There's a feature in the csvtojson package where you can create a nested JSON object from a CSV file permitting you configure the headers correctly. However, I'm having difficulty applying the schema shown in the above link for my CSV file.
My current CSV structure is this:
And the JSON structure I'm trying to create should look something like this:
{
Name: 'Bedminster Twp East',
Contests: [
{
Name: 'JUSTICE OF THE SUPREME COURT',
Candidates: [
{
Name: 'Maria McLaughlin',
Votes: 511
},
{
Name: 'Kevin Brobson',
Votes: 857
},
{
Name: 'Write-In',
Votes: 1
},
]
},
{
Name: 'JUDGE OF THE SUPERIOR COURT',
Candidates: [
{
Name: 'Timika Lane',
Votes: 494
},
{
Name: 'Megan Sullivan',
Votes: 870
},
{
Name: 'Write-In',
Votes: 1
},
]
}
...
],
Turnout: '45.77%'
},
...
This is the existing code I have:
const csv = require('csvtojson');
const axios = require('axios');
axios({
method: 'get',
url: 'URL'
}).then(function(response) {
let x = response.data.split('\n');
x.splice(0, 2);
let newX = x.join('\n');
csv({
noheader: false,
headers: ['Precinct.Name', 'Precinct.Contests.Name', 'Precinct.Contests.Name.Candidates.Name', 'Precinct.Contests.Name.Candidates.Votes', 'Precinct.Turnout']
}).fromString(newX).then((csvRow) => {
console.log(csvRow);
});
});
Which is unfortunately creating the following JSON structure:
[
{
Precinct: {
Name: 'Bedminster Twp East',
Contests: [Object],
Turnout: '47.89%'
}
},
{
Precinct: {
Name: 'Bedminster Twp East',
Contests: [Object],
Turnout: '47.89%'
}
},
{
Precinct: {
Name: 'Bedminster Twp East',
Contests: [Object],
Turnout: '47.89%'
}
},
{
Precinct: {
Name: 'Bedminster Twp East',
Contests: [Object],
Turnout: '47.89%'
}
},
... 19841 more items
I don't know exactly what is in the "Contests" object, but considering that the number of objects is equal to the number of rows in the existing CSV file, I believe there is something wrong with my header grouping. I can't tell if I'm severely misreading the documentation linked earlier or if it's not clear enough. Thanks for any assistance.
EDIT: I'm splitting and joining because the first two rows are metadata that says "UNOFFICIAL RESULTS" and "2022", which I don't want being read in.
