3. Data Wrangling and Exploration

Now that we have our programming environment set up, experience writing Python in Jupyter, using version control with GitHub (Desktop), and some Golden Rules to guide us…

It’s time to science stuff.

We are going to cover

  • wrangling data (load, clean, alter) with numpy and pandas

  • data visualization with seaborn and, when necessary, matplotlib

  • how to merge data ( safely! )

and introduce you to some seriously high-powered finance datasets. What is data science without BIIIIG DATA?