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Web-friendly table

Now let's make the table in the last example more web-friendly.

Bu egzersiz

Building Dashboards with flexdashboard

kursunun bir parçasıdır
Kursu Görüntüle

Egzersiz talimatları

  • Add a table in the Station Usage chart that contains the data in station_trips_df, using the datatable() 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.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

{"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"}
Kodu Düzenle ve Çalıştır