03_viz.Rmd

# Visualize: `ggplot2`, `plotly`, `tmap`

```{r include=FALSE}
library(htmltools)
```

## Plot

Inspiring people:

- [**Hadley Wickham**](http://hadley.nz): grammar of graphics

    `r img(src='https://avatars1.githubusercontent.com/u/4196', width=200)`

- [**Hans Rosling**](https://www.ted.com/speakers/hans_rosling): Gapminder

    ![](figs/hans-rosling_sexy-stats.jpeg)

    [Gapminder World](http://www.gapminder.org/world) - Wealth & Health of Nations

    [![](figs/gapminder-world_motion-chart.png)](http://www.gapminder.org/world)


### Static: `ggplot`

* [Creating publication quality graphics - Software Carpentry](http://swcarpentry.github.io/r-novice-gapminder/08-plot-ggplot2.html)

#### Scatterplot

```{r, message=F, warning=F, results='hide'}
library(dplyr)
library(ggplot2)
library(gapminder)

# preview data
gapminder

# get range of available data
summary(gapminder)
```

```{r, message=F, warning=F}
# setup dataframe
g = gapminder %>%
  filter(year==2007) %>%   # most recent year 
  mutate(pop_m = pop/1e6)  # population, millions

# plot scatterplot of most recent year 
s = ggplot(g, aes(x=gdpPercap, y=lifeExp)) +
  geom_point()
s

# add aesthetic of size by population
s = s + 
  aes(size=pop_m)
s

# add aesthetic of color by continent
s = s + 
  aes(color=continent)
s

# add title, update axes labels
s = s + 
  ggtitle('Health & Wealth of Nations for 2007') +
  xlab('GDP per capita ($/year)') +
  ylab('Life expectancy (years)')
s

# label legend
s = s + 
  scale_colour_discrete(name='Continent') +
  scale_size_continuous(name='Population (M)')
s
```

**Your Turn**

Now with country emissions datasets...

- [CO2 Emissions from Fossil Fuels since 1751, By Nation - Dataset - Frictionless Open Data](http://data.okfn.org/data/kiliakis/co2-fossil-by-nation)
- [datasets/gdp](https://github.com/datasets/gdp/blob/master/data/gdp.csv)

```{r}

```

#### Boxplot

```{r}
# boxplot by continent
b = ggplot(g, aes(x=continent, y=lifeExp)) +
  geom_boxplot()
b

# match color to continents, like scatterplot
b = b +
  aes(fill=continent)
b

# drop legend, add title, update axes labels
b = b +
  theme(legend.position='none') +
  ggtitle('Life Expectancy by Continent for 2007') +
  xlab('Continent') +
  ylab('Life expectancy (years)')
b
```

**Your Turn**: Make a similar plot but for `gdpPercap`. Be sure to update the plot's aesthetic, axis label and title accordingly.

### Interactive: `plotly`

[ggplot2 | plotly](https://plot.ly/ggplot2/)

```{r, message=F, warning=F}
library(plotly) # install.packages('plotly')

# scatterplot (Note: key=country shows up on rollover)
s = ggplot(g, aes(x=gdpPercap, y=lifeExp, key=country)) +
  geom_point()
ggplotly(s)

# boxplot
ggplotly(b)
```

**Your Turn**: Expand the interactive scatterplot to include all the other bells and whistles of the previous plot in one continuous set of code (no in between setting of s).

### Interactive: Exploding Boxplot

```{r}
library(explodingboxplotR) # devtools::install_github('timelyportfolio/explodingboxplotR')

exploding_boxplot(g,
  y = 'lifeExp',
  group = 'continent',
  color = 'continent',
  label = 'country')
```


### Interactive: Motion Plot

The `googleVis` package ports most of the [Google charts](https://developers.google.com/chart/interactive/docs/gallery) functionality.

For every R chunk must set option `results='asis'`, and once before any googleVis plots, set `op <- options(gvis.plot.tag='chart')`.

- [Rmarkdown and googleVis](https://cran.r-project.org/web/packages/googleVis/vignettes/Using_googleVis_with_knitr.html)

- [googleVis examples](https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis_examples.html)

```{r, results='asis', tidy=F}
suppressPackageStartupMessages({
  library(googleVis) # install.packages('googleVis')
})
op <- options(gvis.plot.tag='chart')

m = gvisMotionChart(
  gapminder %>%
    mutate(
      pop_m = pop / 1e6,
      log_gdpPercap = log(gdpPercap)), 
  idvar='country', 
  timevar='year', 
  xvar='log_gdpPercap', 
  yvar='lifeExp', 
  colorvar='continent',
  sizevar='pop_m')
plot(m)
```

**Your Turn**: Repeat the motion chart with the country having the highest `gdpPercap` filtered out.

## Map

Thematic maps [**`tmap`**](https://github.com/mtennekes/tmap):

- [tmap in a nutshell](https://cran.r-project.org/web/packages/tmap/vignettes/tmap-nutshell.html)
- [tmap modes: plot and interactive view](https://cran.r-project.org/web/packages/tmap/vignettes/tmap-modes.html)

### Static

```{r, results='hide', message=FALSE, warning=FALSE}
library(sf)
library(tmap) # install.packages('tmap')

# load world spatial polygons
data(World)

# inspect values in World
World %>% st_set_geometry(NULL)

# gapminder countries not in World. skipping for now
g %>% 
  anti_join(World, by=c('country'='name')) %>% 
  arrange(desc(pop))

# World countries not in gapminder. skipping for now
World %>% 
  anti_join(g, by=c('name'='country')) %>% 
  arrange(desc(pop_est)) %>%
  select(iso_a3, name, pop_est)

# join gapminder data to World
World = World %>%
  left_join(g, by=c('name'='country'))
```

```{r}
# make map
m = tm_shape(World) +
    tm_polygons('lifeExp', palette='RdYlGn', id='name', title='Life expectancy (years)', auto.palette.mapping=F) +
    tm_style_gray() + tm_format_World()
m
```

### Interactive

```{r}
# show interactive map
tmap_leaflet(m)
```


## References

- [ggplot2-cheatsheet-2.0.pdf](../cheatsheets/ggplot2-cheatsheet-2.0.pdf)
- [Interactive Plots and Maps - Environmental Informatics](http://ucsb-bren.github.io/env-info/wk06_widgets.html)
- [Graphs with ggplot2 - Cookbook for R](http://www.cookbook-r.com/Graphs/#graphs-with-ggplot2)
- [ggplot2 Essentials - STHDA](http://www.sthda.com/english/wiki/ggplot2-essentials)
- [NEON Working with Geospatial Data](http://neon-workwithdata.github.io/NEON-R-Spatio-Temporal-Data-and-Management-Intro/)