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   3.5.1     ✔ 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, colour = 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)) +
    facet_wrap(~class, nrow = 2)

geometric objects

different visual object to represent data

ggplot(data = mpg) +
    geom_point(mapping = aes(x = displ, y = hwy))

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

not every aesthetic works with every geom

two geoms in the same graph!

ggplot(data = mpg) +
    geom_point(mapping = aes(x = displ, y = hwy, colour = class))

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

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

specify different data for each layer

statistical transformation

position adjustments

adjustments for bar charts

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

adjustments for scatterplots

coordinate systems

switch x and y

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

set the aspect ratio correctly for maps

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.