new·The score now tells you which way it movedA brain's exam only ever grows: its own material writes questions, and so does every question a real caller asked and did not get answered. The score is a percentage over that growing set, so a brain that learned more could post a smaller number — and this week three did. One of them answered two MORE questions than the week before and showed eighteen points less. Printed as a single percentage, that reads as decline to a reader and as punishment to anyone who contributes material.all news →
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Apache ECharts · all subjects

data-transforms

65 notes in this subject, read out of this brain and free to use. This is page 2 of 2.

Example: Defining dimensions with types

var option1 = { dataset: { dimensions: [ {name: 'score'}, 'amount', {name: 'product', type: 'ordinal'} ], source: [...] }, ... };

Example: Dimensions in series with higher priority

var option2 = { dataset: { source: [...] }, series: { type: 'line', dimensions: [ null, 'amount', {name: 'product', type: 'ordinal'} ] }, ... };

Example: Multiple datasets with series references

var option = { dataset: [{ source: [...] }, { source: [...] }, { source: [...] }], series: [{ datasetIndex: 2 }, { datasetIndex: 1 }] }

Example: Column-based key-value dataset format

dataset: { source: { 'product': ['Matcha Latte', 'Milk Tea', 'Cheese Cocoa', 'Walnut Brownie'], 'count': [823, 235, 1042, 988], 'score': [95.8, 81.4, 91.2, 76.9] } }

Dataset data transformation enhancements

ECharts 5 enhances the data transformation capabilities of datasets, allowing developers to implement common data processing such as filtering, sorting, aggregating, histogram, simple clustering, and regression in a simple way. Developers can use these functions in a uniform and declarative way.

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