From e95e394dc10c08888fad9c868f6a224d66f0aad4 Mon Sep 17 00:00:00 2001 From: plainheart Date: Thu, 11 Jul 2024 14:23:46 +0800 Subject: [PATCH] fix link --- contents/en/concepts/dataset.md | 2 +- contents/zh/concepts/dataset.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/contents/en/concepts/dataset.md b/contents/en/concepts/dataset.md index d1af92ea..8cb03a26 100644 --- a/contents/en/concepts/dataset.md +++ b/contents/en/concepts/dataset.md @@ -160,7 +160,7 @@ The effect of configuration is shown in [this case](${exampleEditorPath}dataset- Most of the data described in commonly used charts is a "two-dimensional table" structure, in the previous case, we use a 2D array to contain a two-dimensional table. Now, when we map a series to a column, that column was called a "dimension" and each row was called "item", vice versa. -The dimension can have their name to display in the chart. Dimension name can be defined in the first column (row). In the [next case](${lang}/concepts/dataset#map-from-data-to-charts-(series.encode)), `'score'`, `'amount'`, `'product'` are the name of dimensions. The actual data locate from the second row. ECharts will automatically check if the first column (row) contained dimension name in `dataset.source`. You can also use `dataset.sourceHeader: true` to declare that the first column (row) represents the dimension name. +The dimension can have their name to display in the chart. Dimension name can be defined in the first column (row). In the [next case](${lang}/concepts/dataset/#map-from-data-to-charts-(series.encode)), `'score'`, `'amount'`, `'product'` are the name of dimensions. The actual data locate from the second row. ECharts will automatically check if the first column (row) contained dimension name in `dataset.source`. You can also use `dataset.sourceHeader: true` to declare that the first column (row) represents the dimension name. Try to use single `dataset.dimensions` or some `series.dimensions` to define the dimensions, therefore you can specify the name and type together. diff --git a/contents/zh/concepts/dataset.md b/contents/zh/concepts/dataset.md index b84f61d9..be10aa1c 100644 --- a/contents/zh/concepts/dataset.md +++ b/contents/zh/concepts/dataset.md @@ -153,7 +153,7 @@ option = { 常用图表所描述的数据大部分是“二维表”结构，上述的例子中，我们都使用二维数组来容纳二维表。现在，当我们把系列（series）对应到“列”的时候，那么每一列就称为一个“维度（dimension）”，而每一行称为数据项（item）。反之，如果我们把系列（series）对应到表行，那么每一行就是“维度（dimension）”，每一列就是数据项（item）。 -维度可以有单独的名字，便于在图表中显示。维度名（dimension name）可以在定义在 dataset 的第一行（或者第一列）。例如下面的[例子](${lang}/concepts/dataset#数据到图形的映射（series.encode）)中，`'score'`、`'amount'`、`'product'` 就是维度名。从第二行开始，才是正式的数据。`dataset.source` 中第一行（列）到底包含不包含维度名，ECharts 默认会自动探测。当然也可以设置 `dataset.sourceHeader: true` 显示声明第一行（列）就是维度，或者 `dataset.sourceHeader: false` 表明第一行（列）开始就直接是数据。 +维度可以有单独的名字，便于在图表中显示。维度名（dimension name）可以在定义在 dataset 的第一行（或者第一列）。例如下面的[例子](${lang}/concepts/dataset/#数据到图形的映射（series.encode）)中，`'score'`、`'amount'`、`'product'` 就是维度名。从第二行开始，才是正式的数据。`dataset.source` 中第一行（列）到底包含不包含维度名，ECharts 默认会自动探测。当然也可以设置 `dataset.sourceHeader: true` 显示声明第一行（列）就是维度，或者 `dataset.sourceHeader: false` 表明第一行（列）开始就直接是数据。 维度的定义，也可以使用单独的 `dataset.dimensions` 或者 `series.dimensions` 来定义，这样可以同时指定维度名，和维度的类型（dimension type）：