Storyboard-commentaar
Laten we commentaar toevoegen op het tweede deel van het verhaal.
Deze oefening maakt deel uit van de cursus
Dashboards bouwen met flexdashboard
Oefeninstructies
- Maak van de twee opsommingstekens met tekst vóór de eerste grafiek commentaar op het tweede deel van het verhaal.
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"}