How to read data From *.CSV file using javascript?

Question

No need to write your own...

The jQuery-CSV library has a function called $.csv.toObjects(csv) that does the mapping automatically.

Note: The library is designed to handle any CSV data that is RFC 4180 compliant, including all of the nasty edge cases that most 'simple' solutions overlook.

Like @Blazemonger already stated, first you need to add line breaks to make the data valid CSV.

Using the following dataset:

heading1,heading2,heading3,heading4,heading5
value1_1,value2_1,value3_1,value4_1,value5_1
value1_2,value2_2,value3_2,value4_2,value5_2

Use the code:

var data = $.csv.toObjects(csv):

The output saved in 'data' will be:

[
  { heading1:"value1_1",heading2:"value2_1",heading3:"value3_1",heading4:"value4_1",heading5:"value5_1" } 
  { heading1:"value1_2",heading2:"value2_2",heading3:"value3_2",heading4:"value4_2",heading5:"value5_2" }
]

Note: Technically, the way you wrote the key-value mapping is invalid JavaScript. The objects containing the key-value pairs should be wrapped in brackets.

If you want to try it out for yourself, I suggest you take a look at the Basic Usage Demonstration under the 'toObjects()' tab.

Disclaimer: I'm the original author of jQuery-CSV.

Update:

Edited to use the dataset that the op provided and included a link to the demo where the data can be tested for validity.

Update2:

Due to the shuttering of Google Code. jquery-csv has moved to GitHub

NOTE: I concocted this solution before I was reminded about all the "special cases" that can occur in a valid CSV file, like escaped quotes. I'm leaving my answer for those who want something quick and dirty, but I recommend Evan's answer for accuracy.

---

This code will work when your data.txt file is one long string of comma-separated entries, with no newlines:

data.txt:

 heading1,heading2,heading3,heading4,heading5,value1_1,...,value5_2

javascript:

$(document).ready(function() {
    $.ajax({
        type: "GET",
        url: "data.txt",
        dataType: "text",
        success: function(data) {processData(data);}
     });
});

function processData(allText) {
    var record_num = 5;  // or however many elements there are in each row
    var allTextLines = allText.split(/\r\n|\n/);
    var entries = allTextLines[0].split(',');
    var lines = [];

    var headings = entries.splice(0,record_num);
    while (entries.length>0) {
        var tarr = [];
        for (var j=0; j<record_num; j++) {
            tarr.push(headings[j]+":"+entries.shift());
        }
        lines.push(tarr);
    }
    // alert(lines);
}

The following code will work on a "true" CSV file with linebreaks between each set of records:

data.txt:

heading1,heading2,heading3,heading4,heading5
value1_1,value2_1,value3_1,value4_1,value5_1
value1_2,value2_2,value3_2,value4_2,value5_2

javascript:

$(document).ready(function() {
    $.ajax({
        type: "GET",
        url: "data.txt",
        dataType: "text",
        success: function(data) {processData(data);}
     });
});

function processData(allText) {
    var allTextLines = allText.split(/\r\n|\n/);
    var headers = allTextLines[0].split(',');
    var lines = [];

    for (var i=1; i<allTextLines.length; i++) {
        var data = allTextLines[i].split(',');
        if (data.length == headers.length) {

            var tarr = [];
            for (var j=0; j<headers.length; j++) {
                tarr.push(headers[j]+":"+data[j]);
            }
            lines.push(tarr);
        }
    }
    // alert(lines);
}

http://jsfiddle.net/mblase75/dcqxr/

Don't split on commas -- it won't work for most CSV files, and this question has wayyyy too many views for the asker's kind of input data to apply to everyone. Parsing CSV is kind of scary since there's no truly official standard, and lots of delimited text writers don't consider edge cases.

This question is old, but I believe there's a better solution now that Papa Parse is available. It's a library I wrote, with help from contributors, that parses CSV text or files. It's the only JS library I know of that supports files gigabytes in size. It also handles malformed input gracefully.

1 GB file parsed in 1 minute:

(Update: With Papa Parse 4, the same file took only about 30 seconds in Firefox. Papa Parse 4 is now the fastest known CSV parser for the browser.)

Parsing text is very easy:

var data = Papa.parse(csvString);

Parsing files is also easy:

Papa.parse(file, {
    complete: function(results) {
        console.log(results);
    }
});

Streaming files is similar (here's an example that streams a remote file):

Papa.parse("http://example.com/bigfoo.csv", {
    download: true,
    step: function(row) {
        console.log("Row:", row.data);
    },
    complete: function() {
        console.log("All done!");
    }
});

If your web page locks up during parsing, Papa can use web workers to keep your web site reactive.

Papa can auto-detect delimiters and match values up with header columns, if a header row is present. It can also turn numeric values into actual number types. It appropriately parses line breaks and quotes and other weird situations, and even handles malformed input as robustly as possible. I've drawn on inspiration from existing libraries to make Papa, so props to other JS implementations.

I am using d3.js for parsing csv file. Very easy to use. Here is the docs.

Steps:

• npm install d3-request

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

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