ETC5521: Exploratory Data Analysis

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# .monash-blue[ETC5521: Exploratory Data Analysis]

<br>

<h2 style="font-weight:900!important;">Exploring data having a space and time context</h2>

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Lecturer: *Di Cook*

<i class="fas fa-envelope"></i>  ETC5521.Clayton-x@monash.edu

<i class="fas fa-calendar-alt"></i> Week 10 - Session 1

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# .monash-white[You show me continents, I see the islands,]

# .monash-white[You count the centuries, I blink my eyes]

.monash-white[[Björk](https://www.bjork.com)]

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# Outline

### .monash-orange2[First part]

- Breaking up data by time, and by space
- Maps of space over time
- Exploring time over space with glyph maps

<br>

### .monash-orange2[Second part]

- Capturing spatial trend
- Bending the choropleth map 
- A flash back to the 1970s: Tukey's median polish

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# .orange[Case study] .bg-orange.circle[1] Temperature change in Americas

.panelset[
.panel[.panel-name[data]
6 years of monthly measurements of a 24x24 spatial grid from Central America collated by Paul Murrell, U. Auckland.

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<td headers="x" class="gt_row gt_right">1</td>
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<td headers="date" class="gt_row gt_right">1995-01-01</td>
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<td headers="ozone" class="gt_row gt_right">260</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">297.4</td>
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<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-111.29565</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
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<td headers="cloudlow" class="gt_row gt_right">31.5</td>
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<td headers="ozone" class="gt_row gt_right">260</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">297.4</td>
<td headers="temperature" class="gt_row gt_right">296.5</td>
<td headers="id" class="gt_row gt_right">2-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">3</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-108.79130</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
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<td headers="cloudlow" class="gt_row gt_right">32.5</td>
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<td headers="ozone" class="gt_row gt_right">260</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">297.4</td>
<td headers="temperature" class="gt_row gt_right">296.0</td>
<td headers="id" class="gt_row gt_right">3-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">4</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-106.28696</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.0</td>
<td headers="cloudlow" class="gt_row gt_right">39.0</td>
<td headers="cloudmid" class="gt_row gt_right">4.0</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">296.9</td>
<td headers="temperature" class="gt_row gt_right">296.5</td>
<td headers="id" class="gt_row gt_right">4-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">5</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-103.78261</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">0.5</td>
<td headers="cloudlow" class="gt_row gt_right">48.0</td>
<td headers="cloudmid" class="gt_row gt_right">4.5</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">296.5</td>
<td headers="temperature" class="gt_row gt_right">295.5</td>
<td headers="id" class="gt_row gt_right">5-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">6</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-101.27826</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">0.0</td>
<td headers="cloudlow" class="gt_row gt_right">50.0</td>
<td headers="cloudmid" class="gt_row gt_right">2.5</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">296.5</td>
<td headers="temperature" class="gt_row gt_right">295.0</td>
<td headers="id" class="gt_row gt_right">6-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">7</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-98.77391</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">0.0</td>
<td headers="cloudlow" class="gt_row gt_right">51.0</td>
<td headers="cloudmid" class="gt_row gt_right">4.5</td>
<td headers="ozone" class="gt_row gt_right">256</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">295.5</td>
<td headers="temperature" class="gt_row gt_right">295.5</td>
<td headers="id" class="gt_row gt_right">7-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">8</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-96.26957</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">0.0</td>
<td headers="cloudlow" class="gt_row gt_right">52.5</td>
<td headers="cloudmid" class="gt_row gt_right">5.0</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">295.5</td>
<td headers="temperature" class="gt_row gt_right">295.0</td>
<td headers="id" class="gt_row gt_right">8-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">9</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-93.76522</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">0.5</td>
<td headers="cloudlow" class="gt_row gt_right">54.0</td>
<td headers="cloudmid" class="gt_row gt_right">8.5</td>
<td headers="ozone" class="gt_row gt_right">256</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">295.0</td>
<td headers="temperature" class="gt_row gt_right">295.0</td>
<td headers="id" class="gt_row gt_right">9-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">10</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-91.26087</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.0</td>
<td headers="cloudlow" class="gt_row gt_right">56.0</td>
<td headers="cloudmid" class="gt_row gt_right">11.5</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">294.6</td>
<td headers="temperature" class="gt_row gt_right">294.6</td>
<td headers="id" class="gt_row gt_right">10-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">11</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-88.75652</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.0</td>
<td headers="cloudlow" class="gt_row gt_right">56.0</td>
<td headers="cloudmid" class="gt_row gt_right">11.5</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">294.6</td>
<td headers="temperature" class="gt_row gt_right">294.6</td>
<td headers="id" class="gt_row gt_right">11-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">12</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-86.25217</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.0</td>
<td headers="cloudlow" class="gt_row gt_right">60.5</td>
<td headers="cloudmid" class="gt_row gt_right">12.5</td>
<td headers="ozone" class="gt_row gt_right">254</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">294.1</td>
<td headers="temperature" class="gt_row gt_right">294.6</td>
<td headers="id" class="gt_row gt_right">12-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">13</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-83.74783</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.5</td>
<td headers="cloudlow" class="gt_row gt_right">57.0</td>
<td headers="cloudmid" class="gt_row gt_right">19.5</td>
<td headers="ozone" class="gt_row gt_right">254</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">293.2</td>
<td headers="temperature" class="gt_row gt_right">294.6</td>
<td headers="id" class="gt_row gt_right">13-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">14</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-81.24348</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">2.5</td>
<td headers="cloudlow" class="gt_row gt_right">57.0</td>
<td headers="cloudmid" class="gt_row gt_right">20.0</td>
<td headers="ozone" class="gt_row gt_right">252</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">293.2</td>
<td headers="temperature" class="gt_row gt_right">294.6</td>
<td headers="id" class="gt_row gt_right">14-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">15</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-78.73913</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.5</td>
<td headers="cloudlow" class="gt_row gt_right">53.5</td>
<td headers="cloudmid" class="gt_row gt_right">22.0</td>
<td headers="ozone" class="gt_row gt_right">254</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">293.2</td>
<td headers="temperature" class="gt_row gt_right">294.6</td>
<td headers="id" class="gt_row gt_right">15-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">16</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-76.23478</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.0</td>
<td headers="cloudlow" class="gt_row gt_right">51.5</td>
<td headers="cloudmid" class="gt_row gt_right">24.5</td>
<td headers="ozone" class="gt_row gt_right">254</td>
<td headers="pressure" class="gt_row gt_right">995</td>
<td headers="surftemp" class="gt_row gt_right">293.6</td>
<td headers="temperature" class="gt_row gt_right">295.5</td>
<td headers="id" class="gt_row gt_right">16-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">17</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-73.73043</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.0</td>
<td headers="cloudlow" class="gt_row gt_right">52.0</td>
<td headers="cloudmid" class="gt_row gt_right">16.5</td>
<td headers="ozone" class="gt_row gt_right">256</td>
<td headers="pressure" class="gt_row gt_right">1000</td>
<td headers="surftemp" class="gt_row gt_right">295.0</td>
<td headers="temperature" class="gt_row gt_right">296.0</td>
<td headers="id" class="gt_row gt_right">17-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">18</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-71.22609</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">1.5</td>
<td headers="cloudlow" class="gt_row gt_right">37.5</td>
<td headers="cloudmid" class="gt_row gt_right">8.0</td>
<td headers="ozone" class="gt_row gt_right">256</td>
<td headers="pressure" class="gt_row gt_right">995</td>
<td headers="surftemp" class="gt_row gt_right">296.9</td>
<td headers="temperature" class="gt_row gt_right">296.9</td>
<td headers="id" class="gt_row gt_right">18-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">19</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-68.72174</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">14.0</td>
<td headers="cloudlow" class="gt_row gt_right">12.5</td>
<td headers="cloudmid" class="gt_row gt_right">22.5</td>
<td headers="ozone" class="gt_row gt_right">258</td>
<td headers="pressure" class="gt_row gt_right">690</td>
<td headers="surftemp" class="gt_row gt_right">294.6</td>
<td headers="temperature" class="gt_row gt_right">288.3</td>
<td headers="id" class="gt_row gt_right">19-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
    <tr><td headers="time" class="gt_row gt_right">1</td>
<td headers="y" class="gt_row gt_right">1</td>
<td headers="x" class="gt_row gt_right">20</td>
<td headers="lat" class="gt_row gt_right">-21.2</td>
<td headers="long" class="gt_row gt_right">-66.21739</td>
<td headers="date" class="gt_row gt_right">1995-01-01</td>
<td headers="cloudhigh" class="gt_row gt_right">29.5</td>
<td headers="cloudlow" class="gt_row gt_right">7.0</td>
<td headers="cloudmid" class="gt_row gt_right">30.0</td>
<td headers="ozone" class="gt_row gt_right">256</td>
<td headers="pressure" class="gt_row gt_right">680</td>
<td headers="surftemp" class="gt_row gt_right">292.7</td>
<td headers="temperature" class="gt_row gt_right">288.8</td>
<td headers="id" class="gt_row gt_right">20-1</td>
<td headers="day" class="gt_row gt_right">0</td>
<td headers="month" class="gt_row gt_right">1</td>
<td headers="year" class="gt_row gt_right">1995</td></tr>
  </tbody>
  
  
</table>
</div>
]
]
.panel[.panel-name[R]

```r
data(nasa)
nasa %>% slice_head(n=20) %>% gt()
```

]
]

---
# Spatiotemporal object in R: cubble

.flex[
.w-45[
.s300.f5[

```r
nasa_cb <- as_cubble(as_tibble(nasa), 
                     key=id, 
                     index=time, 
                     coords=c(long, lat))
nasa_cb
```

```
## # cubble:   key: id [576], index: time, nested form
## # spatial:  [-113.8, -21.2, -56.2, 36.2], Missing CRS!
## # temporal: time [int], date [dttm], cloudhigh [dbl], cloudlow [dbl], cloudmid [dbl], ozone [int], pressure [int], surftemp [dbl], temperature [dbl], day [dbl], month [dbl], year [dbl]
##        y     x   lat   long id    ts                
##    <int> <int> <dbl>  <dbl> <chr> <list>            
##  1     1     1 -21.2 -114.  1-1   <tibble [72 × 12]>
##  2     1     2 -21.2 -111.  2-1   <tibble [72 × 12]>
##  3     1     3 -21.2 -109.  3-1   <tibble [72 × 12]>
##  4     1     4 -21.2 -106.  4-1   <tibble [72 × 12]>
##  5     1     5 -21.2 -104.  5-1   <tibble [72 × 12]>
##  6     1     6 -21.2 -101.  6-1   <tibble [72 × 12]>
##  7     1     7 -21.2  -98.8 7-1   <tibble [72 × 12]>
##  8     1     8 -21.2  -96.3 8-1   <tibble [72 × 12]>
##  9     1     9 -21.2  -93.8 9-1   <tibble [72 × 12]>
## 10     1    10 -21.2  -91.3 10-1  <tibble [72 × 12]>
## # ℹ 566 more rows
```
]

]
.w-5[
.white[space]
]
.w-45[
.s300.f5[

```r
nasa_cb %>% face_temporal()
```

```
## # cubble:   key: id [576], index: time, long form
## # temporal: 1 -- 72 [1], no gaps
## # spatial:  y [int], x [int], lat [dbl], long [dbl]
##    id     time date                cloudhigh cloudlow cloudmid ozone pressure surftemp temperature   day month  year
##    <chr> <int> <dttm>                  <dbl>    <dbl>    <dbl> <int>    <int>    <dbl>       <dbl> <dbl> <dbl> <dbl>
##  1 1-1       1 1995-01-01 00:00:00       0.5     31        2     260     1000     297.        297.     0     1  1995
##  2 1-1       2 1995-02-01 00:00:00       1       33.5      3     254     1000     299.        298.    31     2  1995
##  3 1-1       3 1995-03-01 00:00:00       2       25.5      4     254     1000     298.        298.    59     3  1995
##  4 1-1       4 1995-04-01 00:00:00       4       33.5      5.5   244     1000     299.        299.    90     4  1995
##  5 1-1       5 1995-05-01 00:00:00       6.5     36.5     14     250     1000     298.        297.   120     5  1995
##  6 1-1       6 1995-06-01 00:00:00       3.5     36       10     256     1000     295         296.   151     6  1995
##  7 1-1       7 1995-07-01 00:00:00       1       42.5      6     268     1000     296.        296    181     7  1995
##  8 1-1       8 1995-08-01 00:00:00       0       45.5      1     276     1000     295.        294.   212     8  1995
##  9 1-1       9 1995-09-01 00:00:00       0       43.5      3.5   274     1000     295         294.   243     9  1995
## 10 1-1      10 1995-10-01 00:00:00       1       40        5     282     1000     295         295.   273    10  1995
## # ℹ 41,462 more rows
```
]

<br><br>
Like a `tibble` but can .monash-blue2[pivot back and forth between spatial and temporal] components.

]
]

---
# .orange[Case study] .bg-orange.circle[1] Temperature change in Americas

.flex[
.w-50[
.panelset[
.panel[.panel-name[plot]
<img src="images/lecture-10A/spatial-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[R]
.f5[

```r
nasa_cb %>% 
  ggplot() + 
  geom_point(aes(x=long, y=lat)) +
  geom_point(data=filter(nasa_cb, 
       x==5, y==20),
       aes(x=long, y=lat),
       colour="orange", size=4) +
  geom_point(data=filter(nasa_cb, 
       x==20, y==2),
       aes(x=long, y=lat),
       colour="turquoise", size=4)
```
]
]
]

]

.w-50[
.panelset[
.panel[.panel-name[plot]

<img src="images/lecture-10A/temporal-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[R]
.f5[

```r
nasa_cb_f <- nasa_cb %>% 
  face_temporal() 
ggplot(nasa_cb_f) + 
  geom_line(aes(x=date, 
                 y=surftemp, 
                 group=id), alpha=0.2) +
  geom_line(data=filter(nasa_cb_f , 
       id=="5-20"),
       aes(x=date, 
                 y=surftemp, 
                 group=id),
       colour="orange", linewidth=2) +
  geom_line(data=filter(nasa_cb_f , 
       id=="20-2"),
       aes(x=date, 
                 y=surftemp, 
                 group=id),
       colour="turquoise", linewidth=2)
```
]
]
]
]
]
---
# Pre-processing of time and space

<center>
.info-box[Think of .monash-orange2[time] and .monash-orange2[space] as .monash-orange2[ordered categorical variables].] 
</center>

- Time may need to be converted to categories. 
- Spatial variable *might* need to be discretised, or gridded.

<br>
<br>
For the nasa data, this is already done. Time is an integer from 1 to 72 (6 years of 12 months), as well as a date, and month and year. Space is a 24x24 grid of longitude and latitude, and also provided as an integer 1 to 24 in both x and y.

---
# Slice in time and create a spatial map

.panelset[
.panel[.panel-name[plot]

<img src="images/lecture-10A/raster-1.png" width="40%" style="display: block; margin: auto;" />
]
.panel[.panel-name[learn]

In January 2005, temperatures are

- cool over land in the north 
- cool over the Andes in south america
- warm on the equator, and along the coastline

There are 12*6=72 maps to make!!

]
.panel[.panel-name[R]
.f5[

```r
# Get the map
sth_america <- map_data("world") %>%
  filter(between(long, -115, -53), between(lat, -20.5, 41))

nasa_cb %>% face_temporal() %>%
  filter(month == 1, year == 1995) %>% 
  select(id, time, surftemp) %>%
  unfold(long, lat) %>%
  ggplot() + 
  geom_tile(aes(x=long, y=lat, fill=surftemp)) +
  geom_path(data=sth_america, 
            aes(x=long, y=lat, group=group), 
            colour="white", linewidth=1) +
  scale_fill_viridis_c("", option = "magma") +
  theme_map() +
  theme(legend.position = "bottom") +
  ggtitle("January 1995")
```
]
]
]

---
# Explore spatial trend over time

.panelset[
.panel[.panel-name[plot]
<img src="images/lecture-10A/space_time-1.png" width="75%" style="display: block; margin: auto;" />
]
.panel[.panel-name[learn]

- Exploring spatial trend over time is obtained by .monash-blue2[faceting the maps by time].

- Can you see El Nino in 1997? Can you see the summer vs winter in the different hemispheres?

]
.panel[.panel-name[R]
.f5[

```r
nasa_cb %>% face_temporal() %>%
  select(id, time, month, year, surftemp) %>%
  unfold(long, lat) %>%
  ggplot() + 
  geom_tile(aes(x=long, y=lat, fill=surftemp)) +
  facet_grid(year~month) +
  scale_fill_viridis_c("", option = "magma") +
  theme_map() +
  theme(legend.position = "bottom") 
```
]
]

]
---
# glyphmap: time across space

.flex[
.w-50[
.panelset[
.panel[.panel-name[plot]

<img src="images/lecture-10A/time_space-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[learn]

<br><br>
.monash-blue2[Global scale]: temperature min/max across all spatial locations and time

- Different seasonality at different locations, particularly more north and more south.

]
.panel[.panel-name[R]

.f5[

```r
nasa_cb %>% face_temporal() %>%
  select(id, time, month, year, surftemp) %>%
  unfold(long, lat) %>%
  ggplot() +
    geom_polygon(data=sth_america, 
            aes(x=long, y=lat, group=group), 
            fill="#014221", alpha=0.2, colour="#ffffff") +
    cubble::geom_glyph_box(data=nasa, 
                           aes(x_major = long, 
                               x_minor = day,
                               y_major = lat, 
                               y_minor = surftemp), fill=NA) +
    cubble::geom_glyph(data=nasa, 
                       aes(x_major = long, 
                           x_minor = day,
                           y_major = lat, 
                           y_minor = surftemp)) +
    theme_map() 
```
]
]
]

]
.w-50[
.panelset[
.panel[.panel-name[plot]

]
.panel[.panel-name[learn]

<br><br>
.monash-blue2[Local scale]: min/max for each spatial location

- El Nino year in equatorial region may be visible.
- Notice also odd patterns on the west (Andes mountains) of South America.

]
.panel[.panel-name[R]

.f5[

]
]

---
# glyphmap: time across space

.flex[
.w-50[
.panelset[
.panel[.panel-name[plot]

]
.panel[.panel-name[learn]

<br><br>
.monash-blue2[Global scale]: temperature min/max across all spatial locations and time

- Different seasonality at different locations, particularly more north and more south.

]
.panel[.panel-name[R]

.f5[

]
.w-50[
.panelset[
.panel[.panel-name[plot]

<img src="images/lecture-10A/time_space3-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[learn]

<br><br>
.monash-blue2[Polar coordinates]

- Seasonal pattern may be more visible.

]
.panel[.panel-name[R]

.f5[

```r
nasa_cb %>% face_temporal() %>%
  select(id, time, month, year, surftemp) %>%
  unfold(long, lat) %>%
  ggplot() +
    geom_polygon(data=sth_america, 
            aes(x=long, y=lat, group=group), 
            fill="#014221", alpha=0.2, colour="#ffffff") +
    cubble::geom_glyph_box(data=nasa, 
                           aes(x_major = long, 
                               x_minor = day,
                               y_major = lat, 
                               y_minor = surftemp), 
                           fill=NA) +
    cubble::geom_glyph(data=nasa, 
                       aes(x_major = long, 
                           x_minor = day,
                           y_major = lat, 
                           y_minor = surftemp), 
                       polar=TRUE) +
    theme_map() 
```
]
]
]

]
]
---
# .orange[Case study] .bg-orange.circle[1] Temperature change in Americas

## Exploring El Nino

Slice space, and show the time series, and the pattern is very clear: The seasonal water temperature decrease doesn't happen in 1997, and water in this area stays unseasonably warm.

---

<span><i class="fas  fa-wrench faa-wrench animated-hover faa-slow " style=" color:#D93F00;"></i></span> Your turn using tsibbletalk

.s500.f5[

```r
library(tsibble)
library(tsibbletalk)
library(lubridate)
nasa_shared <- nasa %>% 
  mutate(date = ymd(date)) %>%
  select(long, lat, date, surftemp, id) %>%
  as_tsibble(index=date, key=id) %>%
  as_shared_tsibble()
p1 <- nasa_shared %>%
  ggplot(aes(x = long, y = lat)) +
  geom_point(aes(group = id)) 
p2 <- nasa_shared %>%
  ggplot(aes(x = date, y = surftemp)) +
  geom_line(aes(group = id), alpha = 0.5) 
library(plotly)
subplot(
    ggplotly(p1, tooltip = "Region", width = 100),
    ggplotly(p2, tooltip = "Region", width = 900),
    nrows = 1, widths=c(0.4, 0.6)) %>%
  highlight(dynamic = TRUE)
```
]

---
background-image: url(images/week10A/space-time.jpg)
background-size: 60%
background-position: 95% 35%

.w-35[
# Thinking about spatiotemporal data

Space is a continuous variable, and in theory it fills out a square (or polygon).

Often, though it is .monash-blue2[measured irregularly]. Sensor stations are sporadically placed.

This affects making a density display of the measured variable. Strategy is to .monash-blue2[plot it at the resolution given], before trying to make a regular grid.

]

---
background-image: url(images/week10A/usa-lin-legend.jpg)
background-size: 20%
background-position: 95% 80%

# Glyphmaps of irregular space data

Linear model fit to temperature recorded at historical weather stations across the USA ([USHCN](https://www.ncei.noaa.gov/products/land-based-station/us-historical-climatology-network))

---
background-image: url(images/week10A/usa-lin-collapse-legend.jpg)
background-size: 20%
background-position: 95% 80%

# Regularising

Measurements from nearby stations have been merged. Note, some [areas of the USA have been cooling](https://www.epa.gov/climate-indicators/climate-change-indicators-us-and-global-temperature). This is interesting!

---
background-image: url(images/week10A/usa-season-legend.jpg)
background-size: 20%
background-position: 95% 80%

# Seasonality

De-construct time into a seasonal component, and representing this on the map is reasonable also.

---

# Resources and Acknowledgement

- [cubble](https://huizezhang-sherry.github.io/cubble): A Vector Spatio-Temporal Data Structure for Data Analysis
- [sf](https://r-spatial.github.io/sf/): Simple Features for R
- [Healy (2018) Data Visualization](https://socviz.co/maps.html#maps)
- [Perpinan Lamigueiro (2018) Displaying time series, spatial and space-time data with R](https://oscarperpinan.github.io/bookvis/)
- Wikle, Zammit-Mangion, Cressie (2018) [Spatio-Temporal Statistics with R](https://spacetimewithr.org)
- [Moraga, Paula. (2019). Geospatial Health Data](https://www.paulamoraga.com/book-geospatial/index.html)
- [Visualising spatial data using R](https://rspatialdata.github.io)

---

background-size: cover
class: title-slide
background-image: url("images/bg-12.png")

<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.

.bottom_abs.width100[

Lecturer: *Di Cook*

<i class="fas fa-envelope"></i>  ETC5521.Clayton-x@monash.edu

<i class="fas fa-calendar-alt"></i> Week 10 - Session 1

<br>

]