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new 46e3151 fix link
46e3151 is described below
commit 46e3151f70a892e43a24abcf52fbb0fabe1f08c2
Author: plainheart <[email protected]>
AuthorDate: Thu Jul 11 14:09:16 2024 +0800
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 ef90955..d1af92e 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](${exampleEditorPath}dataset-
Most of the data described in commonly used charts is a "two-dimensional
table" structure, in the previous case, we use a 2D array to contain a
two-dimensional table. Now, when we map a series to a column, that column was
called a "dimension" and each row was called "item", vice versa.
-The dimension can have their name to display in the chart. Dimension name can
be defined in the first column (row). In the [next
case](#map-from-data-to-charts-(series.encode)), `'score'`, `'amount'`,
`'product'` are the name of dimensions. The actual data locate from the second
row. ECharts will automatically check if the first column (row) contained
dimension name in `dataset.source`. You can also use `dataset.sourceHeader:
true` to declare that the first column (row) represents the di [...]
+The dimension can have their name to display in the chart. Dimension name can
be defined in the first column (row). In the [next
case](${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 [...]
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 2ad0c41..b84f61d 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](#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）：
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