Visualizing Data

Learning Objectives

Understand the components of a point in a graph, an $x$ value, and a $y$ value
Understand how to plot a point on a graph, from a point's $x$ and $y$ value
Get a sense of how to use a graphing library, like Plotly, to answer questions about our data

Introduction

We have spent the last few sections introducing ourselves to various data structures in Python - from strings, integers and booleans, to collections like lists, and dictionaries. In this section, we will see how, with the help of library, we can use these same data structures to display our data.

Visualizing Data with Graphs

As we can see, in our list of cities, each city has a population number. And we can display these various populations in a bar chart.

Working with Plotly

To display our data, there are various Python visualization tools. We prefer Plotly, as it produces nice looking graphs and is easy to work with.

We can easily download the plotly library with the use of pip.

Pip is a package management system that allows us to easily download and install libraries written in Python. If you are working in on Learn, we have already installed pip for you. We will not walk through installing pip here, however you can find instructions on installing pip for Mac or for Windows online.

To install a package with pip, the general pattern is to run pip install and the name of the package. We generally do this from a terminal (whatever that is), but you can also instally packages directly from Jupyter, like so. (You can politely ignore any messages below that say requirement already satisfied.)

!pip install plotly

Requirement already satisfied: plotly in /Users/flatironschool/anaconda/lib/python3.6/site-packages
Requirement already satisfied: pytz in /Users/flatironschool/anaconda/lib/python3.6/site-packages (from plotly)
Requirement already satisfied: nbformat>=4.2 in /Users/flatironschool/anaconda/lib/python3.6/site-packages (from plotly)
Requirement already satisfied: requests in /Users/flatironschool/.local/lib/python3.6/site-packages (from plotly)
Requirement already satisfied: decorator>=4.0.6 in /Users/flatironschool/anaconda/lib/python3.6/site-packages (from plotly)
Requirement already satisfied: six in /Users/flatironschool/anaconda/lib/python3.6/site-packages (from plotly)
Requirement already satisfied: certifi>=2017.4.17 in /Users/flatironschool/.local/lib/python3.6/site-packages (from requests->plotly)
Requirement already satisfied: urllib3<1.23,>=1.21.1 in /Users/flatironschool/.local/lib/python3.6/site-packages (from requests->plotly)
Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /Users/flatironschool/anaconda/lib/python3.6/site-packages (from requests->plotly)
Requirement already satisfied: idna<2.7,>=2.5 in /Users/flatironschool/anaconda/lib/python3.6/site-packages (from requests->plotly)

Now we have plotly on our computer. The next step is to get it into this notebook. We do so with the following two lines.

import plotly

plotly.offline.init_notebook_mode(connected=True)
# use offline mode to avoid initial registration

We bring in the plotly library by using the keyword import followed by our library name, plotly. Then we call the method plotly.offline.init_notebook_mode(connected=True) so that we do not have to connect plotly to a registered account online. If you are wondering how to get this knowledge, you simply ask Google.

Ok, now let's get to try to use plotly to build our first graph. This is what we do.

We create new dictionary and assign it equal to trace0. Then we set x key that points to a list of $x$ values. Similarly, we create a y key with a value of a list of $y$ values.

trace0 = dict(x=['jack', 'jill', 'sandy'], y=[8, 11, 8, 13, 6, 4], type='bar')
trace0

{'type': 'bar', 'x': ['jack', 'jill', 'sandy'], 'y': [8, 11, 8, 13, 6, 4]}

We plot our graph by calling the plotly.offline.iplot method and passing through a list of traces to iplot method.

trace0 = {'type': 'bar', 'x': ['jack', 'jill', 'sandy'], 'y': [8, 11, 8, 13, 6, 4]}


plotly.offline.iplot([trace0])

It may be confusing what a trace is, and how it is different from a plot. The easiest way to explain is to have the iplot method taking an list of two traces, instead of just one.

trace0 = {'type': 'bar', 'x': ['jack', 'jill', 'sandy'], 'y': [8, 11, 8, 13, 6, 4]}
trace1 = {'type': 'bar', 'x': ['jack', 'jill', 'sandy'], 'y': [4, 12, 3, 14, 8, 1]}


plotly.offline.iplot([trace0, trace1])

So as you can see, each trace is an associated collection of data.

Summary

In this section, we saw how we use data visualisations to better understand the data.

To display the data with plotly we need to do a couple of things. First, we install plotly by going to our terminal and running pip install plotly. Then to use the library, we import the plotly library into our notebook. Once the library is loaded in our notebook, it's time to use it. We create a new dictionary with keys of $x$ and $y$, with each key pointing to an array of the $x$ or $y$ values of our points. We can pass through a list of traces, which each trace representing associated data.

walkingalchemy/plotting-data-readme-data-science-pilot

Visualizing Data

Learning Objectives

Introduction

Visualizing Data with Graphs

Working with Plotly

Summary