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Date breakdown

How to perform a date breakdown query and how it works
Date breakdowns are aggregations that show the frequency of occurrence of a specific date value within a dataset and let you apply a specific operator over a selected field of the records that are present on that date. When performing a date breakdown query on the Metrics API endpoint you get in the response the list by date of the values of the computation (based on the selected operator) on the selected field, over the selected time interval, aggregated by another field.

Request

To perform a date breakdown query send a POST request to the /{{resource_name}}/date_breakdown endpoint specifying the query keys and filter parameters:
{
"date_breakdown": {
"by": "...",
"field": "...",
"operator": "...",
"interval": "...",
"breakdown": { ... }
},
"filter": { ... },
"meta": { ... }
}

Query keys

Key
Type
Required
Description
Values
by
String
The date field you want the results of the query aggragated by.
The available values for this key depend on the resource you're doing statistics on (see orders, returns, or carts for the related lists).
field
String
The field you want the metrics or statistics computed on.
The available values for this key depend on the resource you're doing statistics on (see orders, returns, or carts for the related lists).
operator
String
The computing operator.
The available operators depend on the field key value (see orders, returns, or carts for the related lists).
interval
String
The time interval over which the metrics / stats are computed. The results will be aggregated by date accordingly (read how).
One of hour, day, week, month, or year (default is month).
breakdown
object
The optional breakdown (eventually nested).
The nested breakdown by key available values depend of the parent breakdown by key value (see orders, returns, or carts for the related lists).

Nesting breakdowns

You can nest a breakdown query into a date breakdown one. This means you can request each aggregation by date over the selected time interval to be in turn aggregated by another field. Since the nested breakdown is a full-fledged breakdown query, it supports its own nesting (up to one level), as shown in the following example.
You cannot group the nested breakdown by the same field by which you're already grouping the parent breakdown.

Response

The response of a date breakdown query returns an aggregation by date over the time interval specified in the interval key, containing the value of the computation (based on the operator specified in the operator key) on the field specified in the field key. If the query contains a nested breakdown, it is also detailed for each item of the array:
{
"data": [
{
"date": "...",
"value": ...,
"...": [ // breakdown by
{
"label": "...",
"value": ...,
"...": [ // nested breakdown by
{
"label": "...",
"value": ...
},
{ ... }
]
},
{ ... }
]
},
{
"date": "...",
"value": ...,
"...": [ // breakdown by
{
"label": "...",
"value": ...,
"...": [ // nested breakdown by
{
"label": "...",
"value": ...
},
{ ... }
]
},
{ ... }
]
},
{ ... }
],
"meta": { ... }
}

Date intervals

The results of a date breakdown query are aggregated over the specified time intervals. You can identify them in the response by looking at the date keys:
{
"data": [
{
"date": "2021-04-01T00:00:00.000Z",
"value": { ... }
},
{
"date": "2021-05-01T00:00:00.000Z",
"value": { ... }
},
{ ... },
{
"date": "2021-09-01T00:00:00.000Z",
"value": { ... }
}
],
"meta": { ... }
}
Please note that those key values are only a reference to identify the related interval. In fact, each date key refers to the very beginning of the interval, regardless of the range specified in the date filter which instead will still be honored for the actual computation (e.g. if you set a date filter that starts on April 15th, 2021 and ends on September 7th, 2021 for a date breakdown by month on the order resource, the first date key will be 2021-04-01T00:00:00.000Z and the last 2021-09-01T00:00:00.000Z, but the stats computation will still count the orders from April 15th to September 7th).
Interval
Date key values
year
YYYY-01-01T00:00:00.000Z
month
YYYY-MM-01T00:00:00.000Z
day
YYYY-MM-DDT00:00:00.000Z
hour
YYYY-MM-DDTHH:00:00.000Z

Examples

The following examples will be focused on the query part of the request. So no specific filter or meta options will be defined (i.e. all the results will be filtered by the default filter and the response won't include the request payload). See the use cases section for more complex combinations of queries and filters.

Date breakdown

Request
Response
The following request performs a date breakdown query to get the stats about the orders placed by month:
curl -g -X POST \
'https://{{your_domain}}.commercelayer.io/metrics/orders/date_breakdown' \
-H 'Accept: application/vnd.api.v1+json' \
-H 'Content-Type: application/vnd.api+json' \
-H 'Authorization: Bearer {{your_access_token}}' \
-d '{
"date_breakdown": {
"by": "order.placed_at",
"field": "order.total_amount_with_taxes",
"operator": "stats",
"interval": "month"
}
}'
On success, the API responds with a 200 OK status code, returning the aggregated values over the selected time intervals in the data object and extra information in the meta object:
{
"data": [
{
"date": "2022-05-01T00:00:00.000Z",
"value": {
"count": 6,
"min": 65.0,
"max": 243.0,
"avg": 128.87,
"sum": 773.2
}
},
{
"date": "2022-06-01T00:00:00.000Z",
"value": {
"count": 132,
"min": 0.0,
"max": 325.0,
"avg": 78.33,
"sum": 10340.09
}
}
],
"meta": {
"type": "date_breakdown",
"trace_id": "b666478b-9c50-497b-a5e4-c7ed4dd7d7f3",
"mode": "test",
"organization_id": "xYZkjABcde",
"market_ids": [ "yzXKjYzaCx", "..." ]
}
}

Date breakdown with nested breakdown

Request
Response
The following request performs a date breakdown query to get the stats about the orders placed by month. Over each time interval, a breakdown of the orders' total amounts to check the maximum by country code is also requested. For each country code, a breakdown of the orders' total amounts to check the maximum by currency code (as long as it's over a specific threshold) is then requested:
curl -g -X POST \
'https://{{your_domain}}.commercelayer.io/metrics/orders/date_breakdown' \
-H 'Accept: application/vnd.api.v1+json' \
-H 'Content-Type: application/vnd.api+json' \
-H 'Authorization: Bearer {{your_access_token}}' \
-d '{
"date_breakdown": {
"by": "order.placed_at",
"field": "order.total_amount_with_taxes",
"operator": "stats",
"interval": "month",
"breakdown": {
"by": "order.country_code",
"field": "order.total_amount_with_taxes",
"operator": "max",
"sort": "desc",
"limit": 3,
"breakdown": {
"by": "order.currency_code",
"field": "order.total_amount_with_taxes",
"operator": "max",
"condition": {
"gt": 100
}
"sort": "desc",
"limit": 2
}
}
}
}'
On success, the API responds with a 200 OK status code, returning the aggregated values over the selected time intervals (nested accordingly) in the data object and extra information in the meta object:
{
"data": [
{
"date": "2022-05-01T00:00:00.000Z",
"value": {
"count": 6,
"min": 65.0,
"max": 243.0,
"avg": 128.87,
"sum": 773.2
},
"order.country_code": [
{
"label": "IT",
"value": 243.0,
"order.currency_code": [
{
"label": "EUR",
"value": 243.0
}
]
}
]
},
{
"date": "2022-06-01T00:00:00.000Z",
"value": {
"count": 132,
"min": 0.0,
"max": 925.0,
"avg": 78.33,
"sum": 10340.09
},
"order.country_code": [
{
"label": "IT",
"value": 925.0,
"order.currency_code": [
{
"label": "EUR",
"value": 925.0
}
]
},
{
"label": "NO",
"value": 855.0,
"order.currency_code": [
{
"label": "NOK",
"value": 855.0
},
{
"label": "EUR",
"value": 105.0
}
]
},
{
"label": "US",
"value": 278.72,
"order.currency_code": [
{
"label": "USD",
"value": 278.72
}
]
}
]
}
],
"meta": {
"type": "date_breakdown",
"trace_id": "0e8e8b2c-4d13-444e-bf5a-1501061b3010",
"mode": "test",
"organization_id": "xYZkjABcde",
"market_ids": [ "yzXKjYzaCx", "..." ]
}
}
Last modified 24d ago