This week has data for Meteors from 8th century to year 2013(well 2101 is an error).
So I have used the packages tidyverse,gganimate,maps and ggthemes to make this more interesting. There are three plots which I have generated, two of them are inspired by others.
meteorites <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-06-11/meteorites.csv")
library(tidyverse)
library(gganimate)
library(maps)
library(ggthemes)Meteorites over the Year
Based on the below tweet I was inspired to creata a similar plot which is animated by years.
#TidyTuesday Playing for the first time with gganimate to visualize meteorite collisions since the 1900s ;)
— CristóbalM (@Cristobal_Montt) June 10, 2019
code: https://t.co/gcEoQiQ4SB#rstats pic.twitter.com/ttBCOsfuJ3
Frames change is based on year, and meteors which have missing values are dropped.
meteorites_rm<-remove_missing(meteorites)
world <- ggplot() + theme_map()+
borders("world", colour = "#353535", fill = "#74e04a")
plot1<-world+geom_point(data=meteorites_rm,x=meteorites_rm$long,y=meteorites_rm$lat,
color="#e20e06")+
transition_states(meteorites_rm$year,transition_length = 1,state_length = 1)+
theme(plot.title = element_text(color = "black",
size = 15,
face = "bold"),
panel.background = element_rect(fill = "#5e8bed")) +
ggtitle("Meteors Falling from the sky by Name Type",subtitle = "Year:{closest_state}")
animate(plot1,nframes=253,fps=1,detail = 1)
Meteorites and Classes
A Bar plot which changes for the top 5 classes based on their counts after the year 1999. This plot is based on the blog post published in Rbloggers. This type is a very popular animated bar plot.
test<-meteorites%>%
subset(year >= 2000 & year < 2101) %>%
group_by(year,class) %>%
count(class) %>%
group_by(year)%>%
mutate(rank=rank(-n),
value_lbl=paste0("",n)) %>%
group_by(class) %>%
filter(rank <=5) %>%
ungroup()
plot3<-ggplot(test, aes(rank, group = class,
fill = as.factor(class), color = as.factor(class))) +
geom_tile(aes(y = n/2,height = n,width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = 0, label = paste(class, " ")), vjust = 0.2, hjust = 1) +
geom_text(aes(y=n,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) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
panel.grid.major.x = element_line( size=.1, color="grey" ),
panel.grid.minor.x = element_line( size=.1, color="grey" ),
plot.title=element_text(size=25, hjust=0.5, face="bold", colour="grey", vjust=-1),
plot.subtitle=element_text(size=18, hjust=0.5, face="italic", color="grey"),
plot.caption =element_text(size=8, hjust=0.5, face="italic", color="grey"),
plot.background=element_blank(),
plot.margin = margin(2,2, 2, 4, "cm")) +
transition_states(year, transition_length = 3, state_length = 2) +
view_follow(fixed_x = TRUE) +
labs(title = 'Meteorites Classes by Year: {closest_state}',
subtitle = "Top 5 Classes")
# For GIF
animate(plot3, nframes=200, fps = 20) 
Below is the same plot but not animated, therefore we can understand patiently how the top 5 classes counts change after year 1999.
test %>%
ggplot(.,aes(x=class,y=n,label=rank,fill=class))+geom_col()+
facet_wrap(~factor(year))+geom_text(vjust=-0.5)+
geom_text(aes(label=n),vjust=1)+
ggtitle("Meteors class count from 2000 to 2013",subtitle = "Top 5 Ranks")+
scale_y_continuous(expand = c(0,75))+theme_dark()+
theme(axis.text.x = element_text(angle = 45))
So I posted a tweet about the Meteor data for week 24 of #TidyTuesday.
Well this is above bar plot but in-animated, but with facets for the same years.#TidyTuesday . GitHubcode:https://t.co/k8bBg3uso3 pic.twitter.com/b5zQa7J9Yk
— Amalan Mahendran (@Amalan_Con_Stat) June 11, 2019
THANK YOU