Ep. 2 Getting familiar with JupyterLab

• After configuring twarc in jupyterlab, helpers can help struggling learners on the twarc2 configuration while the instructor may go over the remaining episode content.
• We’ve written the lesson using @ecodatascience as the solution to the ‘2 Timelines’ so if you do that as an instructor, subsequent code should run as is.

Ep. 3: Anatomy of a Tweet

• The key point is to show a little bit of json and talk people into immediately converting to csv and dataframe
• The difference between timelines and search/filter datasets needs to be made explicit here.

Ep. 4: Twitter Public API

• The final challenge in episode 4 is to live harvest a dataset using a ‘cute’ hashtag. You may wish to pre-harvest a dataset. Beware of improvising: you may get results that you don’t want on your screen.

Code

• This Jupyter Notebook has most lines that use quota or take a long time to run
  are commented out.

• This notebook will run the workshop from start to finish AND consume quota, assuming you have downloaded the appropriate data from the setup page.

• Halfway notebook is a natural starting point for day two if you split this lesson in half. It runs and leaves you with three dataframes in memory.