Web-friendly table
Now let's make the table in the last example more web-friendly.
Diese Übung ist Teil des Kurses
Building Dashboards with flexdashboard
Anleitung zur Übung
- 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.
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---\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"}