Creating a Series

danfo.Series(data, options)

Parameters	Type	Description
data	1D Array, 1D Tensor, JSON object.	Flat data structure to load into DataFrame
options	Object	Optional configuration object. Supported properties are: index: Array of numeric or string names for subseting array. If not specified, indexes are auto-generated. dtypes: Array of data types for each the column. If not specified, dtypes are/is inferred. config: General configuration object for extending or setting NDframe behavior. See full options here

Parameters

Type

Description

data

1D Array, 1D Tensor, JSON object.

Flat data structure to load into DataFrame

options

Object

Optional configuration object. Supported properties are:

index: Array of numeric or string names for subseting array. If not specified, indexes are auto-generated.

dtypes: Array of data types for each the column. If not specified, dtypes are/is inferred.

config: General configuration object for extending or setting NDframe behavior. See full options here

In order to create a Series, you need to call the new Keyword and pass a flat data structure. In the following examples, we show you how to create a Series by specifying different config options.

Creating a Series from an object:

const dfd = require("danfojs-node")

obj_data = { 'B': ["bval1", "bval2", "bval3", "bval4"] }
df = new dfd.Series(obj_data)
df.print()

<!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/npm/danfojs@1.1.2/lib/bundle.min.js"></script>    <title>Document</title>
</head>

<body>

    <script>

         json_data = [{ A: 0.4612, B: 4.28283, C: -1.509, D: -1.1352 },
            { A: 0.5112, B: -0.22863, C: -3.39059, D: 1.1632 },
            { A: 0.6911, B: -0.82863, C: -1.5059, D: 2.1352 },
            { A: 0.4692, B: -1.28863, C: 4.5059, D: 4.1632 }]

        df = new dfd.DataFrame(json_data)
        df.print()

    </script>
</body>

</html>

╔═══╤═══════╗
║ 0 │ bval1 ║
╟───┼───────╢
║ 1 │ bval2 ║
╟───┼───────╢
║ 2 │ bval3 ║
╟───┼───────╢
║ 3 │ bval4 ║
╚═══╧═══════╝

Creating a Series from an array

const dfd = require("danfojs-node")

obj_data = ["bval1", "bval2", "bval3", "bval4"]
df = new dfd.Series(obj_data)
df.print()

<!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/npm/danfojs@1.1.2/lib/bundle.min.js"></script>    <title>Document</title>
</head>

<body>

    <script>

         json_data = [{ A: 0.4612, B: 4.28283, C: -1.509, D: -1.1352 },
            { A: 0.5112, B: -0.22863, C: -3.39059, D: 1.1632 },
            { A: 0.6911, B: -0.82863, C: -1.5059, D: 2.1352 },
            { A: 0.4692, B: -1.28863, C: 4.5059, D: 4.1632 }]

        df = new dfd.DataFrame(json_data)
        df.print()

    </script>
</body>

</html>

╔═══╤═══════╗
║ 0 │ bval1 ║
╟───┼───────╢
║ 1 │ bval2 ║
╟───┼───────╢
║ 2 │ bval3 ║
╟───┼───────╢
║ 3 │ bval4 ║
╚═══╧═══════╝

Creating a Series and specifying index and dtypes

You can create a Series and specify options like index, dtypes, as well as configuration options for display, and memory mode etc.

Note: Specifing dtypes, and index on Series creation makes the process slightly faster.

import { Series } from "danfojs"

let data1 = [1, 2, 3, 4, 5];
let index = ["a", "b", "c", "d", "e"];
let dtypes = ["int32",]

let df = new Series(data1, { index, dtypes });
df.print()

╔═══╤═══╗
║ a │ 1 ║
╟───┼───╢
║ b │ 2 ║
╟───┼───╢
║ c │ 3 ║
╟───┼───╢
║ d │ 4 ║
╟───┼───╢
║ e │ 5 ║
╚═══╧═══╝

Creating a Series and specifying memory mode

To use less space on Series creation, you can set the low memory mode as demonstrated below:

import { Series } from "danfojs"

let data1 = [1, 2.3, 3, 4, 5, "girl"];

let df = new Series(data1, {
    config: { lowMemoryMode: true }
});
df.print()

Note: In low memory mode, less space is used by the Series.

PreviousSeries NextSeries.append

Last updated 1 year ago