Introduction Example

class: left, top, title-slide

.title[
# Introduction<br>Example
]
.author[
### Keith VanderLinden<br>Calvin University
]

---

# Data Science in Action

Consider H. Rosling&rsquo;s well-known demonstration of data visualization.

.footnote[See: https://www.ted.com/talks/hans_rosling_the_best_stats_you_ve_ever_seen]

???
This is Hans Rosling's 2006 TED talk. Rosling died in 2017.

They will have watched this for the preparation assignment. Review the answers to the preparation question on Rosling's students (the problem wasn't so much ignorance and preconceptions). Data tests preconceptions.

Here, we do a single, full example that approximates Rosling's visualization.

References:
- Mine's UN votes (https://www.youtube.com/watch?v=OJ1xR0ObhIw)? 
- H. Rosling's videos (https://youtu.be/Z8t4k0Q8e8Y or https://www.youtube.com/watch?v=hVimVzgtD6w 0:00-5:15) - Ken's example https://cs.calvin.edu/courses/data/202/ka37/slides/w02/w2d2-vis.html

---
# Example: Raw Data

.pull-left[

```r
*gapminder
```
.footnote[See: https://www.rdocumentation.org/packages/gapminder]
]
.pull-right[

```
## # A tibble: 1,704 × 6
##    country     continent  year lifeExp      pop gdpPercap
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
##  1 Afghanistan Asia       1952    28.8  8425333      779.
##  2 Afghanistan Asia       1957    30.3  9240934      821.
##  3 Afghanistan Asia       1962    32.0 10267083      853.
##  4 Afghanistan Asia       1967    34.0 11537966      836.
##  5 Afghanistan Asia       1972    36.1 13079460      740.
##  6 Afghanistan Asia       1977    38.4 14880372      786.
##  7 Afghanistan Asia       1982    39.9 12881816      978.
##  8 Afghanistan Asia       1987    40.8 13867957      852.
##  9 Afghanistan Asia       1992    41.7 16317921      649.
## 10 Afghanistan Asia       1997    41.8 22227415      635.
## # … with 1,694 more rows
```
]

???
This is the raw data, taken from the gapminder library. A tibble is a upgraded R data.frame.
- The dataset is rectangular, as most simple datasets are.
- There are 1704 rows/observations; 6 columns/variables; and, thus, 10224 values (1704*6)

---
# Example: Data Summary

.pull-left[

```r
gapminder %>% 
* summarize(AvgLifeExp = mean(lifeExp))
```
]
.pull-right[

```
## # A tibble: 1 × 1
##   AvgLifeExp
##        <dbl>
## 1       59.5
```
]

???
This groups the data by year and computes an average per group.

---
# Example: Data Aggregation

.pull-left[

```r
gapminder %>% 
* group_by(year) %>%
  summarize(AvgLifeExp = mean(lifeExp))
```
]
.pull-right[

```
## # A tibble: 12 × 2
##     year AvgLifeExp
##    <int>      <dbl>
##  1  1952       49.1
##  2  1957       51.5
##  3  1962       53.6
##  4  1967       55.7
##  5  1972       57.6
##  6  1977       59.6
##  7  1982       61.5
##  8  1987       63.2
##  9  1992       64.2
## 10  1997       65.0
## 11  2002       65.7
## 12  2007       67.0
```
]

???
This groups the data by year and computes an average per group.

---
# Example: Data Visualisation

.pull-left[

```r
gapminder %>% 
  group_by(year) %>%                      
  summarize(AvgLifeExp = mean(lifeExp)) %>%
* ggplot() +
* aes(x=year, y=AvgLifeExp) +
* geom_line()
```
]
.pull-right[
<img src="example_files/figure-html/unnamed-chunk-5-1.png" width="100%" />
]

???
This takes the same data, grouped by year, and plots the average over time using a line plot.

---
# Example: Data Visualisation (cf. Rosling)

.pull-left[

```r
library(scales)

gapminder %>% 
  filter(year == 2007) %>%
  ggplot() +
  aes(x = gdpPercap, y = lifeExp) +
  geom_point(alpha = .8) +
  aes(color = continent) +
  aes(size = pop) + 
  scale_x_continuous( 
    breaks = c(400, 4000, 40000),
    trans = "log10") +
  labs(x = "GDP per Capita") +
  labs(y = "Life Expectancy (years)") + 
  labs(color = "Continent") +
  labs(size = "Population") +
  scale_size_area(labels=label_comma()) + 
  theme_bw() +
  annotation_logticks(sides = "b")
```
]
.pull-right[
<img src="example_files/figure-html/unnamed-chunk-6-1.png" width="100%" />
]

???
This graph approximates one time-stop of Rosling's famous animation.

Summarize this only; we'll demo the code detail in the RStudio slides.