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Installing CLT, Xcode, Hombrew, Python, and Pip for beginners

Python written in VSCode
Python written in VSCode

This blog is part of an ongoing series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow. Check this space for updates about this ongoing project.

I. Hello Python

Python 2.7.7 will be installed on your Mac out of the box. It should be in…


Learn how to create virtual environments for your Python data science projects using Pyenv, Virtualenv, and Pip on Mac OS Big Sur

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow. Check this space for updates about this ongoing project.

If you’ve used Python before, you may have encountered a situation known as “dependency hell”. Some packages…


In the previous section I showed you how to set up your computer for a data science project in Python. In this tutorial, I’ll tell you about the basic data types and operators in Python.

Artistic rendering of Python Code
Artistic rendering of Python Code

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

I. Data Types

Python has about twelve different data types and in this tutorial I’ll introduce you to five of them: string, integer, float, boolean, and list. I’ll also…


A series of tutorials designed to guide beginners through a quick, easy, and end-to-end data science project with Python, Jupyter, Pandas, Matplotlib, and Seaborn.

An abstract photo of melting clocks.
An abstract photo of melting clocks.

Successful data scientists often prescribe projects as the best way to learn data science. Yet, completing an end-to-end project can be daunting as a beginner. There are often bumps in the road when creating a data science environment for the first time and cryptic error messages can be discouraging. I wanted to a develop a resource that would allow beginners to easily start working with popular data science in tools that was packaged in digestible bites with a fairly predictable execution time.

Check this space for updates about this ongoing project.

Completed Sections

Part I: Python Data Science Project Setup (Estimated Completion Time: 1.5 hours)

These tutorials lay the ground work for creating a…


In Pandas II, we began to clean up the Metal Bands by Nation data set. We eliminated an unneeded column and filled some missing values. Now, we are going to examine the other columns, assess their data types and value, and take action as needed.

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

  1. General Setup for Data Science Projects with Python
  2. Virtual Environments I: Installing Pyenv with Homebrew
  3. Virtual Environments II: Creating a Virtual Environment with Pyenv and Installing…

In Pandas I tutorial, we used Jupyter Notebooks and Pandas to begin working the Metal Bands by Nation spreadsheet. We used a few different Pandas methods to do an initial inspection. In this tutorial, we will try to clean up and improve the data frame for analysis.

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

  1. General Setup for Data Science Projects with Python
  2. Virtual Environments I: Installing Pyenv with Homebrew
  3. Virtual Environments II: Creating a Virtual Environment with Pyenv and Installing…

In the last tutorial, I introduced you to Jupyter Notebooks. Now that you have Jupyter notebooks installed, I can show you how to use them to work with data. I will also introduce you to Pandas, a popular library used for working with spreadsheets.

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

  1. General Setup for Data Science Projects with Python
  2. Virtual Environments I: Installing Pyenv with Homebrew
  3. Virtual Environments II: Creating a Virtual Environment with Pyenv and Installing…

In Virtual Environments II and Juypter Notebook I I we created a virtual environment for your project and set up Jupyter Notebooks. Now that you have a nice little environment set up on your local machine inside the folder for your project, it’s time to create your GitHub repository. In this tutorial, we will cover the basics of setting up your workflow with GitHub.

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

I. Why Should I Use GitHub?

GitHub is a powerful tool for collaboration. Using GitHub, you can show case your work to share with others. …


Learn how to install a kernelspec to access your Python data science virtual environments within Jupyter Notebook

A human standing in front of Jupiter
A human standing in front of Jupiter

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow. Check this space for updates about this ongoing project.

In the Creating Virtual Environments for Python Data Science Projects, I explained how to install Pyenv and…


In Virtual Environments I, I explained how to install package managers, the latest release of Python, and Pyenv and Virtualenv. Now that those items are installed, we can set up a virtual environment for a Python project.

Python data science packages, Jupyter, Pandas, Seaborn, Matplotlib
Python data science packages, Jupyter, Pandas, Seaborn, Matplotlib

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

I. Create a Unique Virtual Environment for a Data Science Project with Pyenv-Virtualenv

It’s a good idea to create a new virtual environment for each of your project. So we will start by making a directory for our project.

Christine Egan

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