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Diet Trase Coffee 2020
This notebook summarises the output of the Diet Trase Coffee model. It runs off a single file:
s3://trase-storage/diet-trase/diet-trase-results-2020.parquet
Here is a summary of the data:
FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))
| column_name | column_type | min | max | approx_unique | avg | std | q25 | q50 | q75 | count | null_percentage | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | branch | VARCHAR | 1.2 | 4 | 2 | 2204251 | 0 | |||||
| 1 | country_of_destination | VARCHAR | AFGHANISTAN | ZIMBABWE | 252 | 2204251 | 0 | |||||
| 2 | country_of_production_name | VARCHAR | ANGOLA | ZIMBABWE | 61 | 2204251 | 0 | |||||
| 3 | domestic_consumption_region_geocode | VARCHAR | 0101 | XX | 7496 | 2204251 | 0 | |||||
| 4 | domestic_consumption_region_level | FLOAT | 1.0 | 6.0 | 4 | 5.3594 | 1.31485 | 6 | 6 | 6 | 2204251 | 99.62 |
| 5 | domestic_consumption_region_name | VARCHAR | ABANCAY | ÚTICA | 6290 | 2204251 | 0 | |||||
| 6 | economic_bloc | VARCHAR | AFGHANISTAN | ZIMBABWE | 232 | 2204251 | 0 | |||||
| 7 | exporter_group_name | VARCHAR | 06678 | ZRII LLC SUCURSAL COLOMBIA | 2830 | 2204251 | 0.38 | |||||
| 8 | exporter_group_parent | VARCHAR | BENECKE COFFEE GMBH & CO. KG | WALTER MATTER | 33 | 2204251 | 76.54 | |||||
| 9 | exporter_label | VARCHAR | 06678 | ZRII LLC SUC COLOMBIA | 3462 | 2204251 | 0.38 | |||||
| 10 | exporter_name | VARCHAR | 06678 | ZRII LLC SUCURSAL COLOMBIA | 2943 | 2204251 | 0.38 | |||||
| 11 | exporter_node_id | INTEGER | 17890 | 15608568 | 3106 | 3.96188e+06 | 6.12949e+06 | 71821 | 619340 | 2.3049e+06 | 2204251 | 0.38 |
| 12 | fob | DOUBLE | 3.176467645129476e-05 | 354972528.0 | 2365011 | 9346.14 | 524447 | 97.4157 | 404.975 | 1706.95 | 2204251 | 0.38 |
| 13 | hs6 | VARCHAR | 090111 | 210112 | 6 | 2204251 | 0.38 | |||||
| 14 | importer_group | VARCHAR | 1 RED RANGER LLC | 新疆万达有限公司 [XINJIANG WANDA CO.,LTD] | 2824 | 2204251 | 0.38 | |||||
| 15 | importer_label | VARCHAR | “““““““TABYS”““” LTD,““” | ZYS GLOBAL LOJISTIK TIC LTD STI | 9356 | 2204251 | 0.38 | |||||
| 16 | importer_name | VARCHAR | 1 RED RANGER LLC | 新疆万达有限公司 [XINJIANG WANDA CO.,LTD] | 3003 | 2204251 | 0.38 | |||||
| 17 | is_domestic | BOOLEAN | false | true | 2 | 2204251 | 0 | |||||
| 18 | linear_programming_failure_reason | VARCHAR | Traceback (most recent call last): | 5 | 2204251 | 0.38 | ||||||
| File “/home/sagemaker-user/users/harry/TRASE_copy/trase/models/diet_trase/coffee_fullmodel/model.py”, line 205, in linear_programming | ||||||||||||
| allocation = linear_programming_for_country(supplychain, country) | ||||||||||||
| File “/home/sagemaker-user/users/harry/TRASE_copy/trase/models/diet_trase/coffee_fullmodel/model.py”, line 255, in linear_programming_for_country | ||||||||||||
| assert not dpop.empty, f”Missing population data for {country}” | ||||||||||||
| AssertionError: Missing population data for VIETNAM | ||||||||||||
| 19 | mass_tonnes | DOUBLE | 1.5803179420184944e-08 | 86638.6 | 1357430 | 3.56785 | 154.868 | 0.0323138 | 0.143559 | 0.632827 | 2204251 | 0.38 |
| 20 | mass_tonnes_raw_equivalent | DOUBLE | 1.5803179420184944e-08 | 107581.86044999973 | 1556769 | 4.37439 | 175.085 | 0.0333904 | 0.147416 | 0.650704 | 2204251 | 0 |
| 21 | padded | BOOLEAN | false | true | 2 | 2204251 | 0.38 | |||||
| 22 | padded_type | VARCHAR | partial_pad_hs6_prod_and_dest_countries | 4 | 2204251 | 0 | ||||||
| 23 | port_of_export_label | VARCHAR | 1088 BORDER GATE 1089 LS | ZANZIBAR AIRPORT | 278 | 2204251 | 0.38 | |||||
| 24 | port_of_export_name | VARCHAR | 1088 BORDER GATE 1089 LS | ZANZIBAR AIRPORT | 293 | 2204251 | 0 | |||||
| 25 | production_geocode | VARCHAR | 0101 | XX | 2100 | 2204251 | 0 | |||||
| 26 | production_geocode_level | FLOAT | 1.0 | 6.0 | 4 | 4.89429 | 1.48347 | 3 | 6 | 6 | 2204251 | 0.73 |
| 27 | production_geocode_name | VARCHAR | ABEJORRAL | Óleo | 2235 | 2204251 | 0 | |||||
| 28 | proportion | DOUBLE | 4.1587314263644594e-07 | 1.0 | 819 | 0.0197169 | 0.116376 | 0.000884097 | 0.00271244 | 0.00642852 | 2204251 | 0 |
| 29 | status | VARCHAR | LP FAILED | TO RESULTS | 3 | 2204251 | 0 | |||||
| 30 | year | BIGINT | 2020 | 2020 | 1 | 2020 | 0 | 2020 | 2020 | 2020 | 2204251 | 0 |
The model works on a country-by-country basis. Here is a summary of the outcome of each country:
| branch | status | number of countries | countries |
|---|---|---|---|
| 1.2 | LP FAILED | 4 | VIETNAM, ETHIOPIA, COTE D’IVOIRE, UGANDA |
| 1.2 | LP SUCCEEDED | 6 | INDIA, PERU, COLOMBIA, TANZANIA, INDONESIA, BRAZIL |
| 4 | TO RESULTS | 47 | MALAYSIA, SRI LANKA, GUYANA, UNITED STATES, NEPAL, GABON, PHILIPPINES, DOMINICA ISLAND, HONDURAS, COSTA RICA, EL SALVADOR, FRENCH POLYNESIA, LAO PEOPLE’S DEMOCRATIC REPUBLIC, TRINIDAD AND TOBAGO, FIJI, GUATEMALA, RWANDA, PARAGUAY, CAMBODIA, CHINA (MAINLAND), SAO TOME AND PRINCIPE, ZAMBIA, TOGO, CUBA, DOMINICAN REPUBLIC, MADAGASCAR, BOLIVIA, BURUNDI, TIMOR-LESTE, NICARAGUA, JAMAICA, MALAWI, CAMEROON, MEXICO, MOZAMBIQUE, ANGOLA, BELIZE, THAILAND, NIGERIA, PANAMA, ZIMBABWE, PAPUA NEW GUINEA, ECUADOR, BENIN, KENYA, MYANMAR, CONGO DEMOCRATIC REPUBLIC OF THE |
Quality assurance check: each country should have exactly one status and branch. It cannot be that a country has a mix of statuses and branches. Checking this is the case and reporting back:
✅ Looks good