Note: The content of this article is based on the data what was collected by the project team of Professor Ziqi Chen, School of Mathematics and Statistics, Central South University(China). The data used for this analysis are not complete.
10-import
Load the necessary packages.
library(tidyverse)
library(ggplot2)
library(gganimate)
library(plotly)
library(readxl)
library(lubridate)
library(gifski)
Read data from Excel.
abroad_raw <- read_excel("data/【海外】疫情数据.xlsx")
Convert wide tables to long tables and process date data into a usable form.
data <- abroad_raw %>%
select(-name) %>%
pivot_longer(
-country,
names_to = "date",
values_to = "number",
values_drop_na = TRUE
) %>%
mutate(date = as.integer(date)) %>%
mutate(date = as.Date(date, origin = "1899-12-30"))
20-exploratory-data-analysis
line <- data %>%
ggplot(aes(x = date, y = number, group = country)) +
geom_line(aes(color = country), size = 2, alpha = 0.5) +
geom_point(aes(color = country), size = 3) +
geom_text(
aes(label = country),
#color = "black",
check_overlap = TRUE,
hjust = 0,
nudge_x = 0.3
) +
ggdark::dark_theme_bw() +
theme(plot.title = element_text(face = "bold", size = 20)) +
guides(color = FALSE) +
labs(
title = paste0('COVID-19 non-China cases at ', '{frame_along}'),
y = "Case number",
x = "Date"
) +
transition_reveal(date) +
view_follow() +
ease_aes(default = 'linear')
animate(
line,
width = 1000,
height = 500,
renderer = gifski_renderer(),
duration = 20,
rewind = FALSE,
end_pause = 1
)
anim_save("output.gif")
Project GitHub page: COVID-19-EDA
