Pre- Coding Approach
For my assignment for 2A. I decided to carry out and organize 6 popular movies from the recent year to see what everyone thought of them. The movie I plan to choose are KPDH, Sinners, Avatar:Way of Fire, Captain America, New Avengers & Zootopia2. I do not keep up with movies that often.
After that I intend to use separate values by which rating is addressed by what movie. I will clean the missing value by putting a replacement fill value which should be the summary of the prior score in the category. As an example. if the average of the other 4 scorers rate a move 3.5 than the 5 score will be a 3.5 as well. I will convert the cleaned data into postgre SQL.
After organizing the data, I will load it as a tidyverse dataframe and finalize my summary.
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 4.0.0 ✔ tibble 3.2.1
✔ lubridate 1.9.4 ✔ tidyr 1.3.1
✔ purrr 1.0.4
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors