Thank you for participating in the Introduction to Python for Data Visualization workshop. In preparation for the workshop, we ask that you please follow this guide to install Anaconda Python (a simplified Python distribution) for your particular operating system, as well as download the data that we will be using in advance of the workshop. If you have trouble with any of these steps, please don't hesitate to contact the workshop presenter Pete Lawson: firstname.lastname@example.org who will be happy to assist you in getting set up for the workshop.
Python is a popular language for scientific computing, and great for
general-purpose programming as well. Installing all of its scientific packages
individually can be a bit difficult, however, so we recommend the all-in-one
Regardless of how you choose to install it, please make sure you install Python
version 3.x (e.g., 3.7 is fine). Also, please set up your Python environment at
least a day in advance of the workshop. If you encounter problems with the
installation procedure, ask your workshop organizers via e-mail for assistance so
you are ready to go as soon as the workshop begins.
Note that the following installation steps require you to work from the shell. If you run into any difficulties, please request help before the workshop begins.
Anaconda3-into the terminal window and press tab. The name of the file you just downloaded should appear.
yesand press enter to approve the license. Press enter again to approve the default location for the files. Type
yesand press enter to prepend Anaconda to your
PATH(this makes the Anaconda distribution your user's default Python)
The data we will be using is taken from the gapminder dataset. To obtain it, download and unzip the file python-novice-gapminder-data.zip to your desktop. In order to follow the presented material, you will be launching the Jupyter Notebook server in the same directory your data is stored, so be sure to take note of the location you save the gapminder dataset.
During the day of the workshop we will also utilize the link http://bit.ly/2cLzoxH to download a more advanced gapminder dataset directly into our csv reader.