R for Economics and Social Sciences Research

class: center, middle

# R for Economics and Social Science Research

#### Norberto E. Milla, Jr.

---

class: center, middle

# Day 2: Data Visualization with R

---

#  Introduction to Visualization
.pull-left[
- *"A picture is worth a thousand words”.*

- a good visualization makes it easier to identify patterns and trends

- provides a quick and effective way to communicate information

- displays complex relationships among data

- highlights interesting and compelling "stories" from the data
]

.pull-right[

]

---
# The ggplot2 package

- **ggplot2** is a system for declaratively creating graphics which is inspired by the **Grammar of Graphics** book of *Leland Wilkinson (2005)*

- the key idea behind **ggplot2** is that it allows to easily building up a complex plot layer by layer

- each layer adds an extra level of information to the plot

- sophisticated plots are build tailored to the problem at hand

---
# The ggplot2 package

- using the <tt>ggplot()</tt> function we build a graph in layers

- basic elements:

- **data**: the information you want to visualise
 
 - **mapping**: description of how the variables are mapped to aesthetic attributes
 - *layer*: geometries and statistical summaries
 
 - *scale*: color, shape, size, legend
 
 - *coordinate system*: axes and gridlines 
 
 - *facet*: specifies how to break up and display subsets of data 
 
 - *theme*: controls the finer points of display, like the font size and background color
 
---
# Basic plots: <tt>scatter plot</tt>

``` r
library(carData)
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, y = salary))
```

<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-2-1.png" width="55%" style="display: block; margin: auto;" />
---

# Basic plots: <tt>scatter plot</tt>

``` r
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, y = salary)) +
  geom_point()
```

---
# Basic plots: <tt>scatter plot</tt>
.pull-left[

``` r
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, 
                     y = salary)) +
  geom_point(color = "blue",
             size = 3,
             alpha = 1.5) 
```

]

.pull-right[
<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-5-1.png" width="95%" style="display: block; margin: auto;" />

]
---

# Basic plots: <tt>scatter plot</tt>
.pull-left[

``` r
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, 
                     y = salary)) +
  geom_point(color = "blue",
             size = 3,
             alpha = 1.5) +
  labs(x = "Years of Service",
       y = "Salary") 
```

]

.pull-right[
<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-7-1.png" width="95%" style="display: block; margin: auto;" />

]

---
# Basic plots: <tt>scatter plot</tt>
.pull-left[

``` r
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, 
                     y = salary)) +
  geom_point(color = "blue",
             size = 3,
             alpha = 1.5) +
  labs(x = "Years of Service",
       y = "Salary") +
  geom_smooth(method="lm",
              col = "red")
```

]

.pull-right[
<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-9-1.png" width="95%" style="display: block; margin: auto;" />

]
---
# Basic plots: <tt>scatter plot</tt>
.pull-left[

]

.pull-right[
<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-11-1.png" width="95%" style="display: block; margin: auto;" />

]

---
# Basic plots: <tt>scatter plot</tt>
.pull-left[

``` r
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, 
                     y = salary,
                     color = sex)) +
  geom_point(size = 3,
             alpha = 1.5) +
  labs(x = "Years of Service",
       y = "Salary") +
  geom_smooth(method="lm") +
  theme_classic()
```

]

.pull-right[
<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-13-1.png" width="95%" style="display: block; margin: auto;" />
]

---

# Basic plots: <tt>scatter plot</tt>
.pull-left[

``` r
ggplot(data = Salaries,
       mapping = aes(x = yrs.service, 
                     y = salary)) +
  geom_point(color = "lightblue",
             size = 3,
             alpha = 1.5) +
  labs(x = "Years of Service",
       y = "Salary") +
  geom_smooth(method="lm",
              col = "red") +
  facet_wrap(~sex)+
  theme_classic()
```

]

.pull-right[
<img src="Day-2--Slide-presentation_files/figure-html/unnamed-chunk-15-1.png" width="95%" style="display: block; margin: auto;" />

]
---

# Basic plots: <tt>bar plot</tt>
.pull-left[

``` r
Salaries %>% 
  select(rank) %>% 
  ggplot(aes(x=rank)) +
  geom_bar(fill="lightblue")+
  labs(x="Rank", 
       y = "No. of faculty") +
  theme_classic()
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-17-1.png)

]
---

# Basic plots: <tt>bar plot</tt>
.pull-left[

``` r
Salaries %>% 
  select(rank) %>% 
  ggplot(aes(x=rank)) +
  geom_bar(fill="lightblue")+
  labs(x="Rank", 
       y = "No. of faculty") +
  coord_flip()+
  theme_classic()
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-19-1.png)

]

---
# Basic plots: <tt>bar plot</tt>
.pull-left[

``` r
Salaries %>% 
  select(rank) %>% 
  count(rank) %>% 
  mutate(p=round(n/sum(n)*100,1)) %>% 
  ggplot(aes(x = reorder(rank,p),
             y = p,
             label = p)) +
  geom_col(fill="lightblue", 
           col = "black") +
  geom_text(aes(label = p), 
            hjust=-0.5,
            size = 3.5) +
  labs(x = " ",
       y = "Percent (%)")+
  coord_flip() +
  theme_classic()
```

]
.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-21-1.png)

]

---

# Basic plots: <tt>bar plot</tt>

.pull-left[

``` r
Salaries %>%
  drop_na(salary) %>% 
  group_by(rank) %>% 
  summarize(n = length(salary),
            Mean = mean(salary),
            SD = sd(salary)) %>% 
  mutate(SE = SD/sqrt(n)) %>% 
  as.data.frame() %>% 
  ggplot(aes(x=rank, y = Mean)) +
  geom_col(fill= "lightblue", 
           col="black", 
           width = 0.5) +
  geom_errorbar(aes(ymin = Mean-SE, 
                    ymax = Mean+SE),
                size = 0.7,
                width = 0.15) +
  theme_classic2()
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-23-1.png)
]

---
# Basic plots: <tt>bar plot</tt>
.pull-left[

``` r
Salaries %>% 
  select(discipline, rank, sex) %>% 
  group_by(sex) %>% 
  count(rank) %>% 
  as.data.frame() %>% 
  ggplot(aes(x=rank, 
             y = n, 
             fill=reorder(sex,-n))) +
  geom_bar(stat = "identity", 
           position = "stack", 
           width = 0.5) +
  coord_flip() +
  geom_text(aes(label = n),
            hjust=1.3,
            size = 3)+
  labs(x = "Rank",
       y = "No. of faculty",
       fill = "Sex") +
  theme_classic()
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-25-1.png)

]

---
# Basic plots: <tt>bar plot</tt>
.pull-left[

``` r
Salaries %>% 
 select(discipline, rank, sex) %>% 
 group_by(sex) %>% 
 count(rank) %>% 
 as.data.frame() %>% 
 ggplot(aes(x=rank, 
 y = n, 
 fill = sex)) +
 geom_bar(stat = "identity",
 position = "dodge",
 col = "black") +
 geom_text(aes(label = n),
 position = position_dodge(0.9),
 vjust = -1,
 size = 3)+
 labs(x = "Rank",
 y = "No. of faculty",
 fill = "Sex") +
 scale_y_continuous(expand = c(0,0), 
 limits = c(0,300)) +
 theme_classic()
```
]
.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-27-1.png)

]
---
# Basic plots: histogram

.pull-left[

``` r
Salaries %>% 
 ggplot(aes(x = salary)) +
 geom_histogram(fill = "lightblue",
 color = "black") +
 scale_y_continuous(expand = c(0,0)) +
 facet_wrap(~sex)
```
]
.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-29-1.png)
]

---

# Basic plots: density plot
.pull-left[

``` r
Salaries %>% 
  ggplot(aes(x = salary)) +
  geom_density(fill = "lightblue") +
  scale_y_continuous(expand = c(0,0)) +
  facet_wrap(~rank)
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-31-1.png)

]
---
# Basic plots: density plot
.pull-left[

``` r
Salaries %>% 
  ggplot(aes(x = salary, 
             fill = rank, 
             color = rank)) +
  scale_y_continuous(expand = c(0,0)) +
  geom_density()
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-33-1.png)

]

---
# Basic plots: box plot

.pull-left[

``` r
Salaries %>% 
  ggplot(aes(x = salary, 
             fill = rank, 
             color = rank)) +
  geom_boxplot() + 
  scale_y_continuous(expand = c(0,0)) +
  theme(axis.text.x=element_blank()) +
  coord_flip()
```
]

.pull-right[
![](Day-2--Slide-presentation_files/figure-html/unnamed-chunk-35-1.png)

]
---
class: center, middle

# LUNCH BREAK

---
# Interactive plots

``` r
g1 <- ggplot(data = Salaries,
 mapping = aes(x = yrs.service, 
 y = salary,
 color = sex)) +
 geom_point(size = 3,
 alpha = 1.5) +
 labs(x = "Years of Service",
 y = "Salary") +
 geom_smooth(method="lm") +
 theme_classic()

ggplotly(g1)
```
---
# Interactive plots

<div class="plotly html-widget html-fill-item" id="htmlwidget-54354f9035dd04a4a940" style="width:504px;height:504px;"></div>
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---

# Interactive plots

``` r
g1 <- ggplot(data = Salaries,
 aes(x = yrs.service, 
 y = salary,
 color = sex,
 Label1 = sex,
 Label2 = rank,
 Label3 = discipline)) +
 geom_point(size = 3,
 alpha = 1.5) +
 labs(x = "Years of Service",
 y = "Salary") +
 geom_smooth(method="lm") +
 theme_classic()

ggplotly(g1, tooltip = c("Label1", "Label2", "Label3"))
```
---
# Interactive plots

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---
# Animated plots

``` r
g <- ggplot(data = gapminder, 
 aes(x = gdpPercap, 
 y = lifeExp, 
 size = pop, 
 fill = continent)) +
 geom_point(aes(frame = year,
 id = country)) +
 scale_size(range = c(2, 12)) +
 scale_x_log10() +
 facet_wrap(~continent)

ggplotly(g)
```

---
# Animated plots

<div class="plotly html-widget html-fill-item" id="htmlwidget-c45be0b51fb66084d0c0" style="width:504px;height:504px;"></div>
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---

# Interactive dashboard: <tt>flexdashboard</tt>

- displays various types of data visualizations in a single page

- **flexdashboard** facilitates easy creation of interactive dashboards for R

- Here is [My First Flexdashboard](https://rpubs.com/bertmilla/1289853)

- [My Second Flexdashboard](https://rpubs.com/bertmilla/1289857)