Learning how to learn....

Outline

Context

Learning approaches

Plotly API

{context}

So far.....

Read interesting data into an analysis program

Wrangle the data to ask questions about it

Write and share reports with interesting insights

Understanding of R programming syntax

Ability to use Git and GitHub to track code

What's next....

Interactive graphics

Dynamic applications

Introduction to analytical methods

Visualization and coding principles

Collaborative coding techniques

{learning approaches}

If you wanted to learn how to make a map in R, what steps would you take?

Well....

{then what....?}

Build an example

Start with documentation

Top-down Approach

Start with an example

Consult documentation

Bottom-up Approach

Exercise 1: Getting Started

Find the Plotly R documentation

Find an example of a Plotly R bubble map

Get an example of a bubble map up and running

But what does all this mean?

g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showland = TRUE,
  landcolor = toRGB("gray85"),
  subunitwidth = 1,
  countrywidth = 1,
  subunitcolor = toRGB("white"),
  countrycolor = toRGB("white")
)

If you wanted to figure out what all that syntax meant, what would you do?

Reference code

Start with documentation

Top-down Approach

g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showland = TRUE,
  landcolor = toRGB("gray85"),
  subunitwidth = 1,
  countrywidth = 1,
  subunitcolor = toRGB("white"),
  countrycolor = toRGB("white")
)

Fiddle with your code

Consult documentation

Bottom-up Approach

g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showland = TRUE,
  landcolor = toRGB("gray85"),
  subunitwidth = 1,
  countrywidth = 1,
  subunitcolor = toRGB("white"),
  countrycolor = toRGB("white")
)

Exercise 2: Digging in

Determine what different parameters actually do

Use whatever approach is appropriate

Take good notes!

So, what else do you need to do get the map that you want?

Get your data in the right format

Wide data

Long  data

Long data will let you group by column and compare computed values

Find other examples

Consult documentation

Add / remove parameters

Exercise 3

Resources

Plotly documentation

Plotly examples

Assignments

Assignment-6: Mapping Shootings (due Wed. 2/17)

plotly-mapping

By Michael Freeman

plotly-mapping

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