Let's do a quick #dailycoding exercise.
#rstudioconf2020 is on and few of us, unlucky ones, are tracking it on Twitter. :-(
Let's try to make things a little more exciting and track the progress with some code.
Get the data
## load rtweet package library(rtweet) ## search for 18000 tweets using the rstudioconf2020 hashtag rt <- search_tweets( "#rstudioconf2020", n = 18000, include_rts = FALSE ) tweets <- rt
How is the vibe?
## plot time series of tweets rt %>% ts_plot("3 hours") + ggplot2::theme_minimal() + ggplot2::theme(plot.title = ggplot2::element_text(face = "bold")) + ggplot2::labs( x = NULL, y = NULL, title = "Frequency of #rstudioconf2020 Twitter statuses from past 9 days", subtitle = "Twitter status (tweet) counts aggregated using three-hour intervals", caption = "\nSource: Data collected from Twitter's REST API via rtweet" )
Its getting active!
Where are they tweeting from?
tweets %>% filter(!is.na(place_full_name)) %>% count(place_full_name, sort = TRUE) %>% top_n(5) %>% View
I like the guy in this Tesla :-)
library(dplyr) library(plotly) table_tweet <- data.frame(head(sort(table(tweets$source),decreasing=T),20)) ggplot(table_tweet, aes(x=Var1, y=Freq)) + geom_segment( aes(x=Var1, xend=Var1, y=0, yend=Freq)) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) + labs(title = "Tweets by device/source", x="Device/Source",y="Frequency")+ geom_point( size=5, color="red", fill=alpha("orange", 0.3), alpha=0.7, shape=21, stroke=2)
Yup! iPhones rock! I'm thinking of shifting to Android now though :)