Review of Python Courses (Part 1)

In this post, I introduced you to my recent work learning Python. Although I’ve done all the exercises and taken lots of notes, I have zipped through tens of Python classes in less than four hours each (on average). For this reason, I certainly would not claim to be a Pythonista or a programming expert.

It’s a start, though, and as a way to help solidify my knowledge a bit, I’m going to go through the courses I have taken and provide brief summaries of them all. In doing this, I will go through my notes to aid with my own learning.

My first class was Introduction to Python. This starts by describing a brief history of Python and the DataCamp setup for programming and console (technical term) usage. The section continues with:

• Variables
• Data types
• Lists
• List slicing
• List manipulation

The course continues on with:

• Functions with round() as an exemplar
• Methods
• Packages
• Numpy
• Array types
• Array subsetting
• Data analysis

Class #2 for me was Intermediate Python. Concepts covered in this class include:

• Data visualization including scatter plots, histograms, and line plots (matplotlib)
• Customizing plots with axis labels, title, ticks, and formatting
• Dictionaries [vs. lists]
• [Pandas] Dataframes (Df)
• Df column/row access (.loc and .iloc accessors)
• Comparison operators
• Boolean operators
• If, elif, else
• Df filtering
• For and while loops
• .enumerate() method
• Loop data structures
• .apply() method
• Random numbers, generators, walks, distributions

Really good introductory stuff, here!