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Web-friendly table

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

Cet exercice fait partie du cours

Building Dashboards with flexdashboard

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Instructions

  • 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.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

{"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"}
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