{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![](files/images/EscUpmPolit_p.gif \"UPM\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Course Notes for Learning Intelligent Systems"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © Carlos A. Iglesias"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## [Introduction to Machine Learning](2_0_0_Intro_ML.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Table of Contents\n",
"\n",
"* [Advanced Visualisation](#Advanced-Visualisation)\n",
"* [Install seaborn](#Install-seaborn)\n",
"* [Transform Data into Dataframe](#Transform-Data-into-Dataframe)\n",
"* [Visualisation with seaborn](#Visualisation-with-seaborn)\n",
"* [References](#References)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Advanced Visualisation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the previous notebook we developed plots with the [matplotlib](http://matplotlib.org/) plotting library.\n",
"\n",
"This notebook introduces another plotting library, [**seaborn**](https://stanford.edu/~mwaskom/software/seaborn/), which provides advanced facilities for data visualization.\n",
"\n",
"*Seaborn* is a library for making attractive and informative statistical graphics in Python. It is built on top of *matplotlib* and tightly integrated with the *PyData* stack, including support for *numpy* and *pandas* data structures and statistical routines from *scipy* and *statsmodels*.\n",
"\n",
"*Seaborn* requires its input to be *DataFrames* (a structure created with the library *pandas*)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Install seaborn"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You should install the SeaBorn package. Use `conda install seaborn`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Transform Data into Dataframe"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Seaborn* requires that data is represented as a *DataFrame* object from the library *pandas*. \n",
"\n",
"A *DataFrame* is a 2-dimensional labeled data structure with columns of potentially different types. We will not go into the details of DataFrames in this session."
]
},
{
"cell_type": "code",
"execution_count": 1,
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