还使用颜色编码时如何在 vega-lite 中使用 zero=false?
How to use zero=false in vega-lite when also using a color encoding?
我想知道如何不让我的 y 轴从零开始?它通常对我有用,但如果我添加颜色编码(见下文),它就不再工作了,而是我看到了零。
{
"data": {"name": "d"},
"mark": {"type": "bar"},
"encoding": {
"color": {"type": "nominal", "field": "group"},
"x": {"type": "nominal", "field": "model"},
"y": {
"type": "quantitative",
"field": "inf_f1",
"scale": {"zero": false}
}
},
"$schema": "https://vega.github.io/schema/vega-lite/v4.0.2.json",
"datasets": {
"d": [
{
"model": "lr-bow",
"inf_f1": 0.7991841662090597,
"group" : "A"
},
{
"model": "fcn-bow",
"inf_f1": 0.8220151833558302,
"group" : "B"
}
]
}
}
比例尺包含零的原因是默认情况下条形是堆叠的,并且每个条形都有一个隐含的堆叠 zero-height 条形用于未出现的组,但会影响自动选择的轴限制。您可以通过在 y 编码 (view in editor) 中将 stack
设置为 "none"
来解决此问题:
{
"data": {"name": "d"},
"mark": {"type": "bar"},
"encoding": {
"color": {"type": "nominal", "field": "group"},
"x": {"type": "nominal", "field": "model"},
"y": {
"type": "quantitative",
"field": "inf_f1",
"stack": "none",
"scale": {"zero": false}
}
},
"datasets": {
"d": [
{"model": "lr-bow", "inf_f1": 0.7991841662090597, "group": "A"},
{"model": "fcn-bow", "inf_f1": 0.8220151833558302, "group": "B"}
]
}
}
我想知道如何不让我的 y 轴从零开始?它通常对我有用,但如果我添加颜色编码(见下文),它就不再工作了,而是我看到了零。
{
"data": {"name": "d"},
"mark": {"type": "bar"},
"encoding": {
"color": {"type": "nominal", "field": "group"},
"x": {"type": "nominal", "field": "model"},
"y": {
"type": "quantitative",
"field": "inf_f1",
"scale": {"zero": false}
}
},
"$schema": "https://vega.github.io/schema/vega-lite/v4.0.2.json",
"datasets": {
"d": [
{
"model": "lr-bow",
"inf_f1": 0.7991841662090597,
"group" : "A"
},
{
"model": "fcn-bow",
"inf_f1": 0.8220151833558302,
"group" : "B"
}
]
}
}
比例尺包含零的原因是默认情况下条形是堆叠的,并且每个条形都有一个隐含的堆叠 zero-height 条形用于未出现的组,但会影响自动选择的轴限制。您可以通过在 y 编码 (view in editor) 中将 stack
设置为 "none"
来解决此问题:
{
"data": {"name": "d"},
"mark": {"type": "bar"},
"encoding": {
"color": {"type": "nominal", "field": "group"},
"x": {"type": "nominal", "field": "model"},
"y": {
"type": "quantitative",
"field": "inf_f1",
"stack": "none",
"scale": {"zero": false}
}
},
"datasets": {
"d": [
{"model": "lr-bow", "inf_f1": 0.7991841662090597, "group": "A"},
{"model": "fcn-bow", "inf_f1": 0.8220151833558302, "group": "B"}
]
}
}