Web-friendly table
Now let's make the table in the last example more web-friendly.
Deze oefening maakt deel uit van de cursus
Building Dashboards with flexdashboard
Oefeninstructies
- Add a table in the Station Usage chart that contains the data in
station_trips_df, using thedatatable()function. - Knit and expand the HTML viewer to explore the resulting table. Try sorting on the Gap column, searching for all the Caltrain stations, and going from page to page.
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---\n\n```{r setup, include=FALSE}\nlibrary(flexdashboard)\nlibrary(readr)\nlibrary(tidyverse)\nlibrary(lubridate)\nlibrary(plotly)\nlibrary(knitr)\nlibrary(DT)\n\ntrips_df <- read_csv('https://assets.datacamp.com/production/course_6355/datasets/sanfran_bikeshare_joined_oneday.csv')\n```\n\nColumn {data-width=650}\n-----------------------------------------------------------------------\n\n### Station Usage\n\n```{r}\n\nstation_trips_df <- trips_df %>%\n select(start_station_name, end_station_name) %>%\n pivot_longer(cols = start_station_name:end_station_name, names_to = 'Type', values_to = 'Station') %>%\n group_by(Station, Type) %>%\n summarize(n_trips = n()) %>% \n mutate(Type = ifelse(Type == 'start_station_name', 'Trip Starts', 'Trip Ends')) %>%\n pivot_wider(names_from = 'Type', values_from = 'n_trips') %>%\n replace_na(list(`Trip Starts` = 0, `Trip Ends` = 0)) %>%\n mutate(Gap = `Trip Ends` - `Trip Starts`)\n\n```\n\n\nColumn {data-width=350}\n-----------------------------------------------------------------------\n\n### Median Trip Length\n\n\n### % Short Trips\n\n\n### Trips by Start Time\n\n\n"}