In order to understand the data science world, we have to understand the data science tools. In this series, we set up the proper environment with Anaconda and Jupyter. Then we explore key packages heavily used in the industry such as Matplotlib, NumPy, and Pandas. This is a must-watch for anyone considering data science as a career.
1. Configuring Your Environment
In this video, we get our initial data science environment configured for doing basic analysis. We first download the Anaconda distribution which provides most of the core packages used by data scientists everyday as well as makes sure we have the most up to date version of python.
2. Jupyter Basics
In this video, we get up to speed on using a Jupyter Notebook for our data science programming. We cover the basic elements of notebooks, why they are helpful for data science, and some common operations.
3. Data Science Packages - Numpy, Pandas
In this video, we explore the functionality of three core data science packages: Numpy, Pandas, and Matplotlib. We go over how they can be used together and some history and background and how they came to be.
Join our Slack channel to ask questions about tutorials and discuss general programming and industry topics: