ImportYeti
PowerQuery
GET

Rank Mexico import companies

1 per 10 records

Aggregate Mexico import declarations into a ranked list of Mexican importers.

Parameters#

Query parameters

28 parameters
  • page_sizenumberoptionaldefault 10

    Number of returned results

  • offsetnumberoptionaldefault 0

    Results starting position

  • start_datestringoptionaldefault 01/01/2021
  • end_datestringoptionaldefault 08/31/2026
  • pagenumberoptional

    Page number (1-indexed). Takes precedence over offset.

  • company_namestringoptional
  • supplier_namestringoptional
  • product_descriptionstringoptional

    Supports boolean operators and wildcards

    AND / OR / NOTwildcards * ?
  • weightstringoptional

    Supports ranges

    ranges [a TO b]
  • company_total_shipmentsstringoptional

    Supports ranges

    ranges [a TO b]
  • supplier_total_shipmentsstringoptional

    Supports ranges

    ranges [a TO b]
  • who_pays_freightstringoptionaldefault Foreign entity

    Foreign entity / Mexico entity

    one ofForeign entityMexico entity

fields, exclude, and format work the same way on every endpoint — Response shaping has worked examples.

Response#

A volume-ranked list of Mexican importers that match your filters.

Response shape
{
  "requestCost": 1,
  "creditsRemaining": 9998.5,
  "data": {
    "data": [
      {
        "company_name": "Automotive Bend De Mexico De",
        "total_shipments": 1416801,
        "name_variations": ["Automotive Bend De Mexico S De Rl De Cv", "Automotive Bend De Mexico S De R.L. De C.V"],
        "company_country_code": "MX",
        "company_country": "Mexico",
        "product_descriptions": ["Desperdicio Aluminio", "Juntas Aluminio", "Accesorios Tuberia Aluminio"],
        "incoterms": ["DAP", "DDP", "DPU"],
        "transport_types": ["Undeclared", "Truck", "Sea"]
        // …3 more fields
      }
    ],
    "totalCompanies": 59583
  },
  "executionTime": "224ms"
}

Rows are nested one level deeper

PowerQuery routes put the records at data.data — not at data. The total number of matches is on data.totalCompanies, which is the value you page against. Note that this key is named per route family (totalCount, totalCompanies, totalSuppliers, totalBrokers).

Top-level fields#

  • data — an object holding the result rows (data.data) and the match total (data.totalCompanies)
  • requestCost — Data credits used for this call (0 if none)
  • creditsRemaining — Your data credit balance after the call
  • executionTime — How long the request took
  • totalCompanies — Total matching companies, not just this page

Fields on each row in data.data#

FieldExample
11 fields
  • company_namestringAutomotive Bend De Mexico De
  • total_shipmentsnumber1416801

    The company's total shipments on record, independent of the filters in this query.

  • name_variationsstring[]["Automotive Bend De Mexico S De Rl De Cv", "Automotive Bend De Mexico S De R.L. De C.V"]
  • company_addressstring[]
  • company_country_codestringMX
  • company_countrystringMexico
  • customs_officesstring[]
  • product_descriptionsstring[]["Desperdicio Aluminio", "Juntas Aluminio", "Accesorios Tuberia Aluminio"]
  • incotermsstring[]["DAP", "DDP", "DPU"]
  • transport_typesstring[]["Undeclared", "Truck", "Sea"]
  • hs_codesstring[]["761699", "760200", "761610"]

Errors#

Failures come back as JSON with a statusCode and message. The ones worth handling here are 401 (bad or missing key), 403 (out of credits), and 404 (no such record). See all error responses.