-
Notifications
You must be signed in to change notification settings - Fork 23
/
Copy path01-addendum.Rmd
137 lines (113 loc) · 4.56 KB
/
01-addendum.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
---
title: "Lab 01: Addendum"
subtitle: "CS631"
author: "Alison Hill"
output:
html_document:
theme: flatly
toc: TRUE
toc_float: TRUE
toc_depth: 2
number_sections: TRUE
---
```{r setup, include = FALSE, cache = FALSE}
knitr::opts_chunk$set(error = TRUE, comment = NA, warning = FALSE, errors = FALSE, message = FALSE, tidy = FALSE, cache = FALSE)
```
# Packages
```{r}
library(tidyverse)
library(extrafont)
```
```{r}
hot_dogs <- read_csv("http://bit.ly/cs631-hotdog",
col_types = cols(
gender = col_factor(levels = NULL)
))
```
# Visualizing new world records (for males)
Let's adapt [Nathan Yau's hot dog contest example](http://flowingdata.com/2009/07/02/whos-going-to-win-nathans-hot-dog-eating-contest/hot-dogs-2/).
The first thing we notice is that we don't have data about whether each year's winner is a record or not. Since our data is nicely tidy, we can use `dplyr` window functions:
- First, we use base R's `cummax` to create a new variable that reflects the maximum HDB eaten cumulatively, that is, compared to all earlier years. For this reason, the `arrange(year)` here is critical.
- Next, we want to know if the `hdb_record` is actually a *new* record or not, compared to all previous years. We can use `case_when` to create a logical variable that is TRUE if the `hdb_record` for a given year is greater than the `hdb_record` from the year before (using `dplyr::lag`). If not, this variable is FALSE.
```{r}
hot_dogs_records <- hot_dogs %>%
filter(year >= 1980 & gender == 'male') %>%
arrange(year) %>%
mutate(hdb_record = cummax(num_eaten),
new_record = case_when(
hdb_record > lag(hdb_record) ~ TRUE,
TRUE ~ FALSE
)) %>%
filter(year >= 1981)
```
We'll also make our x-axis ticks again...
```{r}
years_to_label <- seq(from = 1981, to = 2017, by = 4)
years_to_label
hd_years <- hot_dogs_records %>%
distinct(year) %>%
mutate(year_lab = ifelse(year %in% years_to_label, year, ""))
```
```{r}
hdb_records <- ggplot(hot_dogs_records,
aes(x = year, y = num_eaten)) +
geom_col(aes(fill = new_record)) +
labs(x = "Year", y = "Hot Dogs and Buns Consumed") +
ggtitle("Nathan's Hot Dog Eating Contest Results, 1981-2017") +
scale_fill_manual(values = c('#284a29', '#629d62')) +
scale_y_continuous(expand = c(0, 0),
breaks = seq(0, 70, 10)) +
scale_x_continuous(expand = c(0, 0),
breaks = hd_years$year,
labels = hd_years$year_lab) +
coord_cartesian(xlim = c(1980, 2018), ylim = c(0, 80)) +
theme_minimal() +
theme(plot.title = element_text(hjust = 0.5),
axis.text = element_text(size = 12),
panel.background = element_blank(),
axis.line.x = element_line(color = "gray92",
size = 0.5),
axis.ticks = element_line(color = "gray92",
size = 0.5),
text = element_text(family = "Lato"),
legend.position = "bottom",
panel.grid.minor = element_blank())
hdb_records
```
# Visualizing background data
We'll do this to highlight differences in gender.
https://drsimonj.svbtle.com/plotting-background-data-for-groups-with-ggplot2
```{r}
hot_dogs_both <- hot_dogs %>%
filter(year >= 1981)
hot_dog_behind <- hot_dogs_both %>%
filter(gender == "male") %>%
select(-gender)
```
```{r}
hdb_facets <- ggplot(hot_dogs_both,
aes(x = year, y = num_eaten)) +
geom_col(data = hot_dog_behind, fill = '#4254a7', alpha = .1) +
geom_col(aes(fill = gender), show.legend = FALSE) +
facet_wrap(~gender) +
labs(x = "", y = "Hot Dogs and Buns Consumed") +
ggtitle("Nathan's Hot Dog Eating Contest Results, 1981-2017") +
scale_fill_manual(values = c('#4254a7', '#f4b31a')) +
scale_y_continuous(expand = c(0, 0),
breaks = seq(0, 70, 10)) +
scale_x_continuous(expand = c(0, 0),
breaks = seq(1981, 2017, 6)) +
coord_cartesian(xlim = c(1980, 2018), ylim = c(0, 80)) +
theme(axis.text = element_text(size = 10),
panel.background = element_blank(),
axis.line.x = element_line(color = "grey80",
size = 0.5),
axis.ticks = element_line(color = "grey80",
size = 0.5),
text = element_text(family = "Lato"),
legend.position = "bottom",
panel.grid.minor = element_blank(),
panel.spacing = unit(1, "lines"))
hdb_facets
```