---
title: "Manually Load pixarfilms Data"
description: |
  Shows how to load pixarfilms data in R and Python.
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Manually Load pixarfilms Data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

## Overview

This vignette here demonstrates how to manually load data without using the
{pixarfilms} package if you wish to explore and analyze this data elsewhere.




## Loading within R

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}.


```r
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.
```


```r
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
```


## Loading within Python and pandas

Similarly, you can read the data directly


```python
import pandas as pd
#> ModuleNotFoundError: No module named 'pandas'

url = "https://raw.githubusercontent.com/erictleung/pixarfilms/main/data-raw/pixar_films.csv"
pixar_films = pd.read_csv(url)
#> NameError: name 'pd' is not defined
```


```python
pixar_films.head()
#> NameError: name 'pixar_films' is not defined
```


## Data links

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
```
