04. Setting Up Your System

Running Python Locally

In this course, we'll assume you have the ability to run Python locally. Whether you already have Python installed on your computer or not, we recommend downloading and installing Anaconda. This is a scientific Python installation that comes with a lot of libraries and tools we'll be using in this course, some of which are otherwise very difficult to install.

If you haven't already, go through our short course on Anaconda and Jupyter notebooks to set up your computer.
I've included an environment file you can use to create a conda environment that will provide all the necessary packages and versions for this course. If the resource links open up the environment files as text tiles in your browser, you can use right-click (Win) or control-click (Mac) to open up a menu to "Save as…" to download the file. If you'd like to set up your own environment, this course requires Python 2.7, numpy, pandas, matplotlib, and seaborn.

Downloading Data Files

You should also download the data files from the Resources section. Make sure you save these in the same directory as your IPython notebook. The files we'll be using in this lesson are enrollments.csv, daily_engagement.csv, and project_submissions.csv. daily_engagement_full.csv contains more detailed data than daily_engagement.csv, but it's a larger file (about 500 MB), so downloading and using this file is optional.

You should also download and read table_descriptions.txt, which describes what data is present in each file (or table) and what columns are present. The data has been anonymized, and contains a random selection of Data Analyst Nanodegree students who had completed the first project at the time the data was collected, as well as a random selection of students who had not.