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commit 4f4252a647018968a842c5c7767e9335ba95c234
Author: plainheart <y...@all-my-life.cn>
AuthorDate: Thu Nov 3 14:38:11 2022 +0800
fix: update links in concepts/dataset.md
---
contents/en/concepts/dataset.md | 26 +++++++++++++-------------
contents/zh/concepts/dataset.md | 20 ++++++++++----------
2 files changed, 23 insertions(+), 23 deletions(-)
diff --git a/contents/en/concepts/dataset.md b/contents/en/concepts/dataset.md
index 1214a88..a45e9b5 100644
--- a/contents/en/concepts/dataset.md
+++ b/contents/en/concepts/dataset.md
@@ -2,7 +2,7 @@
`dataset` is a component dedicated to manage data. Although you can set the
data in `series.data` for every series, we recommend you use the `dataset` to
manage the data since ECharts 4 so that the data can be reused by multiple
components and convenient for the separation of "data and configs". After all,
data is the most common part to be changed while other configurations will
mostly not change at runtime.
-## Define `data` under `series`
+## Define **data** under **series**
If data is defined under `series`, for example:
@@ -36,7 +36,7 @@ option = {
Define `data` under `series` is suitable for customization for some special
data structures such as "tree", "graph" and large data.
However, it is not conducive to the data sharing for multiple series as well
as mapping arrangement of chart types and series based on the original data.
The other disadvantage is that programmers always need to divide the data in
separate series (and categories) first.
-## Define `data` in `dataset`
+## Define **data** in **dataset**
Here are the advantages if you define `data` in `dataset`:
@@ -106,12 +106,12 @@ The ideas of data visualization: (I) Provide the data,
(II)Mapping from data to
In short, you can set these configs of mapping:
-- Specify 'column' or 'row' of `dataset` to map the `series`. You can use
[series.seriesLayoutBy](${optionPath}#series.seriesLayoutBy) to configure it.
The default is to map according to the column.
-- Rule of specifying dimension mapping: how to mapping from dimensions of
'dataset' to `axis`, `tooltip`, `label` and `visualMap`. To configure the
mapping, please use [series.encode](${optionPath}#series.encode) and
[visualMap](${optionPath}#visualMap). The previous case did not give the
mapping configuration so that ECharts will follow the default: if x-axis is
category, mapping to the first row in `dataset.source`; three-column chart
mapping with each row in `dataset.source` one by one.
+- Specify 'column' or 'row' of `dataset` to map the `series`. You can use
[series.seriesLayoutBy](${optionPath}series.seriesLayoutBy) to configure it.
The default is to map according to the column.
+- Rule of specifying dimension mapping: how to mapping from dimensions of
'dataset' to `axis`, `tooltip`, `label` and `visualMap`. To configure the
mapping, please use [series.encode](${optionPath}series.encode) and
[visualMap](${optionPath}visualMap). The previous case did not give the mapping
configuration so that ECharts will follow the default: if x-axis is category,
mapping to the first row in `dataset.source`; three-column chart mapping with
each row in `dataset.source` one by one.
The details of the configuration are shown below:
-## Map Row or Column of `dataset` to `series`
+## Map Row or Column of **dataset** to **series**
After having the dataset, you can configure flexibly: how the data map to the
axis and graph series.
@@ -202,13 +202,13 @@ Dimension type can be the following values:
- `'number'`: Default, normal data.
- `'ordinal'`: String types data like categories, text can be used on the axis
only with the dimension type 'ordinal'. ECharts will try to judge this type
automatically but might be inaccurate, so you can specify manually.
-- `'time'`: To represent time data, ECharts can automatically analyze data as
timestamp if the dimension type is defined as `'time'`. For instance, ECharts
will auto-analyze if the data of this dimension is '2017-05-10'`. If the
dimension is used as time axis ([axis.type](${optionPath}#xAxis.type)
=`'time'`), the dimension type will also be`'time'`. See
[data](${optionPath}#series.data) for more time type support.
+- `'time'`: To represent time data, ECharts can automatically analyze data as
timestamp if the dimension type is defined as `'time'`. For instance, ECharts
will auto-analyze if the data of this dimension is '2017-05-10'`. If the
dimension is used as time axis ([axis.type](${optionPath}xAxis.type)
=`'time'`), the dimension type will also be`'time'`. See
[data](${optionPath}series.data) for more time type support.
- `'float'`: Use `TypedArray` to optimize the performance in `'float'`
dimension.
- `'int'`: Use `TypedArray` to optimize the performance in `'int'` dimension.
## Map from Data to Charts (series.encode)
-After understand the concept of dimension, you can use
[series.encode](${optionPath}#series.encode) to make a mapping:
+After understand the concept of dimension, you can use
[series.encode](${optionPath}series.encode) to make a mapping:
```js live
var option = {
@@ -340,7 +340,7 @@ option = {
Q: How to set the 2nd column as a label?
A:
-We now support to trace value from specific dimension for
[label.formatter](${optionPath}#series.label.formatter):
+We now support to trace value from specific dimension for
[label.formatter](${optionPath}series.label.formatter):
```js
series: {
@@ -425,7 +425,7 @@ A: Check your spelling, such as misspell the dimension name
`'Life Expectancy'`
## Visual Channel Mapping
-We can map visual channel by using [visualMap](${optionPath}#visualMap). Check
details in the [visualMap](${optionPath}#visualMap) document. Here is an
[example](${exampleEditorPath}dataset-encode0).
+We can map visual channel by using [visualMap](${optionPath}visualMap). Check
details in the [visualMap](${optionPath}visualMap) document. Here is an
[example](${exampleEditorPath}dataset-encode0).
## Formats of Charts
@@ -435,7 +435,7 @@ In most of the normal chart, the data is suitable to be
described in the form of
As the example shown behind, in the data transmission of JavaScript, the
two-dimensional data can be stored directly by two-dimensional array.
-Expect from the two-dimensional array, the dataset also supports using
key-value which is also a common way. However, we don't support
[seriesLayoutBy](${optionPath}#series.seriesLayoutBy) in this format right now.
+Expect from the two-dimensional array, the dataset also supports using
key-value which is also a common way. However, we don't support
[seriesLayoutBy](${optionPath}series.seriesLayoutBy) in this format right now.
```js
dataset: [
@@ -461,7 +461,7 @@ dataset: [
## How to Reference Several Datasets
-ECharts support to define several datasets at the same moment. Series can
assign the one to reference by
[series.datasetIndex](${optionPath}#series.datasetIndex). For example:
+ECharts support to define several datasets at the same moment. Series can
assign the one to reference by
[series.datasetIndex](${optionPath}series.datasetIndex). For example:
```js
var option = {
@@ -494,7 +494,7 @@ var option = {
## series.data in ECharts 3
-ECharts 4 still support the data declaration way in ECharts 3. If the series
has already declared the [series.data](${optionPath}#series.data), then use
[series.data](${optionPath}#series.data) but not `dataset`.
+ECharts 4 still supports the data declaration way in ECharts 3. If the series
has already declared the [series.data](${optionPath}series.data), then use
[series.data](${optionPath}series.data) but not `dataset`.
```js
option = {
@@ -523,7 +523,7 @@ option = {
};
```
-In fact, [series.data](${optionPath}#series.data) is an important setting
method which will always exist. Some special non-table format chart like
[treemap](${optionPath}#series-treemap), [graph](${optionPath}#series-graph)
and [lines](${optionPath}#series-lines) still cannot be edit in dataset, you
still need to use [series.data](${optionPath}#series.data). In another way, for
render huge amount of data (over a million), you need to use
[appendData](${mainSitePath}api.html#echartsInstan [...]
+In fact, [series.data](${optionPath}series.data) is an important setting
method which will always exist. Some special non-table format chart like
[treemap](${optionPath}series-treemap), [graph](${optionPath}series-graph) and
[lines](${optionPath}series-lines) still cannot be edit in dataset, you still
need to use [series.data](${optionPath}series.data). In another way, for render
huge amount of data (over a million), you need to use
[appendData](${mainSitePath}api.html#echartsInstance.ap [...]
## Others
diff --git a/contents/zh/concepts/dataset.md b/contents/zh/concepts/dataset.md
index 9ac416b..ee4f54b 100644
--- a/contents/zh/concepts/dataset.md
+++ b/contents/zh/concepts/dataset.md
@@ -101,8 +101,8 @@ option = {
简而言之，可以进行这些映射的设定：
-- 指定 `数据集` 的列（column）还是行（row）映射为 `系列`（`series`）。这件事可以使用
[series.seriesLayoutBy](${optionPath}#series.seriesLayoutBy)
属性来配置。默认是按照列（column）来映射。
-- 指定维度映射的规则：如何从 dataset 的维度（一个“维度”的意思是一行/列）映射到坐标轴（如 X、Y
轴）、提示框（tooltip）、标签（label）、图形元素大小颜色等（visualMap）。这件事可以使用
[series.encode](${optionPath}#series.encode) 属性，以及
[visualMap](${optionPath}#visualMap)
组件来配置（如果有需要映射颜色大小等视觉维度的话）。上面的例子中，没有给出这种映射配置，那么 ECharts 就按最常见的理解进行默认映射：X
坐标轴声明为类目轴，默认情况下会自动对应到 `dataset.source` 中的第一列；三个柱图系列，一一对应到 `dataset.source`
中后面每一列。
+- 指定 `数据集` 的列（column）还是行（row）映射为 `系列`（`series`）。这件事可以使用
[series.seriesLayoutBy](${optionPath}series.seriesLayoutBy)
属性来配置。默认是按照列（column）来映射。
+- 指定维度映射的规则：如何从 dataset 的维度（一个“维度”的意思是一行/列）映射到坐标轴（如 X、Y
轴）、提示框（tooltip）、标签（label）、图形元素大小颜色等（visualMap）。这件事可以使用
[series.encode](${optionPath}series.encode) 属性，以及
[visualMap](${optionPath}visualMap)
组件来配置（如果有需要映射颜色大小等视觉维度的话）。上面的例子中，没有给出这种映射配置，那么 ECharts 就按最常见的理解进行默认映射：X
坐标轴声明为类目轴，默认情况下会自动对应到 `dataset.source` 中的第一列；三个柱图系列，一一对应到 `dataset.source`
中后面每一列。
下面详细解释这些映射的设定。
@@ -199,13 +199,13 @@ var option2 = {
- `'number'`: 默认，表示普通数据。
- `'ordinal'`: 对于类目、文本这些 string 类型的数据，如果需要能在数轴上使用，须是 'ordinal' 类型。ECharts
默认会试图自动判断这个类型。但是自动判断也可能不准确，所以使用者也可以手动强制指定。
-- `'time'`: 表示时间数据。设置成 `'time'` 则能支持自动解析数据成时间戳（timestamp），比如该维度的数据是
'2017-05-10'，会自动被解析。如果这个维度被用在时间数轴（[axis.type](${optionPath}#xAxis.type) 为
`'time'`）上，那么会被自动设置为 `'time'` 类型。时间类型的支持参见 [data](${optionPath}#series.data)。
+- `'time'`: 表示时间数据。设置成 `'time'` 则能支持自动解析数据成时间戳（timestamp），比如该维度的数据是
'2017-05-10'，会自动被解析。如果这个维度被用在时间数轴（[axis.type](${optionPath}xAxis.type) 为
`'time'`）上，那么会被自动设置为 `'time'` 类型。时间类型的支持参见 [data](${optionPath}series.data)。
- `'float'`: 如果设置成 `'float'`，在存储时候会使用 `TypedArray`，对性能优化有好处。
- `'int'`: 如果设置成 `'int'`，在存储时候会使用 `TypedArray`，对性能优化有好处。
## 数据到图形的映射（ series.encode ）
-了解了维度的概念后，我们就可以使用 [series.encode](${optionPath}#series.encode) 来做映射。总体是这样的感觉：
+了解了维度的概念后，我们就可以使用 [series.encode](${optionPath}series.encode) 来做映射。总体是这样的感觉：
```js live
var option = {
@@ -334,7 +334,7 @@ option = {
问：如何把第二列设置为标签？
答：
-关于标签的显示
[label.formatter](${optionPath}#series.label.formatter)，现在支持引用特定维度的值，例如：
+关于标签的显示 [label.formatter](${optionPath}series.label.formatter)，现在支持引用特定维度的值，例如：
```js
series: {
@@ -419,7 +419,7 @@ var option = {
## 视觉通道（颜色、尺寸等）的映射
-我们可以使用 [visualMap](${optionPath}#visualMap) 组件进行视觉通道的映射。详见
[visualMap](${optionPath}#visualMap) 文档的介绍。这是一个
[示例](${exampleEditorPath}dataset-encode0&edit=1&reset=1)。
+我们可以使用 [visualMap](${optionPath}visualMap) 组件进行视觉通道的映射。详见
[visualMap](${optionPath}visualMap) 文档的介绍。这是一个
[示例](${exampleEditorPath}dataset-encode0&edit=1&reset=1)。
## 数据的各种格式
@@ -429,7 +429,7 @@ var option = {
在 JavaScript 常用的数据传输格式中，二维数组可以比较直观的存储二维表。前面的示例都是使用二维数组表示。
-除了二维数组以外，dataset 也支持例如下面 key-value 方式的数据格式，这类格式也非常常见。但是这类格式中，目前并不支持
[seriesLayoutBy](${optionPath}#series.seriesLayoutBy) 参数。
+除了二维数组以外，dataset 也支持例如下面 key-value 方式的数据格式，这类格式也非常常见。但是这类格式中，目前并不支持
[seriesLayoutBy](${optionPath}series.seriesLayoutBy) 参数。
```js
dataset: [
@@ -455,7 +455,7 @@ dataset: [
## 多个 dataset 以及如何引用他们
-可以同时定义多个 dataset。系列可以通过
[series.datasetIndex](${optionPath}#series.datasetIndex) 来指定引用哪个 dataset。例如：
+可以同时定义多个 dataset。系列可以通过
[series.datasetIndex](${optionPath}series.datasetIndex) 来指定引用哪个 dataset。例如：
```js
var option = {
@@ -488,7 +488,7 @@ var option = {
## ECharts 3 的数据设置方式（series.data）仍正常使用
-ECharts 4 之前一直以来的数据声明方式仍然被正常支持，如果系列已经声明了
[series.data](${optionPath}#series.data)， 那么就会使用
[series.data](${optionPath}#series.data) 而非 `dataset`。
+ECharts 4 之前一直以来的数据声明方式仍然被正常支持，如果系列已经声明了
[series.data](${optionPath}series.data)， 那么就会使用
[series.data](${optionPath}series.data) 而非 `dataset`。
```js live
option = {
@@ -517,7 +517,7 @@ option = {
};
```
-其实，[series.data](${optionPath}#series.data) 也是种会一直存在的重要设置方式。一些特殊的非 table
格式的图表，如
[treemap](${optionPath}#series-treemap)、[graph](${optionPath}#series-graph)、[lines](${optionPath}#series-lines)
等，现在仍不支持在 dataset 中设置，仍然需要使用
[series.data](${optionPath}#series.data)。另外，对于巨大数据量的渲染（如百万以上的数据量），需要使用
[appendData](api.html#echartsInstance.appendData) 进行增量加载，这种情况不支持使用 `dataset`。
+其实，[series.data](${optionPath}series.data) 也是种会一直存在的重要设置方式。一些特殊的非 table
格式的图表，如
[treemap](${optionPath}series-treemap)、[graph](${optionPath}series-graph)、[lines](${optionPath}series-lines)
等，现在仍不支持在 dataset 中设置，仍然需要使用
[series.data](${optionPath}series.data)。另外，对于巨大数据量的渲染（如百万以上的数据量），需要使用
[appendData](api.html#echartsInstance.appendData) 进行增量加载，这种情况不支持使用 `dataset`。
## 其他
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