Get month-over-month comparisons in R

The video tutorial explains how to use R for month-over-month and year-over-year data analysis. It covers importing data, preparing it for analysis, and calculating changes using the dplyr package. The tutorial also demonstrates handling multiple categories, graphing data with ggplot2, and filtering data for reports. Additionally, it introduces weekly reporting techniques using the LABRIDAE package and shows how to create R Studio code snippets for automation.

What is one advantage of using R for month-over-month calculations compared to spreadsheets?

• R provides more accurate results than spreadsheets.

• R is faster than any spreadsheet software.

• R automatically updates data without manual input.

• R eliminates the need to manually drag formulas across cells.

Which R package is used to perform group by and summarize operations?

• ggplot2

• dplyr

• tidyr

• stringr

What function in dplyr is used to compare data with previous values?

• lag

• filter

• lead

• mutate

How can you modify the R code to handle multiple categories in your data?

• By grouping data by category in addition to time period.

• By using the mutate function to add new columns.

• By using the filter function to separate categories.

• By creating separate data frames for each category.

Which R package is mentioned for creating visualizations of the data?

• ggplot2

• plotly

• shiny

• lattice

What is the purpose of the LABRIDAE package in weekly data analysis?

• To perform statistical tests on weekly data.

• To visualize weekly trends in data.

• To manipulate date formats for weekly reporting.

• To automate the generation of weekly reports.

How can RStudio code snippets help in generating reports?

• They ensure data accuracy by validating inputs.

• They provide a graphical interface for report generation.

• They automate repetitive coding tasks, saving time.

• They offer built-in templates for all types of reports.