Published
Edited
Jul 16, 2020
1 fork
44 stars
kw = require('https://bundle.run/kiwis@0.0.7')
h2g2Characters = kw.DataFrame([
{
name: 'Marvin',
surname: '',
occupation: 'Paranoid Android'
},
{
name: 'Zaphod',
surname: 'Beeblebrox',
occupation: 'President of the Galaxy'
},
{
name: 'Arthur',
surname: 'Dent',
occupation: null
}
])
h2g2Characters.toString()
h2g2Characters.columns
h2g2Characters.length
h2g2Characters.get(1)
h2g2Characters.first()
h2g2Characters.last()
h2g2Characters.name.toString()
h2g2Characters.toArray()
oscars = kw.parseCSV(await FileAttachment('oscar_results@1.csv').text(), { prettify: 'camelCase' })
oscars.toString()
// Get the min and max values for the year
oscars.year.extent()
// Get the average box office
oscars.boxOffice.mean()
// Get the different categories
oscars.category.unique()
// Get the 20 movies with the most nominations ("A Star Is Born" is cheating cause there are two of them!)
oscars.title.counts().slice(0, 20)
// Get the 20 movies with the most wins
oscars.filter(row => row.winner === 'true').title.counts().slice(0, 20)
// Only show Sci-Fi movies that won an Oscar
oscars.filter(row => row.genres.includes('Sci-Fi') && row.winner === 'true').toString()
// Only show movies that won Best Picture and were the biggest commercial success of the year (1st at the box office)
oscars.filter(row => row.category === 'Best Picture' && row.winner === 'true' && row.rank === 1).toString()
// Exclude 'Best Visual Effects' from the dataset and only keep a subset of the columns, renaming and reordering them
oscars
.drop(row => row.category === 'Best Visual Effects')
.filter(['year', 'title', 'category', 'winner'])
.rename({ title: 'name', category: 'award' })
.reorder(['name', 'year', 'award', 'winner'])
.toString()
oscars.sort(['year', 'boxOffice']).toString()
pivotTable = oscars.pivot(['category', 'year'])
JSON.parse(pivotTable.toJSON())
// Show the number of films nominated for each category and ceremony
pivotTable.count().toString()
// Show the average box office of the nominees for each category and ceremony
pivotTable.mean('boxOffice').toString()
// Show the winner for each category and ceremony, but remove the rows where the winner is missing
pivotTable
.rollup(l => {
const winner = l.find(row => row.winner === 'true');
return winner ? winner.title : null;
}, { name: 'winner' })
.dropNA()
.toString()
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