datafair.cloud
datafair.cloud
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imperative implementation
Data Fair
First seen 2026-11-05 · Last seen 2026-11-05 · Source: webmcp.com
Answer 13 · Act 6 · Transact 0 · Score: Not yet scored
Tool inspector
calculate_metric
act
imperative
Calculate a single metric on a dataset column: avg, sum, min, max, stats, value_count, cardinality, percentiles. For per-group breakdowns, use aggregate_data.
Page: /
Input schema
| Property | Type | Required | Description |
|---|---|---|---|
datasetId |
string | yes | The exact dataset ID from the "id" field in list_datasets results. Do not use the title or slug. |
fieldKey |
string | yes | The column key to calculate the metric on (use keys from describe_dataset) |
metric |
string | yes | Metric to calculate. Available: avg, sum, min, max (for numbers); min, max, cardinality, value_count (for strings); value_count (for others); stats returns count/min/max/avg/sum; percentiles returns distribution. |
percents |
string | no | Comma-separated percentages for percentiles metric (default: "1,5,25,50,75,95,99"). Only used when metric is "percentiles". |
filters |
object | no | Column filters as key-value pairs: column_key + suffix, all values strings. Example: { "ville_eq": "Paris", "age_lte": "30", "nom_search": "Jean" }. Suffixes include _eq, _in, _gt/_lt, _search and more; if one is rejected the 400 error lists what the column supports. Never _c_-prefix a column filter (use ville_eq, not _c_ville_eq). |
bbox |
string | no | Bounding box "lonMin,latMin,lonMax,latMax" (lon before lat), e.g. "-2.5,43,3,47". Geolocalized datasets only. |
geoDistance |
string | no | Proximity filter "lon,lat,distance" (lon first), e.g. "2.35,48.85,10km"; distance "0" = point-in-polygon. Geolocalized datasets only. |
dateMatch |
string | no | Date "YYYY-MM-DD" (single day) or "YYYY-MM-DD,YYYY-MM-DD" (range), e.g. "2023-11-21". Temporal datasets only. |
Raw JSON schema
{
"type": "object",
"properties": {
"datasetId": {
"type": "string",
"description": "The exact dataset ID from the \"id\" field in list_datasets results. Do not use the title or slug."
},
"fieldKey": {
"type": "string",
"description": "The column key to calculate the metric on (use keys from describe_dataset)"
},
"metric": {
"type": "string",
"description": "Metric to calculate. Available: avg, sum, min, max (for numbers); min, max, cardinality, value_count (for strings); value_count (for others); stats returns count/min/max/avg/sum; percentiles returns distribution."
},
"percents": {
"type": "string",
"description": "Comma-separated percentages for percentiles metric (default: \"1,5,25,50,75,95,99\"). Only used when metric is \"percentiles\"."
},
"filters": {
"type": "object",
"description": "Column filters as key-value pairs: column_key + suffix, all values strings. Example: { \"ville_eq\": \"Paris\", \"age_lte\": \"30\", \"nom_search\": \"Jean\" }. Suffixes include _eq, _in, _gt/_lt, _search and more; if one is rejected the 400 error lists what the column supports. Never _c_-prefix a column filter (use ville_eq, not _c_ville_eq).",
"properties": {}
},
"bbox": {
"type": "string",
"description": "Bounding box \"lonMin,latMin,lonMax,latMax\" (lon before lat), e.g. \"-2.5,43,3,47\". Geolocalized datasets only."
},
"geoDistance": {
"type": "string",
"description": "Proximity filter \"lon,lat,distance\" (lon first), e.g. \"2.35,48.85,10km\"; distance \"0\" = point-in-polygon. Geolocalized datasets only."
},
"dateMatch": {
"type": "string",
"description": "Date \"YYYY-MM-DD\" (single day) or \"YYYY-MM-DD,YYYY-MM-DD\" (range), e.g. \"2023-11-21\". Temporal datasets only."
}
},
"required": [
"datasetId",
"fieldKey",
"metric"
]
}
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