String Cleaning Function Producing Unexpected Output - data-cleaning

Question

I am looking to clean the profile column of the following dataframe:
name profile
6 Pedro ["\n Design ...
7 Leonardo ["\n Design ...
8 Daniel ["\n JavaScript ...
9 Mario ["\n JavaScript ...
10 Christi ["\n Design ...
I've tested the following function on individual rows...
def clean_profile(row):
for index, row in new_df2["profile"].items():
str_row = str(row)
clean_row = (
'""'.join(str_row)
.replace(",", "")
.replace('""', "")
.replace("\\n ", "")
.replace(" ", "")
)
return clean_row
...and found it to transform this str:
'["\\n Design ","\\n Design "]'
to this cleaned string:
'["Design","Design"]'
(the extra replace methods are necessary to clean really messy strings like this one:)
'{"Tools "" Google Analytics ":null," Google Adsense ":null," MailChimp ":null," Google Adwords ","Containers "" Docker ","Digital "" SEO ":null," Email Marketing ":null," Article Writing ":null," Market Research ":null," Social Media ":null," Inbound Marketing ","*Nix "" Ubuntu ":null," Linux ","Java "" Java ","Python "" Django ":null," Python ":null," Flask ","Databases "" MySQL Management ":null," MongoDB Management ":null," PostgreSQL Management ","Visual "" Brand Design ":null," Graphic Design ":null," Logo Design ","HTML "" HTML ","Version Control "" Git ","PHP "" Laravel ":null," Wordpress ":null," PHP ":null," Symfony ","Mobile "" React Native ","Ruby "" Ruby ":null," Sinatra ":null," Rails ","Project Management "" Agile Methodology ":null," Client Management ":null," Scrum ","English "" Written English ":null," Spoken English ","Configuration Management "" Chef ","Webserver "" Nginx ":null," Apache ","CDN "" AWS CloudFront ":null," Cloudflare ","Other "" C++ ","Experience "" Creative Direction ":null," UI/UX Design ":null," Wireframing ","JavaScript "" JavaScript ":null," TypeScript ":null," Redux ":null," Angular JS ":null," Angular ":null," D3.js ":null," Node.js ":null," React ":null," Flux ":null," Express ","CSS "" SASS ":null," LESS ":null," CSS ","Hosting "" Heroku ":null," Digital Ocean ":null," AWS ","Automated Testing "" TDD ":null," Automated Testing ":null," BDD ":null," Jest ","Traditional "" Outbound Marketing ":null," Brand Strategy ","Data Science "" Data Science ":null," Data Analysis ":null," Machine Learning ":null," Data Visualization ":null," R ":null," Statistics "}'
When I loop through the all rows of the dataframe, I get either this repeated for all rows:
["JavaScriptDevOpsPHPJavaScriptDevOpsPHP"]
or this:
<function clean_profile at 0x0845CB20>
I've tried a few different things and nothing has worked...is anyone able to explain what's going on here and maybe suggest a better way of cleaning these strings?
Thank you!

Answer 1

It looks like you didn't declare an initial clean_row variable outside of the for loop, so your clean_row will always equal whatever string you cleaned last.
def clean_profile(row):
clean_row = "" //added this line
for index, row in new_df2["profile"].items():
str_row = str(row)
clean_row = (
'""'.join(str_row)
.replace(",", "")
.replace('""', "")
.replace("\\n ", "")
.replace(" ", "")
)
return clean_row
Additionally, I'd look into the strip function for your string cleaning. Here is a good example: https://www.geeksforgeeks.org/clean-the-string-data-in-the-given-pandas-dataframe/