Remember the Coursera class I mentioned on the last post? Well, the course was such a success (for both organizers and students) that there is a second part to it.
This course has been so successful that we have decided to push further and offer an entire five-course Python specialization that covers the entire textbook and adds a project-oriented Capstone at the end of the specialization.
The second part of this specialization is about:
- Using Python to Access Web Data
- Using Databases with Python
- Retrieving, Processing and Visualizing Data with Python.
All classes are exceptionally well designed. The content is pertinent and everything taught by Professor Charles Severance is very clear.
The best part: it is very enjoyable. In fact, you might even develop a craving for more Python and especially more data!
Before this class, I never asked myself where to find data. Data: to split, to parse, to format, to clean, to visualize and what not.
So, if you are looking for some data to play with, here are six open data sources:
- UN Data
- European Union Open Data Portal
- London DataStore
- NYC Open Data
- Government of Canada: Open Canada Data
- Montreal Data
If you have a favourite one, not listed here, please share.
Cities data sources contain information about restaurants.
Warning: Hypochondriacs, stay away from the restaurant data 😉
Also, for all newfound data troglodytes out there, here is a gem: Quantopian Fetch Method
“Quantopian [has got] a method called Fetcher which basically lets you grab CSV data from anywhere on the Internet: HTTP, HTTPS” — Dr. Jess Stauth
If you wonder what you can do with data coming from cities around the world, you might find some inspiration through the NYC Python talks. I once attended a meetup where they presented the ins and outs of NYC subway users. It was fun.
Here are some quotes to keep you going:
“It does not matter how slowly you go as long as you do not stop”
“There is no elevator to success. You have to take the stairs”
Have fun coding!