Welcome

Ch1 Introduction

The data science project workflow

Prerequisites

  • R
  • RStudio
  • r packages

Install the tidyverse package

Running R code

1+2
## [1] 3

Getting help

  • Google
  • Stackoverflow

Ch2 Introduction to Data Exploration

Ch3 Data Visualization

Set up

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

data

mpg
## # A tibble: 234 × 11
##    manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
##    <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
##  1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
##  2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
##  3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
##  4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
##  5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
##  6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
##  7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
##  8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
##  9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
## 10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
## # ℹ 224 more rows

aesthetics

  • x
  • y
  • color
  • size
  • alpha
  • shape
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = class))

common problems

  • Sometimes you’ll run the code and nothing happens.
  • Putting the + in the wrong place.

How to get help

  • ? function name
  • Select the function name and press F1
  • Read the error message
  • Google the error message

facets

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = class)) +
    facet_grid(drv ~ .) +
    facet_wrap(~ class, nrow = 2)

geometric objects

different visual object to represent data

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + 
  geom_point() + 
  geom_smooth()
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

ggplot(data = mpg) +
  geom_smooth(
    mapping = aes(x = displ, y = hwy, color = drv),
    show.legend = FALSE
  )
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = drv)) + 
  geom_point() + 
  geom_smooth(se = FALSE)
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

not every aesthetic works with every geom

two geoms in the same graph!

local vs. global mappings This makes it possible to display different aesthetics in different layers.

specify different data for each layer

statistical transformation

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge")

position adjustments

adjustments for bar charts

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, colour = cut))

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = cut))

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = clarity))

adjustments for scatterplots

coordinate systems

switch x and y

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = cut)) + coord_flip()

set the aspect ratio correctly for maps

ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
  geom_boxplot() +
  coord_flip()

Polar coordinates reveal an interesting connection between a bar chart and a Coxcomb chart.

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = cut)) + coord_polar()

the layered grammar of graphics

The grammar of graphics is based on the insight that you can uniquely describe any plot as a combination of:

  • a dataset,
  • a geom,
  • a set of mappings,
  • a stat,
  • a position adjustment,
  • a coordinate system, and
  • a faceting scheme.