Interactive Plotting Quiz
This quiz is part of Algoritma Academy assessment process. Congratulations on completing the Interactive Plotting course! We will conduct an assessment quiz to test interactive plotting and building dashboard techniques you have learned on the course. The quiz is expected to be taken in the classroom, please contact our team of instructors if you missed the chance to take it in class.
Inspecting Dataset
We will be using a dataset of trending videos in Youtube stored in youtube.csv. The data consists of all trending videos in the United States from November 2017 to January 2018 with a total of 2986 observations and 9 variables. Please use the following glossary for reference:
trending_date: Video trending datetitle: Title of videochannel_title: Name of the Youtube channelcategory_id: Category of videopublish_time: Date the video was publishedviews: Number of video viewslikes: Number of video likesdislikes: Number of video dislikescomment_count: Number of video comment
Read the dataset into youtube object:
# Your code here
Say you are working as a trend analyst consultant for a Youtube channel. You tried to capture the top rating Youtube channels listed under Music category. The metrics you are using to rate each channel is the ratio between likes and views.
Take the top 10 Youtube channels based on the highest likes ratio by completing the code below:
youtube %>%
___(category_id == "Music") %>%
group_by(channel_title) %>%
___(likes_ratio = mean(likes/views)) %>%
___(desc(likes_ratio)) %>%
head(10)
- Which
dplyr functions is appropriate to fill in the code above?
- [ ] filter, summarise,arrange
- [ ] select, pivot, order
- [ ] filter, mutate, order
- [ ] select, summarise, arrange
Building Dashboard Application
Based on the youtube channels you have extracted, you are planning to create a dashboard prototype for your client using a flexdashboard. You created a mockup with the following design:
- To produce the layout using a flexdashboard templates, how should the layout be structured?
- [ ] orientation: rows ; 2 headers in first section, 1 headers in the second section
- [ ] orientation: columns ; 2 headers in first section, 1 headers in the second section
- [ ] orientation: columns ; 1 headers in first section, 2 headers in the second section
- [ ] orientation: rows ; 1 headers in first section, 2 headers in the second section
Now pay attention to the top right plot. The plot shows the likes and dislikes ratio between trending videos within the Music category. Say you’d like to add a shiny interactivity feature where users could pick their desired category and the plot would change accordingly.
- Which one from input type below is appropriate for the given type of selection?
- [ ] selectInput()
- [ ] sliderInput()
- [ ] numericInput()
- [ ] passwordInput()
You would also like to have the top right plot to be able to show each of the video’s title for further analysis. Since you realized that creating a geom_text could be overcrowded for the plot, you’re planning to render a plotly object that shows each video title for each hover action.
- Which of the following code is correctly paired between render and output in order to create plotly on the dashboard?
- [ ] output$plot1 <- renderPlot({}) ; plotlyOutput("plot1")
- [ ] output$plotly1 <- renderPlotly({}) ; plotOutput("plotly1")
- [ ] output$plot1 <- renderPlot({}) ; plotOutput("plot1")
- [ ] output$plot1 <- renderPlotly({}) ; plotlyOutput("plot1")