São José Do Rio ClaroMunicipality in Mato Grosso State in Brazil
Exports (2019): $64.3M, Rnk 425/2197
Top Destination (2019): $14.2M, China
Top Export (2019): $44.5M, Soybeans
Imports (2019): $32.2k, Rnk 1689/2197
Top Origin (2019): $32.2k, United States
Top Import (2019): $30.1k, Glues
Exports: In 2019, Brazil's São José Do Rio Claro exported $64.3M, making it the 425th largest exporter out of the 2197 exporters in Brazil. In 2019 the top exports of São José Do Rio Claro were Soybeans ($44.5M), Corn ($16.6M), and Sawn Wood ($3.25M).
Imports: In 2019, Brazil's São José Do Rio Claro imported $32.2k, making it the 1689th largest importer out of the 2197 importers in Brazil. In 2019 top imports of São José Do Rio Claro were Glues ($30.1k), Sulfonated, Nitrated or Nitrosated Hydrocarbons ($1.81k), and Machinery Having Individual Functions ($234).
In 2019 the top export destinations of São José Do Rio Claro were China ($14.2M), Saudi Arabia ($11.8M), Netherlands ($10.2M), Mexico ($6.75M), and Turkey ($3.92M).
In 2019 the top exports of São José Do Rio Claro were Soybeans ($44.5M), Corn ($16.6M), and Sawn Wood ($3.25M).
Fastest Growing Exports Destination (May 2019 - May 2020): Algeria , $1.29M (100%)
Rapidly Declining Export Origins (May 2019 - May 2020)
Top Origin (2019): United States, $32.2k
Top Import (2019): Glues, $30.1k
In 2019 the top import origins of São José Do Rio Claro were United States ($32.2k).
In 2019 the top imports of São José Do Rio Claro were Glues ($30.1k), Sulfonated, Nitrated or Nitrosated Hydrocarbons ($1.81k), and Machinery Having Individual Functions ($234).
The municipalities of Brazil with the highest exports in 2019 were Rio De Janeiro ($11.3B), Duque De Caxias ($10.4B), Parauapebas ($7.02B), Canaã Dos Carajás ($4.93B), and São Paulo ($4.14B)
The municipalities of Brazil with the highest imports in 2019 were Manaus ($10.1B), São Paulo ($10.1B), Rio De Janeiro ($9.48B), Itajaí ($7.3B), and Macaé ($5.31B)
This section shows forecasts for total exports and imports from São José do Rio Claro. The forecast is based in a Long Short-Term Memory Model constructed using monthly trade data.
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