This blog post was created for my PIC16B class at UCLA (Previously titled: Blog Post 5 - Distinguishing Between Cats and Dogs Ft. TensorFlow).

This blog post was created for my PIC16B class at UCLA (Previously titled: Blog Post 4 - An Intro to Spectral Clustering).

This blog post was created for my PIC16B class at UCLA (Previously titled: Blog Post 3 - Creating a Simple Webapp Ft. Flask).

This blog post was created for my PIC16B class at UCLA (Previously titled: Blog Post 2 - Webscraping for Filmography Recommendations).

In this post I will outline how to create several interesting, interactive data graphics using the NOAA climate data set.

Downloading the Data

As always, the first thing we have to do before constructing any sort of data visualisation is to download and read in the data. To read in the temperature, station-metadata, and countries data, I will be used the Pandas package and running the following lines of code:

In this post I will outline how to construct a data visualisation of the Palmer Penguins data set.

Downloading the Data

This first step might seem a little obvious, but the first thing we have to do before constructing any sort of data visualisation of a data set, we must first download and read in the data. To do so, I will be used the Pandas package and running the following lines of code: