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Storyboard-kommentarer

Nu ska vi lägga till kommentarer till den andra delen av berättelsen.

Den här övningen är en del av kursen

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Övningsinstruktioner

  • Gör de två punkterna med text före det första diagrammet till kommentarer om den andra delen av berättelsen.

Interaktiv övning med praktiskt arbete

Testa den här övningen genom att slutföra den här exempelkoden.

{"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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