This vignette here demonstrates how to manually load data without using the {pixarfilms} package if you wish to explore and analyze this data elsewhere.
If for some reason, you don’t wish to install the package officially, you can also access the data by reading the data directly from GitHub using {readr}.
library(readr)
url <- "https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/pixar_films.csv"
pixar_films <- read_csv(url)
#> Rows: 27 Columns: 5
#> ── Column specification ────────────────────────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (2): film, film_rating
#> dbl (2): number, run_time
#> date (1): release_date
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
pixar_films
#> # A tibble: 27 × 5
#> number film release_date run_time film_rating
#> <dbl> <chr> <date> <dbl> <chr>
#> 1 1 Toy Story 1995-11-22 81 G
#> 2 2 A Bug's Life 1998-11-25 95 G
#> 3 3 Toy Story 2 1999-11-24 92 G
#> 4 4 Monsters, Inc. 2001-11-02 92 G
#> 5 5 Finding Nemo 2003-05-30 100 G
#> 6 6 The Incredibles 2004-11-05 115 PG
#> 7 7 Cars 2006-06-09 117 G
#> 8 8 Ratatouille 2007-06-29 111 G
#> 9 9 WALL-E 2008-06-27 98 G
#> 10 10 Up 2009-05-29 96 PG
#> # ℹ 17 more rows
Similarly, you can read the data directly
Here are the URL links you can use using the above methods.
https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/academy.csv
https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/box_office.csv
https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/genres.csv
https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/pixar_films.csv
https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/pixar_people.csv
https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/public_response.csv