Data and visualization 💹

---

layout: true
  
<div class="my-footer">
<span>
<a href="https://DataScience4Psych.github.io/DataScience4Psych/" target="_blank">Data Science for Psychologists</a>
</span>
</div>

---

#  Exploring Our Data: What is in a dataset?

---

.pull-left[ 
> "We will be exploring numbers. We need to handle them easily and look at them effectively. Techniques for handling and looking — whether graphical, arithmetic, or intermediate — will be important."

> John Tukey
]

---

## Dataset terminology

- Each row is an **observation**
- Each column is a **variable**

```r
starwars
```

```
## # A tibble: 87 × 14
##   name    height  mass hair_color skin_color eye_color birth_year
##   <chr>    <int> <dbl> <chr>      <chr>      <chr>          <dbl>
## 1 Luke S…    172    77 blond      fair       blue            19  
## 2 C-3PO      167    75 <NA>       gold       yellow         112  
## 3 R2-D2       96    32 <NA>       white, bl… red             33  
## 4 Darth …    202   136 none       white      yellow          41.9
## 5 Leia O…    150    49 brown      light      brown           19  
## 6 Owen L…    178   120 brown, gr… light      blue            52  
## # ℹ 81 more rows
## # ℹ 7 more variables: sex <chr>, gender <chr>, homeworld <chr>,
## #   species <chr>, films <list>, vehicles <list>,
## #   starships <list>
```

]
]
---

## Luke Skywalker

![luke-skywalker](img/luke-skywalker.png)

---

## What's in the Star Wars data?

Take a `glimpse` at the data:
.medi[

```r
glimpse(starwars)
```

```
## Rows: 87
## Columns: 14
## $ name       <chr> "Luke Skywalker", "C-3PO", "R2-D2", "Darth V…
## $ height     <int> 172, 167, 96, 202, 150, 178, 165, 97, 183, 1…
## $ mass       <dbl> 77.0, 75.0, 32.0, 136.0, 49.0, 120.0, 75.0, …
## $ hair_color <chr> "blond", NA, NA, "none", "brown", "brown, gr…
## $ skin_color <chr> "fair", "gold", "white, blue", "white", "lig…
## $ eye_color  <chr> "blue", "yellow", "red", "yellow", "brown", …
## $ birth_year <dbl> 19.0, 112.0, 33.0, 41.9, 19.0, 52.0, 47.0, N…
## $ sex        <chr> "male", "none", "none", "male", "female", "m…
## $ gender     <chr> "masculine", "masculine", "masculine", "masc…
## $ homeworld  <chr> "Tatooine", "Tatooine", "Naboo", "Tatooine",…
## $ species    <chr> "Human", "Droid", "Droid", "Human", "Human",…
## $ films      <list> <"The Empire Strikes Back", "Revenge of the…
## $ vehicles   <list> <"Snowspeeder", "Imperial Speeder Bike">, <…
## $ starships  <list> <"X-wing", "Imperial shuttle">, <>, <>, "TI…
```
]
---

.question[
How many rows and columns does this dataset have?
What does each row represent?
What does each column represent?
]

```r
?starwars
```

---

```r
nrow(starwars) # number of rows
```

```
## [1] 87
```

```r
ncol(starwars) # number of columns
```

```
## [1] 14
```

```r
dim(starwars)  # dimensions (row column)
```

```
## [1] 87 14
```
]

---

## Mass vs. height

.question[ 
How would you describe the relationship between mass and height of Starwars characters?
What other variables would help us understand data points that don't follow the overall trend?
Who is the not so tall but really chubby character?
]

---

## Jabba!

---

## Mass vs. height

```r
ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  geom_point() +
  labs(title = "Mass vs. height of Starwars characters",
       x = "Height (cm)", y = "Weight (kg)")
```

```
## Warning: Removed 28 rows containing missing values
## (`geom_point()`).
```

---

.question[ 
- What are the functions doing the plotting?
- What is the dataset being plotted?
- Which variables map to which features (aesthetics) of the plot?
- What does the warning mean?<sup>+</sup>
]

```r
ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  geom_point() +
  labs(title = "Mass vs. height of Starwars characters",
       x = "Height (cm)", y = "Weight (kg)")
```

```
## Warning: Removed 28 rows containing missing values
## (`geom_point()`).
```

---

## Hello ggplot2!

.pull-left-narrow[
<img src="img/ggplot2-part-of-tidyverse.png" width="80%" style="display: block; margin: auto;" />
] 
.pull-right[
- **ggplot2** is tidyverse's data visualization package 
- `gg` in "ggplot2" stands for Grammar of Graphics 
- Inspired by the book **Grammar of Graphics** by Leland Wilkinson
- `ggplot()` is the main function in ggplot2
- Plots are constructed in layers
- Structure of the code for plots can be summarized as
]
--

```r
ggplot(data = [dataset], 
       mapping = aes(x = [x-variable], y = [y-variable])) +
   geom_xxx() +
   other options
```

---

## ggplot2 `$\in$` tidyverse a.k.a. Grammar of Graphics

.pull-left-narrow[
- **ggplot2** is tidyverse's data visualization package 
- `gg` in "ggplot2" stands for Grammar of Graphics 
- Inspired by the book **Grammar of Graphics** by Leland Wilkinson
- Grammar of graphics is a tool to concisely describe the components of a graphic
- The ggplot2 package comes with the tidyverse

```r
library(tidyverse)
```

- For help with ggplot2, see [ggplot2.tidyverse.org](http://ggplot2.tidyverse.org/)

]
.pull-right-wide[
<img src="img/grammar-of-graphics.png" width="90%" style="display: block; margin: auto;" />
]

.footnote[ Source: [BloggoType](http://bloggotype.blogspot.com/2016/08/holiday-notes2-grammar-of-graphics.html)]

---
class: middle

# Wrapping Up...

---

# Why do we visualize?

---

## Anscombe's quartet

.midi.pull-left[

```
##    set  x     y
## 1    I 10  8.04
## 2    I  8  6.95
## 3    I 13  7.58
## 4    I  9  8.81
## 5    I 11  8.33
## 6    I 14  9.96
## 7    I  6  7.24
## 8    I  4  4.26
## 9    I 12 10.84
## 10   I  7  4.82
## 11   I  5  5.68
## 12  II 10  9.14
## 13  II  8  8.14
## 14  II 13  8.74
## 15  II  9  8.77
## 16  II 11  9.26
## 17  II 14  8.10
## 18  II  6  6.13
## 19  II  4  3.10
## 20  II 12  9.13
## 21  II  7  7.26
## 22  II  5  4.74
```
] 
.midi.pull-right[

```
##    set  x     y
## 23 III 10  7.46
## 24 III  8  6.77
## 25 III 13 12.74
## 26 III  9  7.11
## 27 III 11  7.81
## 28 III 14  8.84
## 29 III  6  6.08
## 30 III  4  5.39
## 31 III 12  8.15
## 32 III  7  6.42
## 33 III  5  5.73
## 34  IV  8  6.58
## 35  IV  8  5.76
## 36  IV  8  7.71
## 37  IV  8  8.84
## 38  IV  8  8.47
## 39  IV  8  7.04
## 40  IV  8  5.25
## 41  IV 19 12.50
## 42  IV  8  5.56
## 43  IV  8  7.91
## 44  IV  8  6.89
```
]

---

## Summarizing Anscombe's quartet
<br>
.medi.pull-left-narrow[

```r
quartet %>%
  group_by(set) %>%
  summarize(
    mean_x = mean(x), 
    mean_y = mean(y),
    sd_x = sd(x),
    sd_y = sd(y),
    r = cor(x, y)
  )
```
]
.pull-right-wide[

```
## # A tibble: 4 × 6
##   set   mean_x mean_y  sd_x  sd_y     r
##   <fct>  <dbl>  <dbl> <dbl> <dbl> <dbl>
## 1 I          9   7.50  3.32  2.03 0.816
## 2 II         9   7.50  3.32  2.03 0.816
## 3 III        9   7.5   3.32  2.03 0.816
## 4 IV         9   7.50  3.32  2.03 0.817
```
]
---

## Visualizing Anscombe's quartet
<br>
.middle[
<img src="d03_dataviz_files/figure-html/quartet-plot-1.png" width="80%" style="display: block; margin: auto;" />
]
---
class: middle

# Wrapping Up...