danfo.read_csv

Reads a comma-separated values (CSV) file into DataFrame. Also supports iterating or breaking of file into chunks.

danfo.read_csv(source, chunk) [source]
Parameters
Type
Description
Default
source:
str, path or URL 
Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, gs, and file. For local file path, it should be prefixed with " file://", for example, "file:///home/path/to/table.csv".
​
chunk:
 int, optional
The number of rows of file to read. Useful for reading pieces of large files.
​
Returns:
     Promise. Resolves to DataFrame
Example
The read_csv method can read csv file from local disk, or over the internet. If the file is to be read from a local disk in Node environment, you have to prefix the full path name with a "file://" prefix. For instance, to read a csv file at the path /home/Desktop/user_names.csv, you can do the following:
Node.js
Browser
Node.js
const dfd = require("danfojs-node")
​
dfd.read_csv("file:///home/Desktop/user_names.csv")
  .then(df => {
  
   df.head().print()
​
  }).catch(err=>{
     console.log(err);
  })
Browser
<!DOCTYPE html>
<html lang="en">
​
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <!--danfojs CDN -->
    <script src="https://cdn.jsdelivr.net/gh/opensource9ja/danfojs@latest/lib/bundle.js"></script>
    <title>Document</title>
</head>
​
<body>
​
    <div id="plot_div"></div>
    <script>
​
         dfd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
            .then(df => {
​
                //do something like display descriptive statistics
                df.describe().print()
                
            }).catch(err => {
                console.log(err);
            })
         
    </script>
</body>
​
</html>
​
Reading Large Files
For extremely large files, that cannot be fit in memory at once, you can read the top portion in chunks. For instance, this dataset has over 1.5 million rows and will throw a memory error if you try to load everything at once. To read these type of files, you can load them in chunks using the chunks parameter in read_csv
JavaScript
Browser
JavaScript
const dfd = require("danfojs-node")
​
//read the first 10000 rows
dfd.read_csv("file:///home/Desktop/bigdata.csv", chunk=10000)
  .then(df => {
  
   df.tail().print()
​
  }).catch(err=>{
      console.log(err);
  })
Browser
​

danfo.read_json

Series

Last updated 1 month ago

Parameters	Type	Description	Default
source:	str, path or URL	Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, gs, and file. For local file path, it should be prefixed with " file://", for example, "file:///home/path/to/table.csv".
chunk:	int, optional	The number of rows of file to read. Useful for reading pieces of large files.