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Static table

Let's imagine that your dashboard viewers need to see how many trips started and ended at each bikeshare station to manage balancing of bikes. We can provide this information in a simple table.

Deze oefening maakt deel uit van de cursus

Building Dashboards with flexdashboard

Cursus bekijken

Oefeninstructies

  • Add a table in the Station Usage chart that contains the data in station_trips_df, using the kable() function.
  • Knit and expand the HTML viewer to explore the resulting table. Try scrolling down.

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"}
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