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 |
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.
{% tabs %} {% tab title="Node" %}
const dfd = require("danfojs-node")
obj_data = { 'B': ["bval1", "bval2", "bval3", "bval4"] }
df = new dfd.Series(obj_data)
df.print()
{% endtab %}
{% tab title="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/npm/[email protected]/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>
{% endtab %} {% endtabs %}
╔═══╤═══════╗
║ 0 │ bval1 ║
╟───┼───────╢
║ 1 │ bval2 ║
╟───┼───────╢
║ 2 │ bval3 ║
╟───┼───────╢
║ 3 │ bval4 ║
╚═══╧═══════╝
{% tabs %} {% tab title="Node" %}
const dfd = require("danfojs-node")
obj_data = ["bval1", "bval2", "bval3", "bval4"]
df = new dfd.Series(obj_data)
df.print()
{% endtab %}
{% tab title="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/npm/[email protected]/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>
{% endtab %} {% endtabs %}
╔═══╤═══════╗
║ 0 │ bval1 ║
╟───┼───────╢
║ 1 │ bval2 ║
╟───┼───────╢
║ 2 │ bval3 ║
╟───┼───────╢
║ 3 │ bval4 ║
╚═══╧═══════╝
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.
{% tabs %} {% tab title="Node" %}
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()
{% endtab %} {% endtabs %}
╔═══╤═══╗
║ a │ 1 ║
╟───┼───╢
║ b │ 2 ║
╟───┼───╢
║ c │ 3 ║
╟───┼───╢
║ d │ 4 ║
╟───┼───╢
║ e │ 5 ║
╚═══╧═══╝
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()
{% hint style="info" %} Note: In low memory mode, less space is used by the Series. {% endhint %}