-
Notifications
You must be signed in to change notification settings - Fork 4
/
Copy pathplaying_gganimate_frames.R
174 lines (132 loc) · 7.06 KB
/
playing_gganimate_frames.R
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
165
166
167
168
169
170
171
172
173
174
---
layout: post
title: How to plot animated maps with gganimate
date: "2017-05-10 10:11:29 UYT"
published: true
tags: [rstats, r, gganimate, maps, gif]
description: How to plot an animated map using the gganimate package, and produce a .gif file to share it!
---
Here I show how to plot an animated map using the `gganimate` package, and produce a .gif file to share it!
<!--more-->
This is the third one of the 3-posts-series, where I go from fetching Twitter users and preparing the data to visualizing it (If I wanted to show everything I've done in a single post, it would be almost as long as my first one! And I didn't want that `r emo::ji("stuck_out_tongue_closed_eyes")` ):
* [How to fetch Twitter users with R]: the title is kind of self explanatory...
* [How to deal with ggplotly huge maps]: where I go through the details of why I chose not to use `ggplotly` and use `plot_geo` instead to generate HTML.
* How to plot animated maps with gganimate: this one. Again, pretty obvious subject.
Finally [I present my favourite visualization here]({% post_url 2017-05-10-visualizing-r-ladies-growth %}).
<br />
## The data
Let's take a look at the R-Ladies' chapters' Twitter accounts dataframe (`rladies`) I produced in the first post of this series:
```{r load_data, echo = FALSE, message = FALSE, warning = FALSE}
# You can find everything I use here:
# https://github.com/d4tagirl/R-Ladies-growth-maps
library(knitr)
# This I took (with a few tweaks courtesy of my amazing hubby <3) from gganimate documentation https://github.com/dgrtwo/gganimate/blob/master/README.Rmd
library(animation)
ani.options(autobrowse = FALSE, ani.width = 850, ani.height = 510)
opts_knit$set(animation.fun = function(x, options, format = "gif") {
x = c(knitr:::sans_ext(x), knitr:::file_ext(x))
fig.num = options$fig.num
format = sub("^[.]", "", format)
base = sub(paste0(fig.num, '$'), '', x[1])
fig.fname = paste0(sub(paste0(fig.num, "$"), "*", x[1]),
".", x[2])
mov.fname = paste0(sub('-$', '', base), '.', format)
# order correctly
figs <- Sys.glob(fig.fname)
figs <- figs[order(as.numeric(stringr::str_match(figs, paste0("(\\d+)\\.", x[2]))[, 2]))]
animation::im.convert(figs, output = mov.fname)
original_path <- basename(mov.fname)
file.rename(original_path, mov.fname)
file.remove(figs)
sprintf("", options$label, paste0(opts_knit$get("base.url"), mov.fname))
})
knitr::opts_chunk$set(dpi = 150, fig.align = 'center', screenshot.force = FALSE, fig.height = 4, fig.cap = "")
# options(width = 80, dplyr.width = 150)
```
```{r head_users, message = FALSE, warning = FALSE}
library(readr)
library(dplyr)
url_csv <- 'https://raw.githubusercontent.com/d4tagirl/R-Ladies-growth-maps/master/rladies.csv'
rladies <- read_csv(url(url_csv)) %>%
select(-1)
library(DT)
datatable(rladies, rownames = FALSE,
options = list(pageLength = 5))
```
<br />
## Plotting the map using ggplot2
The goal is to produce a map where each chapter is plotted according to its location, with the point's size indicating the amount of Twitter followers.
I use the `maps` package to get the world map, using the `ggplot2::ggplot` and `ggthemes::theme_map` functions for plotting it nicely. Then I plot the chapters choosing the purple color, obviously!
```{r message = FALSE, warning = FALSE}
library(ggplot2)
library(maps)
library(ggthemes)
world <- ggplot() +
borders("world", colour = "gray85", fill = "gray80") +
theme_map()
map <- world +
geom_point(aes(x = lon, y = lat,
size = followers),
data = rladies,
colour = 'purple', alpha = .5) +
scale_size_continuous(range = c(1, 8),
breaks = c(250, 500, 750, 1000)) +
labs(size = 'Followers')
```
```{r static_chapters_map, echo = FALSE, message = FALSE, warning = FALSE}
map
```
The `range` parameter is what controls the scale of the points' size.
<br />
## Animating the map using gganimate
Now let's animate the map! The core thing here is that I want every chapter appearing following the creation timeline, to somehow tell a story with the map. Lets start by animating `map`: the `ggplot` object I just created. I have to make a few changes for `gganimate` to work:
- `gganimate` requires a `frame` aesthetic: I'll use the `created_at` variable. You set this as a new aesthetic in `ggplot` which is ignored by it (as shown in the warning messages), but `gganimate` recognizes and uses it;
- I also add the `cumulative = TRUE`, an additional aesthetic (same comment about `ggplot` ignoring it), so once the chapter appears on the map, it keeps showing in all the following frames.
Following [my good friend Bruno](https://www.linkedin.com/in/bruno-chiesa-gispert-b1a6b942)'s suggestion, I add an empty frame at the beginning so that the first frame you see is just the empty map. I generate a dataframe with the same structure than the original one, with some random data, except for the `created_at` field that should be filled with a date prior to the first chapter creation for it to appear at the beginning.
And I add some empty frames at the end as well, to be able to see the final composition of chapters for a bit longer.
```{r}
rladies <- rladies %>%
slice(7:9) %>%
mutate(frame = reorder(as.character(created_at), created_at, ordered = TRUE))
ghost_points_ini <- tibble(
frame = reorder('before', as.Date('2011-09-01')),
followers = 0, lon = 0, lat = 0)
ghost_points_fin <- tibble(
created_at = seq(max(rladies$created_at) + days(1),
as.Date('2017-05-20'),
by = 'days'),
followers = 0, lon = 0, lat = 0) %>%
mutate(frame = reorder(rep('today', times = length(created_at)),
created_at, ordered = TRUE))
levels = unlist(list(ghost_points_ini$frame,
rladies$frame,
ghost_points_fin$frame))
levels <- c(as.character(levels))
levels(rladies$frame) = c(levels(rladies$frame), levels)
levels(ghost_points_ini$frame) = c(levels(ghost_points_ini$frame), levels)
levels(ghost_points_fin$frame) = c(levels(ghost_points_fin$frame), levels)
```
Then I add an extra layer to the `ggplot`: the second `geom_point`, with the `alpha` parameter set to `0` so the point will not show in the plot.
```{r ani_map, fig.show = "animate", fig.align = "center", message = FALSE}
map <- world +
geom_point(aes(x = lon, y = lat,
size = followers,
frame = frame,
cumulative = TRUE),
data = rladies, colour = 'purple', alpha = .5) +
geom_point(aes(x = lon, y = lat, # this is the init transparent frame
size = followers,
frame = frame,
cumulative = TRUE),
data = ghost_points_ini, alpha = 0) +
geom_point(aes(x = lon, y = lat, # this is the final transparent frames
size = followers,
frame = frame,
cumulative = TRUE),
data = ghost_points_fin, alpha = 0) +
scale_size_continuous(range = c(1, 10), breaks = c(250, 500, 750, 1000)) +
labs(size = 'Followers')
library(gganimate)
ani.options(interval = 0.2)
gganimate(map)
```