Aan de slagBegin gratis

Storyboard-commentaar

Laten we commentaar toevoegen op het tweede deel van het verhaal.

Deze oefening maakt deel uit van de cursus

Dashboards bouwen met flexdashboard

Bekijk cursus

Oefeninstructies

  • Maak van de twee opsommingstekens met tekst vóór de eerste grafiek commentaar op het tweede deel van het verhaal.

Interactieve oefening met praktijkervaring

Probeer deze oefening door deze voorbeeldcode aan te vullen.

{"my_document.Rmd":"---\ntitle: \"Bike Shares Daily\"\noutput: \n  flexdashboard::flex_dashboard:\n    orientation: columns\n    vertical_layout: fill\n    storyboard: true\n---\n\n```{r setup, include=FALSE}\nlibrary(flexdashboard)\nlibrary(readr)\nlibrary(leaflet)\nlibrary(DT)\nlibrary(tidyverse)\nlibrary(lubridate)\nlibrary(plotly)\n\ntrips_df <- read_csv('https://assets.datacamp.com/production/repositories/1448/datasets/1f12031000b09ad096880bceb61f6ca2fd95e2eb/sanfran_bikeshare_joined_oneday.csv')\n```\n\n* Bike `r most_used_bike_df$bike_number[1]` made its first trip from `r most_used_bike_df$start_station_name[1]` and ended its day at `r most_used_bike_df$end_station_name[nrow(most_used_bike_df)]`.\n* Its longest trip was `r max(most_used_bike_df$duration_sec)/60` minutes long.\n\n### Most bikes are used only a few times, but a few are used a lot\n\n```{r}\n\ntrips_per_bike_df <- trips_df %>%\n  group_by(bike_number) %>%\n  summarize(n_trips = n()) %>%\n  arrange(desc(n_trips)) \n\nbike_plot <- trips_per_bike_df %>%\n  ggplot(aes(x = n_trips)) +\n  geom_histogram(binwidth = 1) +\n  ylab('') +\n  xlab('Trips per bike') \n\nggplotly(bike_plot)\n\n```\n\n### Where did the most used bike go?\n\n```{r}\n\nmost_used_bike_df <- trips_df %>%\n  filter(bike_number == trips_per_bike_df$bike_number[1])\n\nmost_used_bike_df %>%\n  rename(latitude = start_latitude,\n         longitude = start_longitude) %>%\n  group_by(start_station_id, latitude, longitude) %>%\n  count() %>%\n  leaflet() %>%\n  addTiles() %>%\n  addMarkers()\n\n```\n\n\n"}
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