Data and visualization 
 📉Dr. Lucy D’Agostino McGowan1 / 61

`Starwars`

Go to RStudio Cloud and launch the Starwars project.

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Exploratory data analysis

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What is EDA?

Exploratory data analysis (EDA) is an approach to analyzing data sets to summarize its main characteristics.
Often, this is visual. That's what we're focusing on today.
But we might also calculate summary statistics and perform data wrangling/manipulation/transformation at (or before) this stage of the analysis. That's what we'll focus on next.

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Data visualization

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Data visualization

"The simple graph has brought more information to the data analyst’s mind than any other device." — John Tukey

Data visualization is the creation and study of the visual representation of data.
There are many tools for visualizing data (R is one of them), and many approaches/systems within R for making data visualizations (ggplot2 is one of them, and that's what we're going to use).

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ggplot2 $\in$ tidyverse

ggplot2 is tidyverse's data visualization package
The gg in "ggplot2" stands for Grammar of Graphics
It is inspired by the book Grammar of Graphics by Leland Wilkinson ^†
A grammar of graphics is a tool that enables us to concisely describe the components of a graphic

^† Source: BloggoType

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Which function creates the plot?

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).

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What is the dataset being plotted?

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).

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Which variables are on the x-axis and y-axis?

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).

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What about that warning?

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).

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What does geom_smooth() do? What else changed between the previous plot and this one?

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

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Hello ggplot2!

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ggplot2 components

data
aesthetic mapping
layer(s)

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ggplot2 premise

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Hello ggplot2!

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Hello ggplot2!

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Hello ggplot2!

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Hello ggplot2!

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Hello ggplot2!

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Hello ggplot2!

ggplot() is the main function in ggplot2 and plots are constructed in layers
The structure of the code for plots can often be summarized as

ggplot + 
  geom_xxx

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Hello ggplot2!

ggplot() is the main function in ggplot2 and plots are constructed in layers
The structure of the code for plots can often be summarized as

ggplot + 
  geom_xxx

or, more precisely

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

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Hello ggplot2!

To use ggplot2 functions, first load tidyverse

library(tidyverse)

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Hello ggplot2!

To use ggplot2 functions, first load tidyverse

library(tidyverse)

For help with the ggplot2, see ggplot2.tidyverse.org

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Visualizing Star Wars

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Dataset terminology

What does each row represent? What does each column represent?

starwars

## # A tibble: 5 x 13
##   name  height  mass hair_color skin_color eye_color birth_year gender
##   <chr>  <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr> 
## 1 Luke…    172    77 blond      fair       blue            19   male  
## 2 C-3PO    167    75 <NA>       gold       yellow         112   <NA>  
## 3 R2-D2     96    32 <NA>       white, bl… red             33   <NA>  
## 4 Dart…    202   136 none       white      yellow          41.9 male  
## 5 Leia…    150    49 brown      light      brown           19   female
## # … with 5 more variables: homeworld <chr>, species <chr>, films <list>,
## #   vehicles <list>, starships <list>

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Dataset terminology

What does each row represent? What does each column represent?

starwars

## # A tibble: 5 x 13
##   name  height  mass hair_color skin_color eye_color birth_year gender
##   <chr>  <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr> 
## 1 Luke…    172    77 blond      fair       blue            19   male  
## 2 C-3PO    167    75 <NA>       gold       yellow         112   <NA>  
## 3 R2-D2     96    32 <NA>       white, bl… red             33   <NA>  
## 4 Dart…    202   136 none       white      yellow          41.9 male  
## 5 Leia…    150    49 brown      light      brown           19   female
## # … with 5 more variables: homeworld <chr>, species <chr>, films <list>,
## #   vehicles <list>, starships <list>

Each row is an observation
Each column is a variable

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Luke Skywalker

luke-skywalker

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What's in the Star Wars data?

Take a glimpse at the data:

glimpse(starwars)

## Observations: 87
## Variables: 13
## $ name       <chr> "Luke Skywalker", "C-3PO", "R2-D2", "Darth Vader", "L…
## $ height     <int> 172, 167, 96, 202, 150, 178, 165, 97, 183, 182, 188, …
## $ mass       <dbl> 77.0, 75.0, 32.0, 136.0, 49.0, 120.0, 75.0, 32.0, 84.…
## $ hair_color <chr> "blond", NA, NA, "none", "brown", "brown, grey", "bro…
## $ skin_color <chr> "fair", "gold", "white, blue", "white", "light", "lig…
## $ eye_color  <chr> "blue", "yellow", "red", "yellow", "brown", "blue", "…
## $ birth_year <dbl> 19.0, 112.0, 33.0, 41.9, 19.0, 52.0, 47.0, NA, 24.0, …
## $ gender     <chr> "male", NA, NA, "male", "female", "male", "female", N…
## $ homeworld  <chr> "Tatooine", "Tatooine", "Naboo", "Tatooine", "Alderaa…
## $ species    <chr> "Human", "Droid", "Droid", "Human", "Human", "Human",…
## $ films      <list> [<"Revenge of the Sith", "Return of the Jedi", "The …
## $ vehicles   <list> [<"Snowspeeder", "Imperial Speeder Bike">, <>, <>, <…
## $ starships  <list> [<"X-wing", "Imperial shuttle">, <>, <>, "TIE Advanc…

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What's in the Star Wars data?

How many rows and columns does this dataset have? What does each row represent? What does each column represent?

Run the following in the Console to view the help

?starwars

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Mass vs. height

ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  geom_point()

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

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What's that warning?

Not all characters have height and mass information (hence 28 of them not plotted)

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

Going forward I'll suppress the warning to save room on slides, but it's important to note it

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Mass vs. height

How would you describe this relationship? 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?

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)")

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Jabba!

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Additional variables

We can map additional variables to various features of the plot:

aesthetics
- color
- size
- shape
- alpha (transparency)
faceting: small multiples displaying different subsets

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Aesthetics

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Aesthetics options

Visual characteristics of plotting characters that can be mapped to a specific variable in the data are

color
size
shape
alpha (transparency)

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Mass vs. height + gender

ggplot(data = starwars, mapping = aes(x = height, y = mass, color = gender)) +
  geom_point()

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Mass vs. height + gender

Let's map the size to birth_year:

ggplot(data = starwars,
       mapping = aes(x = height, y = mass, color = gender, 
                     size = birth_year
       )) +
  geom_point()

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Mass vs. height + gender

Let's now increase the size of all points not based on the values of a variable in the data:

ggplot(data = starwars, mapping = aes(x = height, y = mass, color = gender)) +
  geom_point(size = 2)

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Aesthetics summary

Continuous variable are measured on a continuous scale
Discrete variables are measured (or often counted) on a discrete scale

aesthetics	discrete	continuous
color	rainbow of colors	gradient
size	discrete steps	linear mapping between radius and value
shape	different shape for each	shouldn't (and doesn't) work

Use aesthetics for mapping features of a plot to a variable, define the features in the geom for customization not mapped to a variable

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Faceting

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Faceting options

Smaller plots that display different subsets of the data
Useful for exploring conditional relationships and large data

ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  facet_grid(. ~ gender) +
  geom_point() +
  labs(title = "Mass vs. height of Starwars characters",
       subtitle = "Faceted by gender",
       x = "Height (cm)", y = "Weight (kg)")

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Dive further...

In the next few slides describe what each plot displays. Think about how the code relates to the output.

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Dive further...

In the next few slides describe what each plot displays. Think about how the code relates to the output.

The plots in the next few slides do not have proper titles, axis labels, etc. because we want you to figure out what's happening in the plots. But you should always label your plots!

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ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  geom_point() +
  facet_grid(gender ~ .)

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ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  geom_point() +
  facet_grid(. ~ gender)

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ggplot(data = starwars, mapping = aes(x = height, y = mass)) +
  geom_point() +
  facet_wrap(~ eye_color)

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Facet summary

facet_grid():
2d grid
rows ~ cols
use . for no split
facet_wrap(): 1d ribbon wrapped into 2d

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More ggplot2 info:

ggplot2 in 2

https://leanpub.com/ggplot2in2/c/sta-212-f19

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`Starwars`

Go to RStudio Cloud and launch the Starwars project.
Open and knit the R Markdown document

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Identifying variables

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Types of variables

Numerical variables (quantitative variables) can be classified as continuous or discrete based on whether or not the variable can take on an infinite number of values or only non-negative whole numbers, respectively.
If the variable is categorical, we can determine if it is ordinal based on whether or not the levels have a natural ordering.

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Visualizing numerical data

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Describing shapes of numerical distributions

shape:
- skewness: right-skewed, left-skewed, symmetric (skew is to the side of the longer tail)
- modality: unimodal, bimodal, multimodal, uniform
center: mean (mean), median (median), mode (not always useful)
spread: range (range), standard deviation (sd), inter-quartile range (IQR)
unusual observations

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Histograms

ggplot(data = starwars, mapping = aes(x = height)) +
  geom_histogram(binwidth = 10)

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Density plots

ggplot(data = starwars, mapping = aes(x = height)) +
  geom_density()

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Side-by-side box plots

ggplot(data = starwars, mapping = aes(y = height, x = gender)) +
  geom_boxplot()

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Side-by-side box plots

ggplot(data = starwars, mapping = aes(y = height, x = gender)) +
  geom_boxplot(outlier.shape = NA) + 
  geom_jitter()

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Show your data!

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Visualizing categorical data

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Bar plots

ggplot(data = starwars, mapping = aes(x = gender)) +
  geom_bar()

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Segmented bar plots, counts

ggplot(data = starwars,
       mapping = aes(x = gender, fill = hair_color)) +
  geom_bar()

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Segmented bar plots, proportions

ggplot(data = starwars, 
       mapping = aes(x = gender, fill = hair_color)) +
  geom_bar(position = "fill") +
  labs(y = "proportion")

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Which plot is more appropriate?

Which plot is a more useful representation for visualizing the relationship between gender and height?

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?, h	Toggle this help

Data and visualization 📉

Dr. Lucy D’Agostino McGowan

Starwars

Exploratory data analysis

What is EDA?

Data visualization

Data visualization

ggplot2 ∈∈ tidyverse

Hello ggplot2!

ggplot2 components

ggplot2 premise

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Hello ggplot2!

Visualizing Star Wars

Dataset terminology

Dataset terminology

Luke Skywalker

What's in the Star Wars data?

What's in the Star Wars data?

Mass vs. height

What's that warning?

Mass vs. height

Jabba!

Additional variables

Aesthetics

Aesthetics options

Mass vs. height + gender

Mass vs. height + gender

Mass vs. height + gender

Aesthetics summary

Faceting

Faceting options

Dive further...

Dive further...

Facet summary

More ggplot2 info:

ggplot2 in 2

https://leanpub.com/ggplot2in2/c/sta-212-f19

Starwars

Identifying variables

Types of variables

Visualizing numerical data

Describing shapes of numerical distributions

Histograms

Density plots

Side-by-side box plots

Side-by-side box plots

Show your data!

Visualizing categorical data

Bar plots

Segmented bar plots, counts

Segmented bar plots, proportions

Which plot is more appropriate?

Starwars

Help

Data and visualization
📉

`Starwars`

ggplot2 $\in$ tidyverse

`Starwars`

`Starwars`