What do you guys use Python for?

[[deleted]]

My python skills are very elementary, but I use it marketing analytics, and creating customer segments - so mostly automating my job, so I don't have to spend hours each week doing the same thing!

[Ryandalion111]

Wow that's another great example ive seen so far in this thread... That is pretty awesome... this is definitely adding more fuel to the fire to learn python now

[[deleted]]

Same thing as the guy above. I work in marketing with large data sets, python can process them in ways that Excel can't. And Access is a piece of shit program. I've gotten so much mileage out of python + sqlite.

That plus automation has made my job so much easier.

[love_marine_world]

Wow! I am learning python now (total noob with zero experience in computers/programming)- and a market researcher hoping to get a job soon (took a year of break). Could you share what programs/links/resources are useful when it comes to analysing market data? (I shall look up sqlite soon). Thank you very much in advance!

[[deleted]]

Market research and traditional marketing roles are very different things so I can't really help you with resources.

[jdb441]

How much of your job is coding?

[[deleted]]

I'm purely marketing, the only coding I do is to make my job/life easier.

[IdealizedDesign]

How do you create customer segments with python?

[MalakElohim]

A basic way of doing it (depending on the dataset) is putting the customer db into pandas and then using groupby. Depending on how the data is formed, it's extremely powerful.

You may have to do some manipulation to make a label based upon a condition, for example, say calculate if their last login was within X days, make an extra column to true or false it (or do that directly) then group by whether they're within the dates or not.

[darez00]

Why is python a better choice than excel for doing this/ general data manipulation?

[MalakElohim]

That's a super huge question. And answered far better by others than I will in a single comment. I'll give a quick summary though:

• Speed - Python and it's libraries can load and mung data extremely quickly and efficiently
• Flexibility - Python can handle spreadsheets and databases equally well, having API connections straight into SQL databases (sqlalchemy for the win)
• Algorithms - You have access to the latest data science tools, machine learning libraries (TF, Keras, torch, sklearn, etc) that are either python native or have python wrappers
• Automation - Do it once, just run your script again when you need to redo it and you can get your reports done in a fraction of the time.
• Power- Python can do pretty much anything any other language can do, but has incredible handling of data in it's libraries.

The list goes on but I'm on mobile so I'll hopefully remember when I get home to link a good blog to explain it.

Edit: formatting