DataFrame

7 min read

DataFrame is the specified 2D data structure in DW. You can get or slice data by it. The information includes the field's characteristics (field name, data type, statistics, etc.) and properties (continuity, discreteness, etc.), as well as field-to-field relationships (correlation, periodicity, etc.).

new DataFrame

Parameters

data Raw data required

Accept one-dimensional and two-dimensional data.

Type

One-dimensional data
- Base data structure number | string | boolean | undefined | null
- One-dimensional array any[]
- One-dimensional object { [key: string]: any }
Two-dimensional data
- Two-dimensional array any[][]
- Object inside array { [key: string]: any }[]
- Array inside object { [key: string]: any[] }

extra extra parameters optional

Used to configure indexes, columns, and missing values.

Property	Type	Description	Default	Required
indexes	`string \| number`	Index	-	-
columns	`string \| number`	Column	-	-
fillValue	`any`	Filling missing value	-	-
columnTypes	`'null' \| 'boolean' \| 'integer' \| 'float' \| 'date' \| 'string' \| ''`	Data types of columns	-	-

Return value

DataFrame

Usage

import { DataFrame } from '@antv/data-wizard';

/* Basic usage */
const data = [
  { a: 1, b: 4, c: 7 }
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
];

new DataFrame(data);
/*
DataFrame
  {
    axes: [
      [0, 1, 2],
      ['a', 'b', 'c'],
    ],
    data: [
      [1, 4, 7],
      [2, 5, 8],
      [3, 6, 9],
    ],
    colData: [
      [1, 2, 3],
      [4, 5, 6],
      [7, 8, 9],
    ],
  }
*/

/* Set extra indexes and columns */
new DataFrame(data, {
  indexes: ['i1', 'i2', 'i3'],
  columns: ['c', 'b'],
});
/*
DataFrame
  {
    axes: [
      ['i1', 'i2', 'i3'],
      ['c', 'b'],
    ],
    data: [
      [7, 4],
      [8, 5],
      [9, 6],
    ],
    colData: [
      [7, 8, 9],
      [4, 5, 6],
    ],
  }
*/

/* Set extra fillValues */
const data3 = [
  { a: 1, b: 4 },
  { a: 2, c: 8 },
  { b: 6, c: 9 },
];

new DataFrame(data3, {
  fillValue: 201
});
/*
DataFrame
  {
    axes: [
      [0, 1, 2],
      ['a', 'b', 'c'],
    ],
    data: [
      [1, 4, 201],
      [2, 201, 8],
      [201, 6, 9],
    ],
    colData: [
      [1, 2, 201],
      [4, 201, 6],
      [201, 8, 9],
    ],
  }
*/

/* Set extra columnTypes */
const data3 = [
  { a: 1, b: 4 },
  { a: 2, c: 8 },
  { b: 6, c: 9 },
];

new DataFrame(data3, {
  columnTypes: ['', '', 'string']
});
/*
DataFrame
  {
    axes: [
      [0, 1, 2],
      ['a', 'b', 'c'],
    ],
    data: [
      [ 1, 4, 'undefined' ],
      [ 2, undefined, '8' ],
      [ undefined, 6, '9' ]
    ],
    colData: [
      [ 1, 2, undefined ],
      [ 4, undefined, 6 ],
      [ 'undefined', '8', '9' ]
    ],
  }
*/

shape

Get the DataFrame data row and column dimensions.

Usage

import { DataFrame } from '@antv/data-wizard';

const df = new DataFrame([
  { a: 1, b: 4, c: 7 }
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.shape;
// [ 3, 3 ]

get

Get data by row location and column location.

Parameters

rowLoc Row location required

The location of the row described by indexes.

Type (string | number) | (string | number)[] | string

colLoc Column location optional

The location of the column described by columns.

Type (string | number) | (string | number)[] | string

Return value

DataFrame | Series | any

Usage

import { DataFrame } from '@antv/data-wizard';

/* Get data by indexes value */
const df = new DataFrame([
  { a: 1, b: 4, c: 7 },
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.get(0);
/*
Series
  { 
    axes: [['a', 'b', 'c']], 
    data: [1, 4, 7]
  }
*/

/* Get data by an array of indexes value */
df.get([0, 2]);
/*
DataFrame
  {
    axes: [
      [0, 2],
      ['a', 'b', 'c'],
    ],
    data: [
      [1, 4, 7],
      [3, 6, 9],
    ],
    colData: [
      [1, 3],
      [4, 6],
      [7, 9],
    ],
  }
*/

/* Get data by indexes slice value */
df.get('0:2');
/*
DataFrame
 {
    axes: [
      [0, 1],
      ['a', 'b', 'c'],
    ],
    data: [
      [1, 4, 7],
      [2, 5, 8],
    ],
    colData: [
      [1, 2],
      [4, 5],
      [7, 8],
    ],
  }
*/

/* Get data by indexes and columns values */
const df = new DataFrame([
  { a: 1, b: 4, c: 7 },
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.get(1, 'c');
/*
DataFrame
  {
    axes: [[1], ['c']],
    data: [[8]],
    colData: [[8]],
  }
*/

/* Get data by indexes value and an array of columns value */
const df = new DataFrame([
  { a: 1, b: 4, c: 7 },
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.get(1, ['a', 'c']);
/*
DataFrame
  {
    axes: [[1], ['a', 'c']],
    data: [[2, 8]],
    colData: [[2], [8]],
  }
*/

/* Get data by indexes value and an array of columns slice value */
const df = new DataFrame([
  { a: 1, b: 4, c: 7 },
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.get(1, 'a:c');
/*
DataFrame
  {
    axes: [[1], ['a', 'b']],
    data: [[2, 5]],
    colData: [[2], [5]],
  }
*/

getByIndex

Get data by row location and column location using integer index. Similar to the get method, but only can be used by the integer index. For example, getByIndex(0, 0) gets the data of the first row and column.

Parameters

rowLoc Row location required

The integer index row location.

Type number | number[] | string

colLoc Column location optional

The nteger-index column location.

Type number | number[] | string

Return value

DataFrame | Series | any

Usage

import { DataFrame } from '@antv/data-wizard';

/* Get data by row index */
const df = new DataFrame([
  { a: 1, b: 4, c: 7 }
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.getByIndex(0, 1);
/*
DataFrame
  {
    axes: [[0], ['b']],
    data: [[4]],
    colData: [[4]],
  }
*/

getByColumn

Get the data by columns value.

Parameters

col Columns value required

The location of the column described by columns.

Type string | number

Return value

Series

Usage

import { DataFrame } from '@antv/data-wizard';

const df = new DataFrame([
  { a: 1, b: 4, c: 7 }
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.getByColumn('a');
/*
Series
 { 
   axes: [[0, 1, 2]], 
   data: [1, 2, 3] 
  }
*/

info

Get statistical information.

Return value

FieldsInfo

Usage

import { DataFrame } from '@antv/data-wizard';

const df = new DataFrame([
  { a: 1, b: 4, c: 7 },
  { a: 2, b: 5, c: 8 },
  { a: 3, b: 6, c: 9 },
]);

df.info();
/*
  [
    {
      count: 3,
      distinct: 3,
      type: 'integer',
      recommendation: 'integer',
      missing: 0,
      rawData: [1, 2, 3],
      valueMap: { '1': 1, '2': 1, '3': 1 },
      minimum: 1,
      maximum: 3,
      mean: 2,
      percentile5: 1,
      percentile25: 1,
      percentile50: 2,
      percentile75: 3,
      percentile95: 3,
      sum: 6,
      variance: 0.6666666666666666,
      standardDeviation: 0.816496580927726,
      zeros: 0,
      levelOfMeasurements: ['Interval', 'Discrete'],
      name: 'a',
    },
    {
      count: 3,
      distinct: 3,
      type: 'integer',
      recommendation: 'integer',
      missing: 0,
      rawData: [4, 5, 6],
      valueMap: { '4': 1, '5': 1, '6': 1 },
      minimum: 4,
      maximum: 6,
      mean: 5,
      percentile5: 4,
      percentile25: 4,
      percentile50: 5,
      percentile75: 6,
      percentile95: 6,
      sum: 15,
      variance: 0.6666666666666666,
      standardDeviation: 0.816496580927726,
      zeros: 0,
      levelOfMeasurements: ['Interval', 'Discrete'],
      name: 'b',
    },
    {
      count: 3,
      distinct: 3,
      type: 'integer',
      recommendation: 'integer',
      missing: 0,
      rawData: [7, 8, 9],
      valueMap: { '7': 1, '8': 1, '9': 1 },
      minimum: 7,
      maximum: 9,
      mean: 8,
      percentile5: 7,
      percentile25: 7,
      percentile50: 8,
      percentile75: 9,
      percentile95: 9,
      sum: 24,
      variance: 0.6666666666666666,
      standardDeviation: 0.816496580927726,
      zeros: 0,
      levelOfMeasurements: ['Interval', 'Discrete'],
      name: 'c',
    },
  ]
*/