_remover(in_val):
for x in re.findall(r"(\d{1,}TH|\d{1,}RD|\d{1,}ST|\d{1,}ND)", in_val):
in_val = in_val.replace(x, re.sub(r"TH|ST|RD|ND","", x))
return(in_val)
Test it on a sample
street_suffix_remover(test_val)
Output
E 32 ST AND A AVE
Ran it on a dataframe as below
test_df['address'] = test_df.apply(lambda row:street_suffix_remover(row['address']), axis=1)
Upvotes: 0
Reputation: 151
I think I can help with the REGEX replacement. It seems like the function that you want to use is actually sub
instead of replace
.
This is the function signature:
re.sub(pattern, repl, string[, count, flags])
Check the official documentation.
Also here is an outstanding answer to a similar question.
Upvotes: 1
Reputation: 11
You mentioned it doesn't work since the function cannot keep the value/text in memory to return it. Is it mandatory NOT to store the value to a different variable?
t1 = 'E 18TH ST AND A AVE'
for t1 in column: #t1 is address in the dataframe column
t2 = t1.split()
t2[1] = re.sub(r'(TH|ST)', '',t2[1])
t1 = ' '.join(t2)
Upvotes: 1