讓 Dataframe 具備反應性
現在讓我們根據使用者輸入來改變 dataframe。
本練習屬於課程
使用 flexdashboard 建立儀表板
練習說明
- 建立一個名為
show_trips_df的 reactive「dataframe」，只包含使用者選取的起始時間範圍（包含端點）。請把這段程式碼放在和sliderInput()相同的程式區塊，讓結構更清楚。 - 執行文件並變更輸入。觀察會（或不會）發生什麼事。
動手互動練習
試著完成這個範例程式碼，體驗一下這個練習。
{"my_document.Rmd":"---\ntitle: \"Bike Shares Daily\"\noutput: \n flexdashboard::flex_dashboard:\n orientation: columns\n vertical_layout: fill\nruntime: shiny\n---\n\n```{r global, 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/course_6961/datasets/sanfran_bikeshare_joined_oneday.csv') %>%\n mutate(duration_min = duration_sec / 60,\n start_hour = hour(start_date)) %>%\n filter(duration_min <= 8 * 60) # remove trips longer than 8 hours as suspicious data quality\n\n```\n\n\n\nColumn {data-width=200 .sidebar}\n-----------------------------------------------------------------------\n\n```{r}\nsliderInput(\"start_slider\", \n label = \"Select trip start times to display (hour of day):\",\n min = 0, \n max = 24, \n value = c(7,10), \n step = 1)\n\nshow_trips_df <- ___({\n ___ %>%\n filter(start_hour >= ___ &\n start_hour <= ___)\n})\n```\n\nColumn {data-width=450}\n-----------------------------------------------------------------------\n### Origins\n\n```{r}\n\n trips_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 addCircles(radius = ~n)\n\n\n```\n\nColumn {data-width=350}\n-----------------------------------------------------------------------\n\n### Total Trips\n\n```{r}\n\nvalueBox(prettyNum(trips_df %>%\n nrow(), big.mark = ','), \n icon = 'fa-bicycle')\n\n\n```\n\n### Trips by Duration\n\n```{r}\n\ntrips_df %>%\n ggplot(aes(x = duration_min)) +\n theme_bw() +\n xlab('Trip Duration (min) \\n') +\n ylab('# trips') +\n geom_histogram() \n\n```\n\n\n"}