Storyboard Commentary
Let's add commentary on the second part of the story.
Deze oefening maakt deel uit van de cursus
Building Dashboards with flexdashboard
Oefeninstructies
- Make the two bullet points of text before the first chart commentary on the second part of the story.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
{"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"}