Created
July 16, 2020 17:10
-
-
Save rolambert/687741c0dcecc816690fcdb65c492b71 to your computer and use it in GitHub Desktop.
charts with seaborn
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "name": "Matplotlib and Seaborn.ipynb", | |
| "provenance": [], | |
| "collapsed_sections": [], | |
| "toc_visible": true | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "l0qINRpLqWnn", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "You've used numpy and pandas to read in and manipulate your data from a statistical and mathematical standpoint. Now, you'll use the libraries matplotlib and seaborn to visualize your data, to get insights into your data that the statistics alone may not completely convey.\n", | |
| "\n", | |
| "Mike will be your instructor! Mike is a mathematician with a PhD in Cognitive Science from the University of California, Irvine.\n", | |
| "\n", | |
| "\n", | |
| "**[Intro](https://www.youtube.com/watch?v=4BpAF4MYKm8)**" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "pmBw9EG0qhur", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "#What is Tidy Data?\n", | |
| "\n", | |
| "In this course, it is expected that your data is organized in some kind of tidy format. In short, a [tidy dataset](https://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html) is a tabular dataset where:\n", | |
| "\n", | |
| "each variable is a column\n", | |
| "each observation is a row\n", | |
| "each type of observational unit is a table\n", | |
| "The first three images below depict a tidy dataset. This tidy dataset is in the field of healthcare and has two tables: one for patients (with their patient ID, name, and age) and one for treatments (with patient ID, what drug that patient is taking, and the dose of that drug).\n", | |
| "\n", | |
| "" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "6Qn9Xxa4q5Yv", | |
| "colab_type": "text" | |
| }, | |
| "source": [ |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment