library(tidyverse)
tuesdata <- tidytuesdayR::tt_load(2021, week = 34)
tidytuesdayR::readme(tuesdata)Designing Speech Interactions from the Imagined Ideal of Star Trek
voice user interfaces (VUIs) like Alexa reveals mismatches between current designs and user expectations The analysis study voice interactions with the Enterprise’s computer and compare them to current interactions
computer <- tuesdata$computer
head(computer,3)
DataExplorer::profile_missing(computer)df <- computer %>%
select(char,line,type,pri_type,nv_resp:error) %>% #count(char)
mutate(char=if_else(str_detect(char,"Computer"),"Computer",char),
type=if_else(str_detect(type,"command"),"Command",type),
type=if_else(str_detect(type,"question"),"Question",type))df %>%
group_by(char) %>%
summarize(type,nv_resp) %>%
ungroup() %>%
ggplot(aes(y=char,x=type,z=nv_resp)) +
stat_summary_hex(alpha=0.8,bins=50)+
scale_fill_viridis_c()+
labs(fill = "char",title = "type")+
theme(axis.text.x = element_text(angle=90,size=6))library(extrafont)
loadfonts()final <- df %>% #count(type,nv_resp,sort=TRUE)%>%
ggplot(aes(x=fct_reorder(sort(type,decreasing = TRUE),nv_resp),group=nv_resp)) +
geom_histogram(aes(fill=nv_resp),stat="count",position ="stack")+ #position_dodge(width=0))+
coord_flip()+
scale_fill_viridis_d()+
labs(title="Type of words when the computer completes the query but without speaking a response",
subtitle="False or True?",
caption="Infographic: @fgazzelloni\n DataSource: TidyTuesday Week34:Star Trek Voice Commands,SpeechInteraction.org",
fill="Response",
y="N°",x="Word type") +
ggthemes::theme_solarized()+
theme(text = element_text(family="Impact"),
axis.text.x = element_text(angle=0,size=10),
axis.text.y = element_text(angle=0,size=10),
axis.title.x = element_text(size=14),
axis.title.y = element_text(size=14),
plot.title.position = "plot",
plot.title = element_text(face="bold",size=20),
plot.subtitle = element_text(face="bold",size=14),
plot.caption = element_text(size=10),
plot.caption.position = "plot")ragg::agg_png("w34_star_trek.png",
res = 320, width = 14, height = 8, units = "in")
final
dev.off()library(scales)
library(ggbump)
library(extrafont)
library(showtext)
library(cowplot)
library(ggstream)
library(colorspace)
library(ggpubr)
library(ggbump)
library(ggimage)
library(magick)# read the image, attach the Tidytuesday logo and save it --------------------------
library(ggimage)
library(magick)
tidy_logo<-image_read("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/static/plot_logo.png") %>%
image_resize("300x300")
img <-image_read("1200px-Star_Trek_TNG_logo.svg.png")
tidy_final <- image_read("w34_star_trek.png")
attached_logo <- image_composite(tidy_final, tidy_logo,
operator="atop",
gravity="southwest")
image_write(attached_logo, path = "w34_star_trek.png", format = "png")
tidy_final2 <- image_read("w34_star_trek.png")
attached_logo2 <- image_composite(tidy_final2, img,
operator="atop",
gravity="northeast")
image_write(attached_logo, path = "w34_star_trek.png", format = "png") library("ggmosaic")final2 <- df %>%
select(type,char_type) %>%
ggplot() +
geom_mosaic(aes(x = product(type, char_type), fill = type)) +
labs(title="Type of request by count Person or Computer?",
x="",fill="Type of interaction",
caption="Infographic: @fgazzelloni\n DataSource: TidyTuesday Week34:Star Trek Voice Commands,SpeechInteraction.org")+
theme(text=element_text(family="Roboto Condensed"),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_text(color="white",size=10),
axis.ticks.x = element_line(color="white",size=1),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
plot.background = element_rect(color="darkgrey",fill="black"),
plot.title = element_text(color="white",size=30),
legend.position = "left",
legend.text = element_text(color="white"),
legend.background = element_rect(color="darkgrey",fill="black"),
plot.caption = element_text(color="white")
)ragg::agg_png("w34_star_trek2.png",
res = 320, width = 14, height = 8, units = "in")
final2
dev.off()# read the image, attach the Tidytuesday logo and save it --------------------------
library(ggimage)
library(magick)
tidy_logo<-image_read("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/static/plot_logo.png") %>%
image_resize("300x300")
tidy_final <- image_read("w34_star_trek2.png")
attached_logo <- image_composite(tidy_final, tidy_logo,
operator="atop",
gravity="southwest")
image_write(attached_logo, path = "w34_star_trek2.png", format = "png") img <-image_read("white_startrek.png")
tidy_final2 <- image_read("w34_star_trek2.png")
attached_logo2 <- image_composite(tidy_final2, img,
operator="atop",
gravity="northeast")
image_write(attached_logo2, path = "w34_star_trek2.png", format = "png") library(tidymodels)
tidymodels_prefer()df %>% select(char,type,nv_resp) %>%
#mutate(nv_resp=factor(nv_resp)) %>%
recipe(char~.) %>%
step_dummy(all_nominal_predictors(),one_hot = TRUE)%>%
prep() %>%
bake(df) %>%
group_by(char,nv_resp) %>%
summarise_all(.funs = sum) %>%
ungroup() %>%
pivot_longer(cols=type_Alert:type_Wake.Word,names_to="type",values_to="values") %>%
mutate(type=gsub("^type_","",type)) %>%
group_by(char,nv_resp,type) %>%
summarize(tot=sum(values)) %>%
ungroup() %>%
ggplot() +
geom_mosaic(aes(x = product(type, char), fill = nv_resp)) +
#geom_text(aes(x=nv_resp,y=type,label=type))+
theme(
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
plot.background = element_blank(),
legend.position = "left"
)