Storyboard Commentary
Let's add commentary on the second part of the story.
Diese Übung ist Teil des Kurses
Building Dashboards with flexdashboard
Anleitung zur Übung
- Make the two bullet points of text before the first chart commentary on the second part of the story.
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
{"my_document.Rmd":"---\ntitle: \"Bike Shares Daily\"\noutput: \n flexdashboard::flex_dashboard:\n orientation: columns\n vertical_layout: fill\n storyboard: true\n---\n\n```{r setup, include=FALSE}\nlibrary(flexdashboard)\nlibrary(readr)\nlibrary(leaflet)\nlibrary(DT)\nlibrary(tidyverse)\nlibrary(lubridate)\nlibrary(plotly)\n\ntrips_df <- read_csv('https://assets.datacamp.com/production/repositories/1448/datasets/1f12031000b09ad096880bceb61f6ca2fd95e2eb/sanfran_bikeshare_joined_oneday.csv')\n```\n\n* Bike `r most_used_bike_df$bike_number[1]` made its first trip from `r most_used_bike_df$start_station_name[1]` and ended its day at `r most_used_bike_df$end_station_name[nrow(most_used_bike_df)]`.\n* Its longest trip was `r max(most_used_bike_df$duration_sec)/60` minutes long.\n\n### Most bikes are used only a few times, but a few are used a lot\n\n```{r}\n\ntrips_per_bike_df <- trips_df %>%\n group_by(bike_number) %>%\n summarize(n_trips = n()) %>%\n arrange(desc(n_trips)) \n\nbike_plot <- trips_per_bike_df %>%\n ggplot(aes(x = n_trips)) +\n geom_histogram(binwidth = 1) +\n ylab('') +\n xlab('Trips per bike') \n\nggplotly(bike_plot)\n\n```\n\n### Where did the most used bike go?\n\n```{r}\n\nmost_used_bike_df <- trips_df %>%\n filter(bike_number == trips_per_bike_df$bike_number[1])\n\nmost_used_bike_df %>%\n rename(latitude = start_latitude,\n longitude = start_longitude) %>%\n group_by(start_station_id, latitude, longitude) %>%\n count() %>%\n leaflet() %>%\n addTiles() %>%\n addMarkers()\n\n```\n\n\n"}