Looping through pandas data frame while changing row values using regex

Question

-EDIT-

As Daniel Kasatchkow (below) suggested, I have attempted the following:

df._links.str.findall('qwer://abc\\\.x-data\\\.orc/v1/i/\d+/users')

But I get the following output:

0    NaN
1    NaN
2    NaN
3    NaN
4    NaN
5    NaN
...

UPDATE - Still unable to find a solution

Your regex pattern will need to escape the \ and . characters. Also, generally you will need to capture your match with parentheses. — moogle
– moogle, Commented Dec 15, 2016 at 22:28
@moogle Alright. I don't believe that resolves the looping issue. — Enigmatic
– Enigmatic, Commented Dec 15, 2016 at 23:11
@BenF97 Well, it looks like you're trying to regex a dictionary, so instead you'll need to navigate down so that you're regexing a string 'qwer://...' — moogle
– moogle, Commented Dec 15, 2016 at 23:23

Daniel Kasatchkow · Accepted Answer · 2016-12-20 01:12:05Z

1

Try something like this

import pandas as pd

df = pd.DataFrame(["{u'users': {u'href': u'qwer://abc\.x-data\.orc/v1/i/32/users'}, u'self': {u'href': ...","{u'users': {u'href': u'qwer://abc\.x-data\.orc/v1/i/87/users'}, u'self': {u'href': ..."], columns=['_links'])

df._links.str.findall('qwer://abc\\\.x-data\\\.orc/v1/i/\d+/users')

When using regex I find it helpful to trial out the regex on http://pythex.org/

If the data is in a dictionary format, it would be best to convert it over to a DataFrame using pandas.DataFrame.from_dict

edited Dec 20, 2016 at 1:12

answered Dec 16, 2016 at 7:12

Daniel Kasatchkow

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