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Views_script.R
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Views_script.R
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`%notin%` <- Negate(`%in%`) ### function to reverse %in%
library(tidyverse)
library(janitor)
library(lubridate)
library(stringr)
library(patchwork)
library(colorBlindness)
BVCN_colors <- c("#2C76B5", "#FF0000")
theme_set(theme_minimal(base_family="Arial")+
theme(text=element_text(size=10, color="black"),
axis.title=element_text(size=12, color = "black"),
axis.text=element_text(size=10, color = "black"),
strip.text=element_text(size=14, color="black"),
legend.text=element_text(size=10),
legend.title=element_text(size=12),
axis.title.y=element_text(margin=margin(l=10, unit="pt"))))
watches_plot <- read_csv("Date 2020-04-05_2021-04-22 Bioinformatics Virtual Coordination Network/Table data.csv") %>%
mutate(Date=ymd(Date)) %>%
drop_na() %>%
arrange(Date) %>%
clean_names() %>% ### makes lower case values
group_by(month=floor_date(date, "month")) %>%
summarise(views=sum(views)) %>%
ggplot() +
geom_line(aes(x = month, y = views), size = 1, col = "darkorange",alpha=0.6, linetype="dashed") +
geom_point(aes(x=month, y=views),pch=21, fill="darkorange", colour="#020202", stroke=1.2, size=3)+
xlab("Date") +
ylab("Monthly \n YouTube \nviews") +
coord_cartesian(ylim=c(0,3000))+
theme(axis.title.y = element_text(angle = 0, vjust=0.5))
playlist_plot <- read_csv("Playlist 2020-04-05_2021-04-22 Bioinformatics Virtual Coordination Network/Table data.csv") %>%
drop_na() %>%
clean_names() %>%
mutate(playlist_title=str_remove_all(playlist_title, "Topic: ")) %>%
filter(!str_detect(playlist_title,"Speaker Introduction")) %>%
filter(playlist_title %notin% c("General Information", "BVCN Essentials")) %>%
mutate(prop_views=(views/sum(views))*100) %>%
ggplot(aes(x=playlist_title, y=prop_views))+
geom_bar(stat="identity", aes(x=reorder(playlist_title, prop_views), y=prop_views), col=NA, fill="darkorange", size=2, alpha=0.8)+
geom_text(aes(label=sprintf("%1.2f%%", prop_views), group=1),stat="identity", hjust= -0.3, size=3, colour="black")+
coord_flip()+
theme(axis.title.x = element_text(hjust=1.55), axis.title.y=element_blank())+
ylab("% Views")+
ylim(0,35)+
scale_x_discrete(labels = function(x) str_wrap(str_replace_all(x, "foo" , " "),
width = 12))
traffic_plot <- read_csv("Traffic source 2020-04-05_2021-04-22 Bioinformatics Virtual Coordination Network/Table data.csv") %>%
clean_names() %>%
mutate(source=if_else(traffic_source %in% c("External","Direct or unknown"), "External", "within \nYouTube")) %>%
filter(traffic_source != "Total") %>%
mutate(prop_views=(views/sum(views))*100) %>%
ggplot(aes(x=traffic_source, y=prop_views))+
geom_bar(stat="identity", aes(x=reorder(traffic_source, prop_views), y=prop_views, fill=source), col=NA, size=2, alpha=0.8)+
geom_text(aes(label=sprintf("%1.2f%%", prop_views), group=1),stat="identity", hjust= -0.3, size=3, colour="black")+
scale_fill_manual(values=BVCN_colors)+
coord_flip()+
labs(fill="Traffic source")+
facet_grid(rows=vars(source), scales="free_y", space="free_y", switch="y")+
theme(strip.text.y=element_blank(),legend.position = c(0.7, 0.2), axis.title.x = element_blank(), axis.title.y=element_blank())+
ylim(0,35)+
scale_x_discrete(labels = function(x) str_wrap(str_replace_all(x, "foo" , " "),
width = 12))
slack_plot <- read_csv("slack data/Bioinformatics Virtual Coordination Network - Pandemic Enterprise Analytics All time - May 4, 2021.csv") %>%
arrange(Date) %>%
filter(Date < "2021-04-01") %>%
filter(Date >"2020-04-06") %>%
clean_names() %>%
select(date, weekly_active_members, weekly_members_posting_messages) %>%
pivot_longer(!date, names_to="member", values_to="value") %>%
ggplot(aes(x=date, y=value, color=member, linetype=member)) +
geom_line(size = 1)+
scale_color_manual(values=c("#006F51", "purple"), name="", labels=c("Active members","Members posting messages"))+
scale_linetype_manual(values=c("solid", "twodash"),name="", labels=c("Active members","Members posting messages"))+
xlab("Date") +
ylab("Slack \nactive \nusers") +
theme(axis.title.y = element_text(angle = 0, vjust=0.5), legend.position = c(0.7, 0.8))
plot1 <- (watches_plot+theme(axis.title.y=element_text(margin = margin(t = 0, r = -40, b = 0, l = 10))))/(playlist_plot+traffic_plot)+
plot_annotation(tag_levels="A")&
theme(plot.caption=element_text(size=12, color = "black", hjust=0.5),
plot.tag = element_text(size = 16, face="bold"))
Figure1 <- plot1/(slack_plot+theme(axis.title.y=element_text(margin = margin(t = 0, r = -40, b = 0, l = 10))))+plot_layout(heights=c(1,2,1))&
theme(plot.tag = element_text(size = 16, face="bold"))
Figure1
cvdPlot(Figure1) ### check colour blind compatible
### ggsave(plot=Figure1, "Figure/Figure1.tiff", type="cairo", dpi=300, units="mm", width=180, height=300) ### specifications for Frontiers submission
### ggsave(plot=Figure1, "Figure/Figure1.png", type="cairo", dpi=300, units="mm", width=180, height=300) ### specification to embed in Google Doc MS