Installing CLT, Xcode, Hombrew, Python, and Pip for beginners
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…
Learn the Python basics so that you can use it for your data science projects.
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. About Python 🐍
Created by Dutch programmer Guido van Rossum at Centrum Wiskunde & Informatica, Python made its debut in 1991. Over thirty years it has gained popularity earned…
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.
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.
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.
Begin learning the essential Pandas methods to begin creating data science projects with Python, head(), info(), sum(), and describe().
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. About Pandas for Data Science in Python
Pandas is a data analysis library that is built on top of Python. This flexible library is useful for manipulating and analyzing data in a variety…
Learn how to use GitHub repositories to share and collaborate on data science projects
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.
I. What is Git?
Git is a version control system — a software tool that allows developers to track and manage…
Learn how to install a kernelspec to access your Python data science virtual environments within Jupyter Notebook
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.
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.
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