This past week my adventure took another turn when I started learning Python in my advanced analytics course. From what I read about it, Python was created to be more user-friendly than earlier programming languages, so I was excited to start. The first few lessons were great: how to use Jupyter Notebooks, object-oriented programming, basic data types and data conversions, clean code, functions, and operators. Most things made perfect analogous sense after working with either SQL or r. But then we got to conditional statements and loops. And suddenly, things weren't making as much sense. 

Part of that is simply learning to think more logically. To stop and structure ideas step by step before attempting to move forward. It is a work in progress. But that wasn't all. As I sat there stumped trying to complete programming exercises, I stopped to really think about why I was having so much trouble. And I realized something about the language itself that may have been tripping me up. Python was created to be more user-friendly, to be more like a human language and less like a computer one. When I learned the basics of SQL and r, every word was specifically meaningful. It was a function name, an operator name, an assigned variable, etc. There are no 'just words' when you code in those languages. At least as far as I've seen.

Coding in Python was a surprise because sometimes there are 'just words'. I remember the first time I got completely stumped. I had to get the answer and go back to work through it so I could understand. But when I did, all I could think was "Well, I'd have figured it out if I knew that I could just throw random words in there!". For example:

def purchases_100 (sales):
   count = 0
   
   for customer in sales:
       customer_total = 0
       for purchase in customer:
           customer_total += purchase
       if customer_total >= 100:
           
           count += 1
   return count
 

This lovely bit of code defines a function that we are calling 'purchases_100' that takes an argument 'sales'. It calculates the number of customers who have made purchases over $100 from the list of sales by customer. So you enter the variable name for your sales list and out pops the desired number of customers. The reason this was so confusing for me initially is because 'customer' and 'purchase' are just words. There is no table with these column names. No variable list of elements is actually assigned to these words. For example, here is the tiny list of sales used in the exercise:

sales = [[2.75], [50.0, 50.0], [150.46, 200.12, 111.30]]

Each of the internal brackets represents a single customer's activity, and each of the numbers separated by commas inside that bracket represents the individual purchases made by that customer. So the way the function definition is written makes perfect sense, but it doesn't have to be written that way. Nothing in the little list of sales data says that certain information is labeled 'customer' and other information is labeled 'purchase'. I could as easily write this:

def purchases_100 (sales):
   count = 0
   
   for x in sales:
       x_total = 0
       for y in x:
           x_total += y
       if x_total >= 100:
           
           count += 1
   return count

And the function works the same way. Now, the first way is how it should be written in best practice because it makes clear exactly what the function does in a way that others can easily understand. Also,  you can come back to it later and not be confused by it if you've forgotten what x and y were meant to signify. But the point is that Python lets you have that flexibility. But with that flexibility, it also grants you the option to be unclear. It is truly more like a human language. I think that is why it's almost harder for me to learn. Just like a non-English speaker rolling their eyes at the constant exceptions to the rules and pronunciation, the relative flexibility of verbiage in Python compared to SQL or r, has me floundering a little. 

Ultimately, I can see how the tradeoff is worth it. Python is a powerful programming tool that allows for human flexibility while still communicating in clear ways that computers can understand. I just need to remember to think outside the box a little as I continue my Python journey!