@msrvida/data-inference

Infer column types in tabular data. Inference is from vega-loader's inferTypes function (or similar function of your choice). This library enriches the column metadata with a ColumnStats object.

Demo

Usage

You will need an array of data objects, so that columns types can be inferred.

$3

``js
import * as DataInference from '@msrvida/data-inference';
import { inferTypes } from 'vega-loader';

const data = [
{
Name: 'chevrolet chevelle malibu',
Miles_per_Gallon: 18,
Cylinders: 8,
Displacement: 307,
Horsepower: 130,
Weight_in_lbs: 3504,
Acceleration: 12,
Year: '1970-01-01',
Origin: 'USA',
},
{
Name: 'buick skylark 320',
Miles_per_Gallon: 15,
Cylinders: 8,
Displacement: 350,
Horsepower: 165,
Weight_in_lbs: 3693,
Acceleration: 11.5,
Year: '1970-01-01',
Origin: 'USA',
},
];

const columns = DataInference.getColumnsFromData(inferTypes, data);
console.log(columns);
`

$3

`html



`

Sample output

`json
[
{
"name": "Name",
"type": "string",
"quantitative": false,
"stats": {
"distinctValueCount": 2,
"max": null,
"mean": null,
"min": null
},
"isColorData": false
},
{
"name": "Miles_per_Gallon",
"type": "integer",
"quantitative": true,
"stats": {
"distinctValueCount": 2,
"max": 18,
"mean": 16.5,
"min": 15,
"hasNegative": false,
"isSequential": false
}
},
{
"name": "Cylinders",
"type": "integer",
"quantitative": true,
"stats": {
"distinctValueCount": 1,
"max": 8,
"mean": 8,
"min": 8,
"hasNegative": false,
"isSequential": false
}
},
.
.
.
]
`

Pandas-style simulation

As of version 1.2, the pandasSimulation namespace provides describe(), head(), and info() functions to emit data inferences in similar format of Python's Pandas library

$3

`js
console.log(DataInference.pandasSimulation.head(columns, data));
`

`
Name Miles_per_Gallon Cylinders Displacement Horsepower \
1 chevrolet chevelle malibu 18 8 307 130
2 buick skylark 320 15 8 350 165
3 plymouth satellite 18 8 318 150
4 amc rebel sst 16 8 304 150
5 ford torino 17 8 302 140

Weight_in_lbs Acceleration Year Origin
3504 12 1970-01-01 USA
3693 11.5 1970-01-01 USA
3436 11 1970-01-01 USA
3433 12 1970-01-01 USA
3449 10.5 1970-01-01 USA
`

$3

`js
console.log(DataInference.pandasSimulation.info(columns, data));
`

`
info

Index: 406 entries, 0 to 405
Data columns (total 9 columns):

Column Non-Null Count Dtype

- ---------------- -------------- --------------
0 Name 406 non-null object
1 Miles_per_Gallon 398 non-null float64
2 Cylinders 406 non-null int64
3 Displacement 406 non-null float64
4 Horsepower 400 non-null int64
5 Weight_in_lbs 406 non-null int64
6 Acceleration 406 non-null float64
7 Year 406 non-null datetime64[ns]
8 Origin 406 non-null object


dtypes: 3 float64, 3 int64, 2 object
memory usage: 21.0 KB
``

For more information

Please visit the SandDance website.