-
Notifications
You must be signed in to change notification settings - Fork 1
/
2019_41_Powerlifting.Rmd
164 lines (135 loc) · 6.51 KB
/
2019_41_Powerlifting.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
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
---
title: "2019_41_Powerlifting"
author: "Jongseung John Lim"
date: "10/8/2019"
output:
html_document:
theme: paper
highlight: kate
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE)
#install.packages("tidyverse")
devtools::install_github("dkahle/ggmap")
devtools::install_github("dr-harper/ggmapstyles")
#devtools::install_github("clauswilke/ggtext")
```
```{r prep, message=FALSE}
library(tidyverse)
library(ggtext)
library(gganimate)
library(gridExtra)
library(reshape2)
library(ghibli)
library(here)
source(here::here('R/utils/secrets.R'))
source(here::here('R/utils/utils.R'))
source(here::here("R/utils/custom_themes.R"))
theme_set(theme_custom(base_family="dosis"))
```
```{r data}
ipf_lifts <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-10-08/ipf_lifts.csv")
ipf_lifts <- ipf_lifts %>%
mutate(date = substr(date, 1, 4))
```
```{r theme}
theme_update(rect = element_rect(fill = "grey10"),
plot.title = element_markdown(size = 35,
lineheight = 1.2,
hjust = 0.5),
plot.subtitle = element_markdown(size = 22,
color = "grey50",
hjust = 0,
lineheight = 1.4),
plot.caption = element_markdown(family = "dosis",
face = "bold",
size = 18,
color = "grey50"),
axis.text.x = element_text(size = 14,
family = "Roboto Mono",
color = "grey40"),
axis.text.y = element_text(size = 14,
family = "Roboto Mono",
color = "grey40"),
axis.ticks.x = element_line(color = "grey30"),
axis.ticks.y = element_blank(),
strip.background = element_blank())
```
```{r pressure, echo=FALSE}
male <- subset(ipf_lifts, sex=="M") %>%
mutate(date = substr(date, 1, 4) )
female <- subset(ipf_lifts, sex=="F") %>%
mutate(date = substr(date, 1, 4) )
maleBestSquat <- male %>%
group_by(date) %>%
mutate(Rank = row_number(-best3squat_kg) * 1,
Value_rel = best3squat_kg/best3squat_kg[Rank==1],
Value_lbl = paste0(" ", best3squat_kg)) %>%
filter(Rank <= 10) %>%
ungroup()
theme_set(theme_minimal(base_family="dosis"))
p <- ggplot(maleBestSquat, aes(Rank, group = name, fill = as.factor(name), color = as.factor(name) )) +
geom_tile(aes(y = best3squat_kg/2,
height = best3squat_kg,
width = 0.5), alpha = 0.8, color = NA) +
geom_text(aes(y = 0, label = paste(name, " ")), vjust = 0.2, hjust = 1.05) +
geom_text(aes(y=best3squat_kg, label = Value_lbl, hjust=0)) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title='{closest_state}', x = "", y = "Squatting Weight (kg)",
caption = "Sources: Open Powerlifting | Plot generated by John Lim") +
theme(plot.title = element_text(hjust = 0, size = 22, face="bold"),
axis.ticks.y = element_blank(), # These relate to the axes post-flip
axis.text.y = element_blank(), # These relate to the axes post-flip
plot.margin = unit(c(1,1,1,5), "cm")) +
transition_states(date, transition_length = 5, state_length = 10) +
ease_aes('quadratic-in-out') + enter_fade() + exit_fade()
anim <- animate(p, fps = 30, duration = 30, width = 800, height = 600)
anim_save(here::here("plots/2019_41/2019_41_Powerlifting.gif"), anim)
#ggplot(male, aes(name, best3squat_kg)) + geom_point(alpha = 0.7, show.legend = FALSE) + facet_wrap( ~event) + labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') + transition_states(date, transition_length = 4, state_length = 1)
```
```{r scatterplot}
male <- subset(ipf_lifts, sex=="M") %>%
mutate(date = as.numeric(substr(date, 1, 4) ) )
female <- subset(ipf_lifts, sex=="F") %>%
mutate(date = as.numeric(substr(date, 1, 4) ) )
theme_set(theme_minimal(11, "dosis"))
theme_update(plot.title = element_markdown(hjust = 0, size = 22, face="bold"),
plot.margin = margin(5,5,5,10, "mm"))
meltedmale <- melt(male, measure.vars = c("best3squat_kg", "best3bench_kg", "best3deadlift_kg"))
meltedmale <- subset(meltedmale, place == 1)
spm <- ggplot(meltedmale, aes(x=bodyweight_kg, y=value, color=variable, fill=variable)) +
geom_point( position = position_jitter(w = 1, h = 1)) +
geom_smooth(aes(group=variable), method="loess", size=1, color="grey30") +
xlim(c(35, 200)) +
ylim(c(0, 500)) +
labs(subtitle="Male champions",
y="Lifting weight (kg)",
x="Body weight (kg)",
title="<img src='img/powerlifting.png' width='30'></img> Body Weight vs Lifting Performance in Power Lifting<br>") +
scale_colour_ghibli_d(name = "LaputaMedium", direction = -1, "Lifting cateogry" , labels= c("Sqauat", "Bench", "Deadlift")) +
scale_fill_ghibli_d(name = "LaputaMedium", direction = -1, "Lifting cateogry" , labels= c("Sqauat", "Bench", "Deadlift"))
meltedfemale <- melt(female, measure.vars = c("best3squat_kg", "best3bench_kg", "best3deadlift_kg"))
meltedfemale <- subset(meltedfemale, place == 1)
spf <- ggplot(meltedfemale, aes(x=bodyweight_kg, y=value, color=variable, fill=variable)) +
geom_point( position = position_jitter(w = 1, h = 1)) +
geom_smooth(aes(group=variable), method="loess", size=1, color="grey30") +
xlim(c(35, 200)) +
ylim(c(0, 500)) +
labs(subtitle="Female champions",
y="Lifting weight (kg)",
x="Body weight (kg)",
caption = "Source: Open Powerlifting | Visualization by John Lim") +
scale_colour_ghibli_d("PonyoMedium", direction = -1, "Lifting cateogry" , labels= c("Sqauat", "Bench", "Deadlift")) +
scale_fill_ghibli_d(name = "PonyoDark", direction = -1, "Lifting cateogry" , labels= c("Sqauat", "Bench", "Deadlift"))
g <- arrangeGrob(spm, spf, layout_matrix = rbind(c(1), c(1), c(1), c(1), c(1), c(1),c(2) ,c(2) ,c(2),c(2),c(2)))
plot(g)
```
```{r saveplot}
ggsave(g, file = "plots/2019_41/2019_41_Powerlifting.png", width= 10.5, height = 9.5, type = "cairo", dpi = 96) # adjust dpi accordingly
ggsave(g, file = "plots/2019_41/2019_41_Powerlifting.pdf", width= 10.5, height = 9.5, device =cairo_pdf, dpi = 96) # adjust dpi accordingly
```