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Brazil soy supply sheds input data
This notebook is a simple summary of the input data to the supply sheds model for Brazil soy.
Extracting data from source ... took 0.2 seconds
Skipping re-process of Municipality
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Skipping re-process of Production
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Running pre-processing for CrushingCapacity
Report: Before processing
| Row Count: 1,791
Report: Filtered to 2022
| Row Count: 109
Report: Dropping zero or missing capacity
| Row Count: 109
| Sum of capacity: 73,000,000
Report: Consolidate over municipality
| Row Count: 82
Report: After processing
| Row Count: 82
Written /Users/harrybiddle/dev/TRASE/trase/models/brazil/soy_supply_sheds/2023/prepared/crushing_capacity.csv
Extracting data from source ...
/Users/harrybiddle/dev/TRASE/trase/tools/etl/pandas_wrapper.py:397: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
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Skipping re-process of Cost
Loading data from disk took 11.9 seconds
Extracting data from source ... took 0.2 seconds
Skipping re-process of Flows
| Category | Value | Value (2sf) |
|---|---|---|
| Production (tn) | 152,144,238 | 150,000,000 |
| Storage capacity (tn) | 116,767,634 | 120,000,000 |
| Crushing capacity (tn) | 73,000,000 | 73,000,000 |
How well does crushing capacity align with storage capacity?
Overall Crush-to-Storage Ratio (crush / storage): 0.6252
Correlation between storage and crushing capacity: 0.4190
Per-Municipality Ratio Analysis:
| storage_capacity | crushing_capacity | crush_to_storage_ratio | |
|---|---|---|---|
| count | 1405 | 1405 | 1398 |
| mean | 83108.6 | 51957.3 | 1.44971 |
| std | 201464 | 295976 | 36.4854 |
| min | 0 | 0 | 0 |
| 25% | 8100 | 0 | 0 |
| 50% | 25790 | 0 | 0 |
| 75% | 70740 | 0 | 0 |
| max | 2.85643e+06 | 5.8765e+06 | 1351.85 |
Identifying Key Municipalities & Imbalances
Top 5 Municipalities by Storage Capacity:
| storage_capacity | municipality.trase_id | municipality.name | _id | crushing_capacity | crush_to_storage_ratio | |
|---|---|---|---|---|---|---|
| 1289 | 2.85643e+06 | BR-5107925 | SORRISO | 1289 | 438000 | 0.153338 |
| 1258 | 2.11446e+06 | BR-5106224 | NOVA MUTUM | 1258 | 1.825e+06 | 0.863105 |
| 1273 | 1.95487e+06 | BR-5107040 | PRIMAVERA DO LESTE | 1273 | 1.095e+06 | 0.560138 |
| 1173 | 1.92623e+06 | BR-5003702 | DOURADOS | 1173 | 1.898e+06 | 0.985343 |
| 1288 | 1.8591e+06 | BR-5107909 | SINOP | 1288 | 0 | 0 |
Top 5 Municipalities by Crushing Capacity:
| storage_capacity | municipality.trase_id | municipality.name | _id | crushing_capacity | crush_to_storage_ratio | |
|---|---|---|---|---|---|---|
| 1280 | 727888 | BR-5107602 | RONDONOPOLIS | 1280 | 5.8765e+06 | 8.07336 |
| 1378 | 1.49563e+06 | BR-5218805 | RIO VERDE | 1378 | 3.4675e+06 | 2.31842 |
| 646 | 821790 | BR-4119905 | PONTA GROSSA | 646 | 3.358e+06 | 4.0862 |
| 1058 | 145722 | BR-4315602 | RIO GRANDE | 1058 | 2.628e+06 | 18.0343 |
| 241 | 981293 | BR-3170206 | UBERLANDIA | 241 | 2.5185e+06 | 2.56651 |
Municipalities with Crushing Capacity but NO Storage:
| storage_capacity | municipality.trase_id | municipality.name | _id | crushing_capacity | crush_to_storage_ratio | |
|---|---|---|---|---|---|---|
| 1398 | 0 | BR-1301902 | ITACOATIARA | nan | 730000 | nan |
| 1399 | 0 | BR-2914406 | IRAQUARA | nan | 328500 | nan |
| 1400 | 0 | BR-3539202 | PIRAPOZINHO | nan | 109500 | nan |
| 1401 | 0 | BR-4118204 | PARANAGUA | nan | 730000 | nan |
| 1402 | 0 | BR-4307708 | ESTEIO | nan | 219000 | nan |
Municipalities with Storage Capacity but NO Crushing:
| storage_capacity | municipality.trase_id | municipality.name | _id | crushing_capacity | crush_to_storage_ratio | |
|---|---|---|---|---|---|---|
| 0 | 16780 | BR-1100023 | ARIQUEMES | 0 | 0 | 0 |
| 1 | 4180 | BR-1100031 | CABIXI | 1 | 0 | 0 |
| 2 | 38637 | BR-1100049 | CACOAL | 2 | 0 | 0 |
| 3 | 1490 | BR-1100072 | CORUMBIARA | 3 | 0 | 0 |
| 4 | 27090 | BR-1100122 | JI-PARANA | 4 | 0 | 0 |
Now we plot crushing versus storage capacity. The below plot is a scatter, where each municipality is a dot. The x-axis represents storage capacity and the y-axis crushing capacity. Since the capacities span a huge range, both axes are log-scale.
The plot shows three distinct clusters of data points:
- “Storage Only” (points on bottom line). Municipalities that have storage capacity but zero crushing capacity - the largest group. This could represent gaps in the crushing data, or legitimately represent municipalities with storage but no crushing.
- “Crushing Only” (points on left line). Municipalities that have crushing capacity but zero storage capacity. This is a smaller group that most likely represents gaps in our storage data.
- “Mixed Capacity” (upper-right quadrant). These are the municipalities that have both storage and crushing capacity. There is a loose correlation between storage and crushing capacity.