Let's make CSV's from row objects
I wanted to create an iterative CSV, one row at a time. But I also want ot add properties.
This module will make a CSV one row at a time. It will also modify the CSV header as it goes. Because it uses Node pipes and buffers, it can handle super large files.
npm install lets-make-csvs
const async = require('async')
let lmcsv = require("lets-make-csvs")
let csv = new lmcsv("test.csv")
let myobj = [{
"id": 1,
"first_name": "Hartley",
"last_name": "Mulvenna",
"email": "[email protected]",
"gender": "Male",
"ip_address": "6.25.240.135",
"hobbies": ["fishing", "camping", "hiking"]
}, {
"id": 2,
"first_name": "Antonio",
"last_name": "Pigne",
"email": "[email protected]",
"gender": "Male",
"ip_address": "102.234.210.24",
"hobbies": ["bowling", "music"],
"farm animals":{
"pigs":3,
"cows":{
"male":2,
"female":1
},
"horses":1
}
}, {
"id": 3,
"first_name": "Gamaliel",
"last_name": "Graser",
"email": "[email protected]",
"SAT score": 1420
}, {
"id": 4,
"first_name": "Celestyna",
"last_name": "Pawels",
"email": "[email protected]",
"gender": "Female",
"ip_address": "18.17.253.197",
"age": 22
}, {
"id": 5,
"first_name": "Mommy",
"last_name": "Caitlin",
"email": "[email protected]",
"gender": "Female",
"ip_address": "213.145.160.242"
}, {
"id": 6,
"first_name": "Nettle",
"last_name": "Mordey",
"email": "[email protected]",
"gender": "Female",
"ip_address": "178.58.2.233",
"occupation":"Engineer"
}]
async.eachSeries(myobj, function eachRow(row, cb) {
csv.writeRow(row, function(err) {
if (err) return cb(err)
return cb(null)
})
}, function endEachRow(err) {
if (err) throw err
console.log("done")
})
output:
"id","first_name","last_name","email","gender","ip_address","hobbies","activites","crimes","age"
"1","Hartley","Mulvenna","[email protected]","Male","6.25.240.135","["fishing","camping","hiking"]
"2","Antonio","Pigne","[email protected]","Male","102.234.210.24"," ","["bowling","crime"]
"3","Gamaliel","Graser","[email protected]","Male","32.18.140.241"," "," ","{"theft":"misdemeanor","treason":"felony","attempted murder":"misdemeanor"}
"4","Celestyna","Pawels","[email protected]","Female","18.17.253.197"," "," "," ","22"
"5","Mommy","Caitlin","[email protected]","Female","213.145.160.242"," "," "," "," "
"6","Nettle","Mordey","[email protected]","Female","178.58.2.233"," "," "," "," "
Open the result in your Excel or Google Sheets and you should see something like this:
id | first_name | last_name | gender | ip_address | hobbies | farm animals | SAT score | age | occupation | |
1 | Hartley | Mulvenna | [email protected] | Male | 6.25.240.135 | ["fishing","camping","hiking"] | ||||
2 | Antonio | Pigne | [email protected] | Male | 102.234.210.24 | ["bowling","music"] | {"pigs":3,"cows":{"male":2,"female":1},"horses":1} | |||
3 | Gamaliel | Graser | [email protected] | 1420 | ||||||
4 | Celestyna | Pawels | [email protected] | Female | 18.17.253.197 | 22 | ||||
5 | Mommy | Caitlin | [email protected] | Female | 213.145.160.242 | |||||
6 | Nettle | Mordey | [email protected] | Female | 178.58.2.233 | Engineer |
- Array method