sample_page.md

Netflix Activity Dashboard

As an avid Tableau user, I was always curious why data analysts/scientists prefer ‘scripting’ their data visualizations which requires more practical time and effort to learn. For that, I’ve decided to experience it myself and built my first R Shiny web app using the 'flexdashboard' framework - presenting insights of my Netflix viewing history!

1. Suggest hypotheses about the causes of observed phenomena

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# import packages
library(tidyverse) # data manipulation & visualizations
library(gridExtra) # to plot multiple ggplot objects
library(scales)
library(lubridate) # date formatting
library(readxl) # importing excel files 
library(readr)
library(zoo)
library(reshape2)
library(kableExtra) # table formatting
library(flexdashboard) # dashboard framework
library(htmlwidgets)
library(DT)
library(shiny) # dashboard framework - web application
library(plotly) # to build interactive plots
library(viridisLite)
library(rvest) # webscraping
library(bslib)
library(shinyWidgets)

2. Assess assumptions on which statistical inference will be based

if (isAwesome){
  return true
}

3. Support the selection of appropriate statistical tools and techniques

4. Provide a basis for further data collection through surveys or experiments

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