This demo app demonstrates how it is possible to combine the best of modern R 📦 packages to create interactive web applications at zero cost and without HTML, CSS, or JavaScript knowledge.
Based on search term, the app takes data from google trends and shows results about Italy or US depending on the user selection.
These are the two main pages:
Dashboard
- Trends over the time and forecasting
- Interest by city (top ten)
- Regional Interest
Download Forecast Data
- Google trends Italy
- Added google trends US
- Added Download Forecast Data
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✨
{Shiny}provides an elegant and powerful web framework for building web applications using R. -
📊
{highcharter}is a rich R interface to the popular Highcharts JavaScript graphics library. -
💻
{flexdashboard}helps construct flexible, attractive, interactive dashboards. -
🔧
{dplyr}contains a set of functions (or “verbs”) that perform common data manipulation operations such as filtering for rows, selecting specific columns, re-ordering rows, adding new columns and summarizing data. -
🔮
{forecast}contains function for automatic forecasting determining an appropriate time series model, estimate the parameters and compute the forecasts. -
📑
{stringr}contains functions for manipulating strings in R. -
📅
{lubridate}facilitates working with dates and times. -
📈
{gtrendsR}provides an interface for retrieving and displaying Google Trends information. -
📝
{DT}provides a R interface to the JavaScript library DataTables. R data objects (matrices or data frames) can be displayed as tables on HTML pages, and DataTables provides filtering, pagination, sorting, and many other features in the tables.
- 📄 1 file
- 🕚 1 day of work (starting from tutorials of one of my courses)
- ✍ 200 lines of code
- 🚿 30 %>% pipe
- 🤹 100% fun