My csv data looks like this:
heading1,heading2,heading3,heading4,heading5,value1_1,value2_1,value3_1,value4_1,value5_1,value1_2,value2_2,value3_2,val
Here's a JavaScript function that parses CSV data, accounting for commas found inside quotes.
// Parse a CSV row, accounting for commas inside quotes
function parse(row){
var insideQuote = false,
entries = [],
entry = [];
row.split('').forEach(function (character) {
if(character === '"') {
insideQuote = !insideQuote;
} else {
if(character == "," && !insideQuote) {
entries.push(entry.join(''));
entry = [];
} else {
entry.push(character);
}
}
});
entries.push(entry.join(''));
return entries;
}
Example use of the function to parse a CSV file that looks like this:
"foo, the column",bar
2,3
"4, the value",5
into arrays:
// csv could contain the content read from a csv file
var csv = '"foo, the column",bar\n2,3\n"4, the value",5',
// Split the input into lines
lines = csv.split('\n'),
// Extract column names from the first line
columnNamesLine = lines[0],
columnNames = parse(columnNamesLine),
// Extract data from subsequent lines
dataLines = lines.slice(1),
data = dataLines.map(parse);
// Prints ["foo, the column","bar"]
console.log(JSON.stringify(columnNames));
// Prints [["2","3"],["4, the value","5"]]
console.log(JSON.stringify(data));
Here's how you can transform the data into objects, like D3's csv parser (which is a solid third party solution):
var dataObjects = data.map(function (arr) {
var dataObject = {};
columnNames.forEach(function(columnName, i){
dataObject[columnName] = arr[i];
});
return dataObject;
});
// Prints [{"foo":"2","bar":"3"},{"foo":"4","bar":"5"}]
console.log(JSON.stringify(dataObjects));
Here's a working fiddle of this code.
Enjoy! --Curran
Actually you can use a light-weight library called any-text.
npm i -D any-text
var reader = require('any-text');
reader.getText(`path-to-file`).then(function (data) {
console.log(data);
});
or use async-await :
var reader = require('any-text');
const chai = require('chai');
const expect = chai.expect;
describe('file reader checks', () => {
it('check csv file content', async () => {
expect(
await reader.getText(`${process.cwd()}/test/files/dummy.csv`)
).to.contains('Lorem ipsum');
});
});
$(function() {
$("#upload").bind("click", function() {
var regex = /^([a-zA-Z0-9\s_\\.\-:])+(.csv|.xlsx)$/;
if (regex.test($("#fileUpload").val().toLowerCase())) {
if (typeof(FileReader) != "undefined") {
var reader = new FileReader();
reader.onload = function(e) {
var customers = new Array();
var rows = e.target.result.split("\r\n");
for (var i = 0; i < rows.length - 1; i++) {
var cells = rows[i].split(",");
if (cells[0] == "" || cells[0] == undefined) {
var s = customers[customers.length - 1];
s.Ord.push(cells[2]);
} else {
var dt = customers.find(x => x.Number === cells[0]);
if (dt == undefined) {
if (cells.length > 1) {
var customer = {};
customer.Number = cells[0];
customer.Name = cells[1];
customer.Ord = new Array();
customer.Ord.push(cells[2]);
customer.Point_ID = cells[3];
customer.Point_Name = cells[4];
customer.Point_Type = cells[5];
customer.Set_ORD = cells[6];
customers.push(customer);
}
} else {
var dtt = dt;
dtt.Ord.push(cells[2]);
}
}
}
I am using d3.js for parsing csv file. Very easy to use. Here is the docs.
Steps:
Using Es6;
import { csv } from 'd3-request';
import url from 'path/to/data.csv';
csv(url, function(err, data) {
console.log(data);
})
Please see docs for more.
Update - d3-request is deprecated. you can use d3-fetch
function CSVParse(csvFile)
{
this.rows = [];
var fieldRegEx = new RegExp('(?:\s*"((?:""|[^"])*)"\s*|\s*((?:""|[^",\r\n])*(?:""|[^"\s,\r\n]))?\s*)(,|[\r\n]+|$)', "g");
var row = [];
var currMatch = null;
while (currMatch = fieldRegEx.exec(this.csvFile))
{
row.push([currMatch[1], currMatch[2]].join('')); // concatenate with potential nulls
if (currMatch[3] != ',')
{
this.rows.push(row);
row = [];
}
if (currMatch[3].length == 0)
break;
}
}
I like to have the regex do as much as possible. This regex treats all items as either quoted or unquoted, followed by either a column delimiter, or a row delimiter. Or the end of text.
Which is why that last condition -- without it it would be an infinite loop since the pattern can match a zero length field (totally valid in csv). But since $ is a zero length assertion, it won't progress to a non match and end the loop.
And FYI, I had to make the second alternative exclude quotes surrounding the value; seems like it was executing before the first alternative on my javascript engine and considering the quotes as part of the unquoted value. I won't ask -- just got it to work.
If you want to solve this without using Ajax, use the FileReader() Web API.
Example implementation:
.csv
filefunction readSingleFile(e) {
var file = e.target.files[0];
if (!file) {
return;
}
var reader = new FileReader();
reader.onload = function(e) {
var contents = e.target.result;
displayContents(contents);
displayParsed(contents);
};
reader.readAsText(file);
}
function displayContents(contents) {
var element = document.getElementById('file-content');
element.textContent = contents;
}
function displayParsed(contents) {
const element = document.getElementById('file-parsed');
const json = contents.split(',');
element.textContent = JSON.stringify(json);
}
document.getElementById('file-input').addEventListener('change', readSingleFile, false);
<input type="file" id="file-input" />
<h3>Raw contents of the file:</h3>
<pre id="file-content">No data yet.</pre>
<h3>Parsed file contents:</h3>
<pre id="file-parsed">No data yet.</pre>