Vega-lite Multiple aggregations in Transforms - vega

Question

I want to implement two diff aggregations in a transform as they have different groupby conditions, but it seems not possible with vega-lite
{
"$schema": "https://vega.github.io/schema/vega/v5.json",
"data": {
{"response":200,"request":"/ST"},
{"response":500,"request":"/ST"},
{"response":200,"request":"/PP"},
{"response":500,"request":"/PP"},
{"response":200,"request":"/CP"},
{"response":200,"request":"/CP"},
{"response":500,"request":"/CP"},
{"response":500,"request":"/CP"},
{"response":500,"request":"/CP"},
{"response":500,"request":"/CP"},
{"response":500,"request":"/CP"},
{"response":500,"request":"/CP"},
{"response":503,"request":"/CP"},
{"response":503,"request":"/CP"},
{"response":503,"request":"/CP"}
"transform": [
{
"aggregate": [{
"op": "count",
"as": "response_count"
}],
"groupby": ["response","request"]
},
{
"aggregate": [{
"op": "count",
"as": "response_c"
}],
"groupby": ["request"]
}
],
{"mark": "bar",
"encoding": {
"x": {"field": "response_count", "type": "quantitative", "stack": "zero"},
"y": {"field": "request", "type": "nominal"},
"color": {"field": "response", "type": "nominal"}}
}
Is there any way of achieving this ? Are multiple aggregations like this supported?

Answer 1

Yes, multiple aggregations like this are supported, but your chart has undefined fields in the end because you have have not referenced them in your aggregations. You start with this data:
[
{"response": 200, "request": "/ST"},
{"response": 500, "request": "/ST"},
{"response": 200, "request": "/PP"},
{"response": 500, "request": "/PP"},
{"response": 200, "request": "/CP"},
{"response": 200, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 503, "request": "/CP"},
{"response": 503, "request": "/CP"},
{"response": 503, "request": "/CP"}
]
The first aggregation groups by "response" and "request", and adds "response_count" in each group, which looks like this:
[
{"response": 200, "request": "/ST", "response_count": 1},
{"response": 500, "request": "/ST", "response_count": 1},
{"response": 200, "request": "/PP", "response_count": 1},
{"response": 500, "request": "/PP", "response_count": 1},
{"response": 200, "request": "/CP", "response_count": 2},
{"response": 500, "request": "/CP", "response_count": 6},
{"response": 503, "request": "/CP", "response_count": 3},
]
Your second aggregation takes this, groups by "request", and adds "response_c" in each group, which looks like this:
[
{"request": "/ST", "response_c": 2},
{"request": "/PP", "response_c": 2},
{"request": "/CP", "response_c": 3},
]
Notice that any fields you don't reference in the aggregation are dropped.
Your specification then refers to fields that no longer exist in the dataset, which results in a blank chart.
You could fix this by specifying in the second aggregation what you want to happen with the fields that are dropped; for example, you could keep the sum of "response_count" and the minimum of "response" (open in editor):
{
"data": {
"values": [
{"response": 200, "request": "/ST"},
{"response": 500, "request": "/ST"},
{"response": 200, "request": "/PP"},
{"response": 500, "request": "/PP"},
{"response": 200, "request": "/CP"},
{"response": 200, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 503, "request": "/CP"},
{"response": 503, "request": "/CP"},
{"response": 503, "request": "/CP"}
]
},
"transform": [
{
"aggregate": [{"op": "count", "as": "response_count"}],
"groupby": ["response", "request"]
},
{
"aggregate": [
{"op": "count", "as": "response_c"},
{"op": "sum", "field": "response_count", "as": "response_count"},
{"op": "min", "field": "response", "as": "response"}
],
"groupby": ["request"]
}
],
"mark": "bar",
"encoding": {
"x": {"field": "response_count", "type": "quantitative", "stack": "zero"},
"y": {"field": "request", "type": "nominal"},
"color": {"field": "response", "type": "nominal"}
}
}
Better in this particular case might be to leave out the second aggregation altogether, in which case the second aggregation essentially happens visually via stacking of the bars (editor):
{
"data": {
"values": [
{"response": 200, "request": "/ST"},
{"response": 500, "request": "/ST"},
{"response": 200, "request": "/PP"},
{"response": 500, "request": "/PP"},
{"response": 200, "request": "/CP"},
{"response": 200, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 500, "request": "/CP"},
{"response": 503, "request": "/CP"},
{"response": 503, "request": "/CP"},
{"response": 503, "request": "/CP"}
]
},
"transform": [
{
"aggregate": [{"op": "count", "as": "response_count"}],
"groupby": ["response", "request"]
}
],
"mark": "bar",
"encoding": {
"x": {"field": "response_count", "type": "quantitative", "stack": "zero"},
"y": {"field": "request", "type": "nominal"},
"color": {"field": "response", "type": "nominal"}
}
}