Danfo.js
  • Danfo.js Documentation
  • Getting Started
  • API reference
    • General Functions
      • danfo.tensorflow
      • danfo. convertFunctionTotransformer
      • danfo.streamCsvTransformer
      • danfo.streamJSON
      • danfo.streamCSV
      • danfo.Utils
      • danfo.Str
      • danfo.Dt
      • danfo.dateRange
      • danfo.OneHotEncoder
      • danfo.StandardScaler
      • danfo.MinMaxScaler
      • danfo.LabelEncoder
      • danfo.toDateTime
      • danfo.getDummies
      • danfo.concat
      • danfo.merge
    • Input/Output
      • danfo.readExcel
      • danfo.toExcel
      • danfo.readJSON
      • danfo.toJSON
      • danfo.readCSV
      • danfo.toCSV
    • Series
      • Creating a Series
      • Series.append
      • Series.cumSum
      • Series.cumMax
      • Series.cumProd
      • Series.cumMin
      • Series.str.split
      • Series.str.len
      • Series.str.join
      • Series.str.trim
      • Series.str.substring
      • Series.str.substr
      • Series.str.slice
      • Series.str.search
      • Series.str.repeat
      • Series.str.replace
      • Series.str.lastIndexOf
      • Series.str.indexOf
      • Series.str.includes
      • Series.str.endsWith
      • Series.str.startsWith
      • Series.str.concat
      • Series.str.charAt
      • Series.str.toUpperCase
      • Series.str.toLowerCase
      • Series.str.capitalize
      • Series.dt.seconds
      • Series.dt.minutes
      • Series.dt.dayOfMonth
      • Series.dt.monthName
      • Series.dt.hours
      • Series.dt.dayOfWeek
      • Series.dt.dayOfWeek
      • Series.dt.month
      • Series.dt.year
      • Series.argMax
      • Series.argMin
      • Series.argSort
      • Series.replace
      • Series.isNa
      • Series.fillNa
      • Series.dropNa
      • Series.dropDuplicates
      • Series.valueCounts
      • Series.nUnique
      • Series.unique
      • Series.abs
      • Series.ne
      • Series.eq
      • Series.ge
      • Series.le
      • Series.gt
      • Series.lt
      • Series.iloc
      • Series.loc
      • Series.at
      • Series.iat
      • Series.ndim
      • Series.shape
      • Series.dtype
      • Series.values
      • Series.tensor
      • Series.index
      • Series.apply
      • Series.map
      • Series.setIndex
      • Series.resetIndex
      • Series.describe
      • Series.copy
      • Series.sortValues
      • Series.var
      • Series.std
      • Series.round
      • Series.minimum
      • Series.maximum
      • Series.count
      • Series.sum
      • Series.max
      • Series.min
      • Series.mode
      • Series.median
      • Series.mean
      • Series.mod
      • Series.pow
      • Series.div
      • Series.mul
      • Series.sub
      • Series.add
      • Series.sample
      • Series.tail
      • Series.head
      • Series.and
      • Series.or
    • Dataframe
      • Creating a DataFrame
      • DataFrame.sortIndex
      • DataFrame.append
      • DataFrame.nUnique
      • DataFrame.tensor
      • DataFrame.print
      • DataFrame.toCSV
      • DataFrame.toJSON
      • DataFrame.toExcel
      • DataFrame.sortValues
      • DataFrame.setIndex
      • DataFrame.resetIndex
      • DataFrame.rename
      • DataFrame.drop
      • DataFrame.asType
      • DataFrame.shape
      • DataFrame.axis
      • DataFrame.ndim
      • DataFrame.values
      • DataFrame.selectDtypes
      • DataFrame.ctypes
      • DataFrame.index
      • DataFrame.loc
      • DataFrame.iloc
      • DataFrame.at
      • DataFrame.iat
      • DataFrame.head
      • DataFrame.tail
      • DataFrame.sample
      • DataFrame.add
      • DataFrame.sub
      • DataFrame.mul
      • DataFrame.div
      • DataFrame.pow
      • DataFrame.mod
      • DataFrame.mean
      • DataFrame.median
      • DataFrame.min
      • DataFrame.max
      • DataFrame.std
      • DataFrame.var
      • DataFrame.count
      • DataFrame.round
      • DataFrame.cumSum
      • DataFrame.cumMin
      • DataFrame.cumMax
      • DataFrame.cumProd
      • DataFrame.copy
      • DataFrame.describe
      • DataFrame.sum
      • DataFrame.abs
      • DataFrame.query
      • DataFrame.addColumn
      • DataFrame.groupby
      • DataFrame.column
      • DataFrame.fillNa
      • DataFrame.isNa
      • DataFrame.dropNa
      • DataFrame.apply
      • DataFrame.applyMap
      • DataFrame.It
      • DataFrame.gt
      • DataFrame.le
      • DataFrame.ge
      • DataFrame.ne
      • DataFrame.eq
      • DataFrame.replace
    • Configuration Options
    • Plotting
      • Timeseries Plots
      • Violin Plots
      • Box Plots
      • Tables
      • Pie Charts
      • Histograms
      • Scatter Plots
      • Bar Charts
      • Line Charts
      • Customizing your plots
    • Groupby
      • Groupby.getGroups
      • Groupby.col
      • Groupby.max
      • Groupby.min
      • Groupby.sum
      • Groupby.mean
      • Groupby.std
      • Groupby.var
      • Groupby.count
      • Groupby.cumSum
      • Groupby.cumMax
      • Groupby.cumMin
      • Groupby.cumProd
      • Groupby.agg
  • User Guides
    • Migrating to the stable version of Danfo.js
    • Using Danfojs in React
    • Titanic Survival Prediction using Danfo.js and Tensorflow.js
  • Building Data Driven Applications with Danfo.js - Book
  • Contributing Guide
  • Release Notes
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On this page
  • Convert DataFrame/Series to JSON and return value
  • Convert DataFrame/Series to JSON and write to file path
  • Convert DataFrame/Series to JSON and download file in browser

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  1. API reference
  2. Input/Output

danfo.toJSON

danfo.toJSON(data, options)

Parameters

Type

Description

Default

data

Series or DataFrame

The Series or DataFrame to write to CSV

options

object, optional

Configuration object:

{

filePath: Local file path to write the CSV file to. If not specified, the CSV will be returned as a string. Only needed in Nodejs version fileName: The name of the file to download as. Only needed in browser environment. format: The format of the JSON. Can be one of row or column.

}

{ format: "column" }

The toJSON function can be used to write out a DataFrame or Series to JSON format/file. The output is configurable and will depend on the environment. In the following examples, we show you how to write/download a JSON file from Node and Browser environments.

Convert DataFrame/Series to JSON and return value

const dfd = require("danfojs-node")

let data = {
  Abs: [20.2, 30, 47.3],
  Count: [34, 4, 5],
  "country code": ["NG", "FR", "GH"],
};

let df = new dfd.DataFrame(data);

const jsonObj = dfd.toJSON(df); //column format
console.log(jsonObj);

//output
[
  { Abs: 20.2, Count: 34, 'country code': 'NG' },
  { Abs: 30, Count: 4, 'country code': 'FR' },
  { Abs: 47.3, Count: 5, 'country code': 'GH' }
]

//row format
const jsonObj = dfd.toJSON(df, {
    format: "row"
});

console.log(jsonObj);
//output
{
  Abs: [ 20.2, 30, 47.3 ],
  Count: [ 34, 4, 5 ],
  'country code': [ 'NG', 'FR', 'GH' ]
}
<!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/danfojs@1.2.0/lib/bundle.min.js"></script>
    <title>Document</title>
</head>

<body>

    <script>

       let data = {
          Abs: [20.2, 30, 47.3],
          Count: [34, 4, 5],
          "country code": ["NG", "FR", "GH"],
        };
        
        let df = new dfd.DataFrame(data);
        
        const csv = df.toJSON();
        console.log(csv);
    </script>
</body>

</html>

Convert DataFrame/Series to JSON and write to file path

Writing a DataFrame/Series as JSON, to a local file path is only supported in the Nodejs environment

const dfd = require("danfojs-node")

let data = {
    Abs: [20.2, 30, 47.3],
    Count: [34, 4, 5],
    "country code": ["NG", "FR", "GH"],
};

let df = new dfd.DataFrame(data);

dfd.toJSON(df, { filePath: "./testOutput.json" });

Convert DataFrame/Series to JSON and download file in browser

You can automatically convert and download a DataFrame/Series as a JSON file in a browser environment, by specifying a fileName and setting download to true.

let data = {
    Abs: [20.2, 30, 47.3],
    Count: [34, 4, 5],
    "country code": ["NG", "FR", "GH"],
};

let df = new dfd.DataFrame(data);

dfd.toJSON(df, { fileName: "test_out.json", download: true });
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