danfo.readCSV
Reads a comma-separated values (CSV) file into DataFrame. Also supports the reading of CSV files in chunks.
danfo.readCSV(source, options)
Parameters
Type
Description
Default
source
File object, File path, URL
Any valid string path is acceptable. The string could be a URL or a valid local file path.
A browser input file object is also supported.
options
object, optional
Supports all Papaparse config parameters. See https://www.papaparse.com/docs#config.
{
header: true
}
The readCSV method can read a CSV file from a local disk, or over the internet (URL). Reading of local files is only supported in Nodejs, while reading of input file objects is only supported in the browser.
Reading files from local disk
By specifying a valid file path, you can load CSV files from local disk:
const dfd = require("danfojs-node")
dfd.readCSV("./user_names.csv") //assumes file is in CWD
.then(df => {
df.head().print()
}).catch(err=>{
console.log(err);
})Reading files from a URL
By specifying a valid URL, you can load CSV files from any location into Danfo**'**s data structure:
const dfd = require("danfojs-node")
dfd.readCSV("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv") //assumes file is in CWD
.then(df => {
df.head().print()
}).catch(err=>{
console.log(err);
})Reading an input file object in the browser
By specifying a valid file object, you can load CSV files in the browser in DataFrames/Series
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<script src="https://cdn.jsdelivr.net/npm/[email protected]/lib/bundle.min.js"></script>
<title>Document</title>
</head>
<body>
<input type="file" id="file" name="file">
<script>
inputFile.addEventListener("change", async () => {
const csvFile = inputFile.files[0]
dfd.readCSV(csvFile).then((df) => {
df.print()
})
})
</script>
</body>
</html>Last updated
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