STA 326 2.0 Programming and Data Analysis with R

# STA 326 2.0 Programming and Data Analysis with R
## The Grammar of Graphics
### Dr Thiyanga Talagala
### Online distance learning/teaching materials during the COVID-19 outbreak.

---

![description of the image](SmallChange.gif)

---

# Grammar of Graphics

]

<img src="Leland.jpg" alt="knitrhex" width="350"/>
]
---
# Packages

```r
library(tidyverse) # To obtain ggplot2
library(magrittr)
```

---

# Dataset

```r
library(gapminder)
glimpse(gapminder)
```

```
Rows: 1,704
Columns: 6
$ country   <fct> Afghanistan, Afghanistan, Afghanistan, Afghanistan, Afghani…
$ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia,…
$ year      <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997,…
$ lifeExp   <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854, 40.…
$ pop       <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 1…
$ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.1134,…
```

---

# Plotting with R

## Base R

- using `plot()` function

## Using ggplot2: grammar of graphics

1.  ggplot2 package: `qplot()` function

- **q**plot: **quick** plot
    
    - very similar to how you graph with `plot()` function

2. ggplot2 package: `ggplot()` function

- fully utilize the power of grammar

---
# Grammar

## English

- Nouns

- Article

- Adjective

- Verb

- Adverb

- Proposition

]

## Graphics

]

---

# Grammar

## English

The little monkey hangs confidently by a branch.

- Article: The

- Adjective: little

- Noun: monkey

- Verb: hangs

- Adverb: Confidently

- Proposition: by

- Noun: a branch

]

## Graphics

```r
ggplot(iris)+
  aes(x = Sepal.Length,
      y = Sepal.Width)+
  geom_point()
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-3-1.png)

]

---
## Elements of ggplot2 object

- Data

- Aesthetics: `x`, `y`, `col`

- Geometrics: `geom_point`, `geom_boxplot`

---

# Elements of ggplot2 object

- Data: `data`

- Aesthetics: `aes`

- Geometrics: `geom_*`
]

---
background-image: url('ggplot2_paint_thiyanga.PNG')
background-position: center
background-size: contain

---

# Making your first plot with ggplot

---

# Data: data to be plotted
.pull-left[
<img src="ggplotaes/data.PNG" alt="knitrhex" height="500"/>
]

```
'data.frame':	150 obs. of  5 variables:
 $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
 $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
 $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
 $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
 $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
```

]
---
## Data

]

---

## Aesthetics: mapping variables

- y

- colour

- shape

]
---
## Data + Aesthetics

]

---
# Geometrics

- geom_point

- geom_boxplot
]
---

## Data + Aesthetics + Geometrics

]

---

## Data + Aesthetics + Geometrics

```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width))+
  geom_point()
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-8-1.png)
]

]

---

## Data + Aesthetics + Geometrics

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width))+
*    geom_point(col = "forestgreen")
```

]

---

## Data + Aesthetics + Geometrics

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width))+
    geom_point(col = "forestgreen",
*    shape = 8)
```

]

---
 
## Data + Aesthetics + Geometrics

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
*    col = Species))+
    geom_point()
```

]

.right-plot[
![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-11-1.png)
]
---
 
## Data + Aesthetics + Geometrics

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col= Species))+
    geom_point(
*    shape = 3
    )
```

]

---
## Data + Aesthetics + Geometrics

```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species))+
    geom_point()
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-13-1.png)

]

]
---
# Facets: small multiples

---

## Data + Aesthetics + Geometrics + Facets

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species))+
    geom_point()+
*    facet_grid(~Species)
```

]

## Data + Aesthetics + Geometrics + Facets

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species))+
    geom_point()+
*    facet_grid(Species ~.)
```

]

# Statistics

---

## Data + Aesthetics + Geometrics + Facets + Statistics

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species))+
    geom_point()+
    facet_wrap(~Species)+
*    stat_smooth(method = "lm", se = F, col ="red")
    
```

]

---

## Data + Aesthetics + Geometrics + Facets + Statistics

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species))+
    geom_point()+
    facet_wrap( ~ Species)+
*    stat_smooth(method = "lm", se = T, col = "red")
    
```

]

.right-plot[
![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-17-1.png)
]
---
# Coordinate

---

## Data + Aesthetics + Geometrics + Facets + Statistics + Coordinate

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species)) +
    geom_point() +
    facet_wrap( ~ Species) +
    stat_smooth(method = "lm", se = T, col = "red") + 
*    coord_equal()
    
```

]

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-18-1.png)
]
---
# Theme

---

## Data + Aesthetics + Geometrics + Facets + Statistics +  Coordinate+ Theme

]

.right-plot[
<img src="l12_grammar_of_graphics_files/figure-html/unnamed-chunk-19-1.png" width="100%" />
]

---

# Scale

---

## Data + Aesthetics + Geometrics + Facets + Statistics + Coordinate + Theme + Scale

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species)) +
    geom_point() +
    facet_wrap( ~ Species) +
    stat_smooth(method = "lm", se = T, col = "red") + 
    coord_equal() + 
    theme(legend.position = "bottom") +
*    scale_color_manual(values = c("#1b9e77", "#d95f02", "#7570b3"))
    
```

]

.right-plot[
<img src="l12_grammar_of_graphics_files/figure-html/unnamed-chunk-20-1.png" width="100%" />
]

---

## titles and axes labels

.left-code[
```r
ggplot(iris,
aes(x = Sepal.Length, 
    y = Sepal.Width,
    col = Species)) +
    geom_point() +
    facet_wrap( ~ Species) +
    stat_smooth(method = "lm", se = T, col = "red") + 
    coord_equal() + 
    theme(legend.position = "bottom") +
    scale_color_manual(values = c("#1b9e77", "#d95f02", "#7570b3"))+
*labs(title="Scatter plot of Sepal Length  vs Sepal Width",
        x ="Sepal Length (cm)", y = "Sepal Width (cm)")
    
```

]

.right-plot[
<img src="l12_grammar_of_graphics_files/figure-html/unnamed-chunk-21-1.png" width="100%" />
]

---
class: duke-green,  middle

# Your turn

Dataset: gapminder

Visualize the relationship between life expectancy, GDP per capita and continent in 2007.

---

.left-code[
```r
gapminder2007 <- gapminder %>%
  filter(year == 2007)
  
ggplot(gapminder2007,
aes(x = lifeExp, y = gdpPercap, col=continent)) +
    geom_point() + theme(legend.position = "bottom") + 
labs(title = "Relationship between life expectancy and GPD per capita by continent - 2007",
        x ="life expectancy at birth, in years",
        y = "GDP per capita (US$, inflation-adjusted)")
    
```

]

---

# Add a vertical line

.left-code[
```r
gapminder2007 <- gapminder %>%
  filter(year == 2007)
  
ggplot(gapminder2007,
aes(x = lifeExp, y = gdpPercap, col=continent)) +
    geom_point() + 
*    geom_vline(xintercept = 70)

```

]

---

# Add a horizontal line

.left-code[
```r
gapminder2007 <- gapminder %>%
  filter(year == 2007)
  
ggplot(gapminder2007,
aes(x = lifeExp, y = gdpPercap, col=continent)) +
    geom_point() + 
*    geom_hline(yintercept = 20000)

```

]

---

# Add a diagonal line

.left-code[
```r
gapminder2007 <- gapminder %>%
  filter(year == 2007)
  
ggplot(gapminder2007,
aes(x = lifeExp, y = gdpPercap, col=continent)) +
    geom_point() + 
*    geom_abline(intercept = 20, slope=200)

```

]

---
# All Geoms

```
 [1] "geom_abline"         "geom_area"           "geom_bar"           
 [4] "geom_bin2d"          "geom_blank"          "geom_boxplot"       
 [7] "geom_col"            "geom_contour"        "geom_contour_filled"
[10] "geom_count"          "geom_crossbar"       "geom_curve"         
[13] "geom_density"        "geom_density_2d"     "geom_density2d"     
[16] "geom_dotplot"        "geom_errorbar"       "geom_errorbarh"     
[19] "geom_freqpoly"       "geom_hex"            "geom_histogram"     
[22] "geom_hline"          "geom_jitter"         "geom_label"         
[25] "geom_line"           "geom_linerange"      "geom_map"           
[28] "geom_path"           "geom_point"          "geom_pointrange"    
[31] "geom_polygon"        "geom_qq"             "geom_qq_line"       
[34] "geom_quantile"       "geom_raster"         "geom_rect"          
[37] "geom_ribbon"         "geom_rug"            "geom_segment"       
[40] "geom_sf"             "geom_sf_label"       "geom_sf_text"       
[43] "geom_smooth"         "geom_spoke"          "geom_step"          
[46] "geom_text"           "geom_tile"           "geom_violin"        
[49] "geom_vline"         
```
---

# geom_boxplot

]

---

# geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent, color=continent)) +
geom_boxplot()
    
```

]

---

# geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent, fill=continent)) +
geom_boxplot()
    
```

]

---

# geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent)) +
geom_boxplot(fill="forestgreen")
    
```

]

---

# geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent)) +
geom_boxplot(fill="forestgreen", alpha=0.5)
    
```

]

# geom_point

]

---

#  geom_jitter

]

---

#  geom_jitter + geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent)) +
  geom_jitter() +
  geom_boxplot()
    
```

]

---

#  geom_jitter + geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent)) +
  geom_jitter() +
  geom_boxplot(alpha=0.5)
    
```

]

---

# geom_jitter + geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent)) +
  geom_boxplot() + 
  geom_jitter() 
    
```

]

#  geom_jitter + geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent, fill=continent)) +
  geom_boxplot() + 
  geom_jitter() 
    
```

]

---

#  geom_jitter + geom_boxplot

.left-code[
```r
ggplot(gapminder2007, aes(x=lifeExp, y=continent, fill=continent)) +
  geom_boxplot() + 
  geom_jitter(aes(col=continent)) 
    
```

]

---

#  geom_jitter + geom_boxplot (outlier.shape = NA)

.left-code[
```r
ggplot(gapminder2007, aes(x = lifeExp, y = continent, fill = continent)) +
*  geom_boxplot(outlier.shape = NA) + 
  geom_jitter(aes(col = continent)) 
    
```

]

#  geom_jitter + geom_boxplot

.left-code[
```r
*ggplot(gapminder2007, aes(x=lifeExp, y=continent, fill=continent, col=continent))+
  geom_boxplot(outlier.shape = NA) + 
  geom_jitter(aes(col=continent)) 
    
```

]

---

#  geom_jitter + geom_boxplot

.left-code[
```r
ggplot(gapminder2007, 
aes(x=lifeExp, y=continent, fill=continent, col=continent))+
*  geom_boxplot(outlier.shape = NA, alpha=0.2) + 
  geom_jitter(aes(col=continent)) 
    
```

]

#  geom_jitter + geom_boxplot + coord_flip

.left-code[
```r
ggplot(gapminder2007, 
aes(x=lifeExp, y=continent, fill=continent, col=continent))+
  geom_boxplot(outlier.shape = NA, alpha=0.2) + 
  geom_jitter(aes(col=continent)) +
*  coord_flip()
    
```

]

---

#  geom_boxplot

]

#  geom_boxplot + facet_wrap

.left-code[
```r
ggplot(gapminder2007, 
aes(y = lifeExp))+
  geom_boxplot() + facet_wrap(~continent, ncol = 5)
    
```

]

---

#  geom_density

.left-code[
```r
ggplot(gapminder2007, 
aes(x=lifeExp))+
*  geom_density() + 
  facet_wrap(~continent, ncol=5)
    
```

]

---
class: duke-green,  middle

# Your turn

Modify the code below to obtain the following plot.

]

.right-plot[
![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-46-1.png)
]
---
#  geom_histogram

]

.right-plot[
![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-47-1.png)
]
---
# geom_bar

]

---
class: duke-green,  middle

# Your turn

Modify the code below to obtain the following plot.

]

.right-plot[
![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-49-1.png)
]
---
## geom_bar (stat="identity")

Method 1

```r
cut.percent <- data.frame(cut=c("Fair", "Good", "Very Good", "Premium", 
                                "Ideal"), percent=c(3, 9, 22.4, 25.6, 40))
cut.percent
```

```
        cut percent
1      Fair     3.0
2      Good     9.0
3 Very Good    22.4
4   Premium    25.6
5     Ideal    40.0
```

```r
ggplot(data=cut.percent, aes(x=cut, y=percent)) +
  geom_bar(stat="identity")
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-51-1.png)

---

## geom_col

Method 2

```r
cut.percent <- data.frame(cut=c("Fair", "Good", "Very Good", "Premium", 
                                "Ideal"), percent=c(3, 9, 22.4, 25.6, 40))
cut.percent
```

```
        cut percent
1      Fair     3.0
2      Good     9.0
3 Very Good    22.4
4   Premium    25.6
5     Ideal    40.0
```

```r
ggplot(data=cut.percent, aes(x=cut, y=percent)) +
  geom_col()
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-53-1.png)

---
## Change the order of levels

Method 2

```r
cut.percent <- data.frame(cut=c("Fair", "Good", "Very Good", "Premium", 
                                "Ideal"), percent=c(3, 9, 22.4, 25.6, 40))
cut.percent$cut <- factor(cut.percent$cut, 
                  levels = c("Fair", "Good", "Very Good", 
                             "Premium", "Ideal"))    
```

```r
ggplot(data=cut.percent, aes(x=cut, y=percent)) +
  geom_col()
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-55-1.png)

---
# geom_point

.left-code[
```r
gapminder %>%
filter(country == "India") %>%
ggplot(aes(x = year, y = gdpPercap)) +
geom_point()
    
```

]

---
# geom_line

.left-code[
```r
gapminder %>%
filter(country == "India") %>%
ggplot(aes(x = year, y = gdpPercap)) +
geom_line()
    
```

]

---

# geom_line + geom_point

.left-code[
```r
gapminder %>%
filter(country == "India") %>%
ggplot(aes(x = year, y = gdpPercap)) +
geom_line() + 
geom_point()
    
```

]

# Your turn

Modify the code below to obtain the following plot.

```r 
gapminder %>% filter(country == "India") %>%
ggplot(aes(x = year, y = gdpPercap)) + geom_line() + geom_point()
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-59-1.png)

---

# Data Wrangling + Data Visualization

```r
avglifeExp <- gapminder %>%
  group_by(continent, year) %>%
  summarise(meanlifeExp=mean(lifeExp))
avglifeExp
```

```
# A tibble: 60 x 3
# Groups:   continent [5]
   continent  year meanlifeExp
   <fct>     <int>       <dbl>
 1 Africa     1952        39.1
 2 Africa     1957        41.3
 3 Africa     1962        43.3
 4 Africa     1967        45.3
 5 Africa     1972        47.5
 6 Africa     1977        49.6
 7 Africa     1982        51.6
 8 Africa     1987        53.3
 9 Africa     1992        53.6
10 Africa     1997        53.6
# … with 50 more rows
```

---
class: duke-green,  middle

# Your turn

Write an R code to reproduce the plot below.

Hint: use `avglifeExp`

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-61-1.png)
---
class: duke-green,  middle

# Your turn

Write an R code to reproduce the plot below.

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-62-1.png)

---
class: duke-green,  middle

# Your turn

Write an R code to reproduce the plot below.

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-63-1.png)

Hint: Next slide
---

```r
gapminder %>%
  ggplot(aes(y=log(lifeExp), x=log(gdpPercap), color=continent)) + 
  geom_point() + 
  labs(y = "log(Life Expectancy)",
       x = "log(GDP per capita)")
```

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-64-1.png)
---
class: duke-green,  middle

# Your turn

Write an R code to reproduce the plot below.

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-65-1.png)

---
# geom_point

]

---
# geom_smooth

.left-code[
```r
ggplot(gapminder, aes(x=year, y=gdpPercap, colour=continent))+
*geom_smooth()
    
```

]

.right-plot[
![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-67-1.png)
]
---
class: duke-green,  middle

# Your turn

Write an R code to reproduce the plot below.

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-68-1.png)

---
class: duke-green,  middle

# Your turn

Write an R code to reproduce the plot below.

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-69-1.png)

---
class: duke-green,  middle

# Your turn

Write an R code to visualize the shape of standard normal distribution.

Hint: `dnorm`

![](l12_grammar_of_graphics_files/figure-html/unnamed-chunk-70-1.png)

---
# Recap

## aes

- x
- y
- colour
- size

## geom

- geom_point
- geom_jitter
- geom_line
- geom_bar
- geom_col
- geom_histogram
- geom_smooth
- geom_density
- geom_abline
- geom_vline
- geom_hline
]

## geom arguments

- colour
- fill
- size
- alpha
- shape

## other elements

- labs
- coord_equal
- coord_flip
- scale_colour_manual
- labs
- facet_wrap
- theme

]
---
class: center, middle

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