Back to Basics: Essential Tools in Programming

Julie Delda
Sep 18, 2020 · 4 min read

Hi! Welcome to my blog.

Today, I am going to share with you some of the free tools which you could use to run a program! Are you excited?

Google Colab

What is Colaboratory?

It allows you to write and execute Python in your browser.

What makes it special?

It has no configuration required, has free access to GPUs and has easy sharing!

Let’s try coding!

text cell
code cell

This is an interactive environment called a Colab Notebook. It lets you write text and execute code.

Here are some markdown examples.

And now, let me share with you our exercise using Colab.

To save this, click on File, then Save.

Also, you could save a copy of your Colab notebook directly to Github by clicking on File, then Save a Copy on Github.

You could choose the repository where you want to store the copy.

Want to learn more? Watch this Introduction to Colab.

Jupyter

Welcome to Jupyter!

This is an open-source web application that allows us to run code, equations, visualizations and narrative text. This is use for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Let’s do the exercise.

First, launch the Jupyter Notebook from Anaconda Navigator.

Let us open FTW4-Github-Homework-1.

Click on New, then Python. This will create a new notebook with Python 3.

This is what it look like.

Now, let’s do the coding exercise!

Try to run it by shift + enter. You will then see this as a result.

Cool, right?

Now, let’s try to drop all rows with missing values. Here is the code.

You’ll see that all rows with missing values should have been removed and it is saved on your folder as a new file.

For more information about Jupyter, please feel free to visit jupyter.org

Spyder

Spyder is also available in Anaconda Navigator. Let’s launch it!

And now, let’s do the exercise using Spyder.

To run this, simply click on the green triangle, the Run File, or simply press f5.

You should now see the generated csv file and the saved .py file in the same folder.

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