rstrip | ruby executable that removes trailing whitespaces

Based on my local testing using a UTF-8 encoded Python script, isalpha() was returning false for inputs containing characters with accents:

You don't need to use .split()

I would add the celery user to the sudoers file with the only command allowed being the one needed. Use visudo and add these lines

You can probably combine multiple rstrips if you have mixed endings, but the best answer is to use regular expressions.

My thought is to use regex to identify the machines in each string and their intersection:

You can remove the set and do all the operations using list.

See this link for more help.

Solution:

The favorite_language = favorite_language.rstrip() reassigns the favorite_language with new value, which is the value returned from the favorite_language.rstrip().

The favorite_language.rstrip() itself does not change the original string (str() in Python is immutable in any case) just by calling the method. To have the favorite_language modified we have to explicitly say:

"Hey, favorite_language, here's new value for you".

Which is: favorite_language = new_value

But in this case the new value is the value that the favorite_language.rstrip() returns.

All the expressions on the right side of the = are evaluated before any assignment happens. Also, since str() in Python is immutable, calling favorite_language.rstrip() is not modifying anything, it produces new value, which then can be stored in the favorite_language. So, the production of the new value happens before any reassignment.

For more on the evaluation order (and many more), check the documentation.

The pandas DataFrame is designed for tabular data in which all the entries in any one column have the same type (e.g. integer or string). One row usually represents one instance, sample, or individual. So the natural way to parse your data into a DataFrame is to have two rows, one for each institution, and define the columns as what you have called index (perhaps with the address split into several columns), e.g. business type, street, city, state, post code, phone number, etc.

So there would be one row per institution, and the index would be used to assign a unique identifier to each of them. That's why it's desirable for the index to contain no duplicates.

You have lots of unnecessary for loops. The only loop you need is for the lines in the file, you don't need to loop over the characters in fields when you're splitting them or removing something from the whole field.

At the end, you should be adding the result of the calculation to a dictionary.