| 1 | # Transform
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| 2 |
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| 3 | ## Install
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| 4 |
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| 5 | ### npm
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| 6 |
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| 7 | ```shell
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| 8 | npm install @antv/dw-transform
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| 9 | ```
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| 10 |
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| 11 | ### yarn
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| 12 |
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| 13 | ```shell
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| 14 | yarn add @antv/dw-analyzer
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| 15 | ```
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| 16 |
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| 17 | ## Schema
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| 18 |
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| 19 | ```js
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| 20 | {
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| 21 | "groupBy": [...],
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| 22 | "actions": [
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| 23 | {
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| 24 | "type": ...,
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| 25 | "field": ...,
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| 26 | "as": ...,
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| 27 | "options": {
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| 28 | ...,
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| 29 | }
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| 30 | }
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| 31 | ]
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| 32 | }
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| 33 | ```
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| 34 |
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| 35 | ## Usage
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| 36 |
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| 37 | ### autoTransform
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| 38 |
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| 39 | The `autoTransform` function generates transform schemas to aggregate data fields in a default way.
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| 40 |
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| 41 | ```ts
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| 42 | const data = [
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| 43 | { gender: 'Male', height: 180 },
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| 44 | { gender: 'Female', height: 165 },
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| 45 | { gender: 'Male', height: 170 },
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| 46 | ];
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| 47 |
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| 48 | const { result, schemas } = autoTransform(data);
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| 49 |
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| 50 | console.log(schemas);
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| 51 | // [
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| 52 | // {
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| 53 | // groupBy: ['gender'],
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| 54 | // actions: [
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| 55 | // {
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| 56 | // type: 'sum',
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| 57 | // field: 'height',
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| 58 | // as: 'SUM(height)',
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| 59 | // },
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| 60 | // ],
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| 61 | // },
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| 62 | // ]
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| 63 |
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| 64 | console.log(result);
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| 65 | // [
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| 66 | // { gender: 'Male', 'SUM(height)': 350 },
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| 67 | // { gender: 'Female', 'SUM(height)': 165 },
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| 68 | // ]
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| 69 | ```
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| 70 |
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| 71 | #### renameOption
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| 72 |
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| 73 | The `renameOption` parameter of the `autoTransform` function defines how the created aggregation field would be named.
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| 74 |
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| 75 | Say, field title is `field1` and aggregation type is `sum`:
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| 76 |
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| 77 | | renameOption | as |
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| 78 | | :--------------------------------: | :------------------: |
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| 79 | | `'brackets'` (default) <br> `true` | `'SUM(field1)'` |
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| 80 | | `'underline'` | `'SUM_field1'` |
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| 81 | | `'origin'` <br> `false` | `'field1'` |
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| 82 | | *function* `f(a,b)` | `f('field1', 'sum')` |
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| 83 |
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| 84 | ```ts
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| 85 | const data = [
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| 86 | { gender: 'Male', height: 180 },
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| 87 | { gender: 'Female', height: 165 },
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| 88 | { gender: 'Male', height: 170 },
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| 89 | ];
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| 90 |
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| 91 | const { result, schemas } = autoTransform(data, false);
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| 92 |
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| 93 | console.log(schemas);
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| 94 | // [
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| 95 | // {
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| 96 | // groupBy: ['gender'],
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| 97 | // actions: [
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| 98 | // {
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| 99 | // type: 'sum',
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| 100 | // field: 'height',
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| 101 | // as: 'height', // as origin
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| 102 | // },
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| 103 | // ],
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| 104 | // },
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| 105 | // ]
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| 106 |
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| 107 | console.log(result);
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| 108 | // [
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| 109 | // { gender: 'Male', 'height': 350 }, // as origin
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| 110 | // { gender: 'Female', 'height': 165 }, // as origin
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| 111 | // ]
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| 112 | ```
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| 113 |
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| 114 | ### parse
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| 115 |
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| 116 | If you already have a dataset and a transform schema for it, you can use the function `parse` to get the result.
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| 117 |
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| 118 | ```ts
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| 119 | const data = [
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| 120 | { id: '1', height: 10.5, weight: 60 },
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| 121 | { id: '2', height: null, weight: 40 },
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| 122 | { id: '3', height: 9.5, weight: null },
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| 123 | { id: '', height: 9.5, weight: 80 },
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| 124 | { id: '5', height: 9.5 },
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| 125 | ];
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| 126 |
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| 127 | const schema = {
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| 128 | actions: [
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| 129 | {
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| 130 | type: 'removeNull',
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| 131 | field: 'id',
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| 132 | as: null,
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| 133 | },
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| 134 | ],
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| 135 | }
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| 136 |
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| 137 | const result = parse(data, schema);
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| 138 | // [
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| 139 | // { id: '1', height: 10.5, weight: 60 },
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| 140 | // { id: '2', height: null, weight: 40 },
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| 141 | // { id: '3', height: 9.5, weight: null },
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| 142 | // { id: '5', height: 9.5 },
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| 143 | // ]
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| 144 | ```
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