Review of Python Courses (Part 3)

In Part 2, I summarized the next three Datacamp courses I took. Today I will continue with courses 6-8.

As a reminder, I introduced you to my recent work learning Python here.

Course #6 was Python Data Science Toolbox, Part 2. This course covers:

• Iterators and iterables
• List and dictionary comprehensions
• Conditionals in comprehensions
• Generator expressions
• Using pandas read_csv iterator for streaming data

The next course I took was Merging Dataframes with pandas. Concepts covered in this course include:

• Reading multiple data files (including use of glob)
• Reindexing dataframes
• Arithmetic with series and dataframes
• Appending and concatenating series and dataframes
• Example of reading multiple files at once with a loop to build dataframe
• Concatenation, keys, and MultiIndexes
• Outer and inner joins
• Converting to, manipulating as, and stacking arrays
• Merging and joining dataframes
• Reshaping and plotting

My course #8 was Introduction to Importing Data in Python. Concepts covered here include:

• Importing text and tabular data
• Flat files
• Importing flat files using NumPy and pandas
• Importing pickled files and Excel spreadsheets
• Importing SAS/Stata files using pandas
• Importing HDF5 and MATLAB files
• Introduction to relational databases
• Creating a database engine in Python
• Querying relational databases in Python and directly with pandas
• Advanced querying: exploiting table relationships

As a bonus, let’s recap my class #9: Intermediate Importing Data with Python. Concepts covered here include:

• Importing flat files from the web with the urllib package
• HTTP requests to import files from the web
• Scraping the web in Python using BeautifulSoup
• Introduction to APIs and JSONs
• APIs and interacting with the world wide web
• The Twitter API and authentication

I will continue summarizing classes later.