Add 2020-2025 data

Reorganized data files and added 2020-2025 customs data.

.gitattributes

@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
 boc_lite_*.csv filter=lfs diff=lfs merge=lfs -text
+yearly/csv/*.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -16,9 +16,9 @@ size_categories:
 
 ## Dataset Summary
 
-This dataset contains **20,255,360 import transactions** from the Bureau of Customs of the Philippines spanning from **2012 to 2019**. It represents a comprehensive record of goods imported into the Philippines, including detailed information on product classifications, values, duties paid, countries of origin, and ports of entry.
+This dataset contains **65,163,468 import transactions** from the Bureau of Customs of the Philippines spanning from **2012 to 2025**. It represents a comprehensive record of goods imported into the Philippines, including detailed information on product classifications, values, duties paid, countries of origin, and ports of entry.
 
-The data was extracted from the Bureau of Customs' electronic2mobile (e2m) system and has been cleaned and standardized for research purposes. This "lite" version contains 30 variables selected from the original 52 variables in the complete dataset, focusing on the most analytically useful fields while excluding sensitive information such as importer identities.
+The data was extracted from the Bureau of Customs' electronic2mobile (e2m) system and has been cleaned, standardized, and unified for research purposes. The original 2012-2019 data contains 20,255,360 transactions with 30 variables, while the extended 2020-2025 data adds 44,908,108 transactions. All data has been combined into a unified schema with 37 columns.
 
 ## Languages
 
@@ -28,140 +28,179 @@ The dataset is primarily in English (`en`).
 
 ### Data Instances
 
-The dataset is split into 8 CSV files, one for each year from 2012 to 2019.
+The unified dataset is available in Parquet format combining all years from 2012 to 2025. The data follows a standardized schema across all years with 37 columns.
 
+Example record structure:
 ```json
 {
+  "year": 2012,
+  "month": null,
+  "quarter": 1,
+  "month_code": null,
   "uid": "2012q1 00000001",
-  "ty": 2012,
-  "tq": "2012q1",
-  "tm": null,
-  "entry": "C",
-  "hscode": "15119090000",
-  "goodsdescription": "PALM OLEIN IN BULK",
-  "p": 0.97359568,
-  "q": 2499867,
-  "m_fob": 2433859.8,
-  "m_cif": 2486856.3,
-  "fx_usd": 1,
-  "dutiablevalueforeign": 2486856.15,
-  "exchangerate": 43.921,
+  "entry_number": null,
+  "hs_code": "15119090000",
+  "goods_description": "PALM OLEIN IN BULK",
+  "country_origin": "MYS",
+  "country_export": "MYS",
+  "quantity": 2499867,
+  "unit_of_measure": null,
+  "unit_price": 0.97359568,
+  "gross_mass_kg": null,
+  "net_mass_kg": null,
   "currency": "USD",
-  "dutiablevaluephp": 109225209,
-  "dutypaid": 0,
-  "exciseadvalorem": 0,
+  "dutiable_value_foreign": 2486856.15,
+  "exchange_rate": 43.921,
+  "dutiable_value_php": 109225209,
+  "customs_value": null,
+  "fx_usd": 1,
+  "fob_value": 2433859.8,
+  "cif_value": 2486856.3,
+  "freight": null,
+  "insurance": null,
   "arrastre": 274985,
   "wharfage": null,
-  "vatbase": 112934962,
-  "vatpaid": 13552195,
-  "othertax": null,
-  "finesandpenalties": null,
-  "dutiestaxes": 13552195,
-  "prefcode": "AFTA",
-  "countryorigin_iso3": "MYS",
-  "countryexport_iso3": "MYS",
-  "subport": null,
-  "port": null
+  "duty": 0,
+  "vat_base": 112934962,
+  "vat": 13552195,
+  "excise_ad_valorem": 0,
+  "duties_taxes_total": 13552195,
+  "other_tax": null,
+  "fines_penalties": null,
+  "preference_code": "AFTA",
+  "port": null,
+  "subport": null
 }
 ```
 
 ### Data Fields
 
+The unified schema contains 37 columns standardized across all years (2012-2025):
+
 | Field | Description | Data Type |
 |-------|-------------|-----------|
-| `uid` | Unique identifier for each transaction (format: YYYYqQ XXXXXXXX) | string |
-| `ty` | Transaction year (2012-2019) | integer |
-| `tq` | Transaction quarter (e.g., "2012q1") | string |
-| `tm` | Transaction month | string |
-| `entry` | Entry type: C (Consumption), W (Warehousing), T (Transshipment), C-Temp (Consumption-Temporary) | string |
-| `hscode` | 11-digit ASEAN Harmonized Tariff Nomenclature (AHTN) code | string |
-| `goodsdescription` | Text description of the imported goods | string |
-| `p` | Unit price (dutiable value / quantity) in USD | float |
-| `q` | Quantity of goods imported | float |
-| `m_fob` | Free on Board value in USD | float |
-| `m_cif` | Cost, Insurance, and Freight value in USD | float |
-| `fx_usd` | Exchange rate to convert foreign currency to USD | float |
-| `dutiablevalueforeign` | Dutiable value in foreign currency | float |
-| `exchangerate` | Exchange rate to convert to Philippine Peso | float |
-| `currency` | Original currency code of the transaction | string |
-| `dutiablevaluephp` | Dutiable value in Philippine Peso | float |
-| `dutypaid` | Customs duty paid in PHP | float |
-| `exciseadvalorem` | Ad valorem excise tax paid in PHP | float |
-| `arrastre` | Arrastre (cargo handling) charges in PHP | float |
-| `wharfage` | Wharfage fees in PHP | float |
-| `vatbase` | Base amount for VAT computation in PHP | float |
-| `vatpaid` | Value Added Tax paid in PHP | float |
-| `othertax` | Other taxes paid in PHP | float |
-| `finesandpenalties` | Fines and penalties assessed in PHP | float |
-| `dutiestaxes` | Total duties and taxes paid in PHP | float |
-| `prefcode` | Preferential trade agreement code (e.g., AFTA, ACFTA, JPEPA, AKFTA, AANZFTA, PJEPA, AIFTA, GSP) | string |
-| `countryorigin_iso3` | ISO 3166-1 alpha-3 code for country of origin | string |
-| `countryexport_iso3` | ISO 3166-1 alpha-3 code for country of export | string |
-| `subport` | Subport of entry code | string |
-| `port` | Port of entry code | string |
+| `year` | Transaction year (2012-2025) | Int32 |
+| `month` | Transaction month (1-12) | Int32 |
+| `quarter` | Transaction quarter (1-4) | Int32 |
+| `month_code` | Month code identifier | String |
+| `uid` | Unique identifier for each transaction | String |
+| `entry_number` | Entry declaration number | String |
+| `hs_code` | Harmonized System tariff code (typically 11-digit AHTN) | String |
+| `goods_description` | Text description of the imported goods | String |
+| `country_origin` | Country of origin (ISO 3166-1 alpha-3 code or full name) | String |
+| `country_export` | Country of export (ISO 3166-1 alpha-3 code or full name) | String |
+| `quantity` | Quantity of goods imported | Float64 |
+| `unit_of_measure` | Unit of measurement for quantity | String |
+| `unit_price` | Unit price (calculated as dutiable value / quantity) | Float64 |
+| `gross_mass_kg` | Gross mass in kilograms | Float64 |
+| `net_mass_kg` | Net mass in kilograms | Float64 |
+| `currency` | Original currency code of the transaction | String |
+| `dutiable_value_foreign` | Dutiable value in foreign currency | Float64 |
+| `exchange_rate` | Exchange rate to convert to Philippine Peso | Float64 |
+| `dutiable_value_php` | Dutiable value in Philippine Peso | Float64 |
+| `customs_value` | Customs valuation amount | Float64 |
+| `fx_usd` | Exchange rate to convert foreign currency to USD | Float64 |
+| `fob_value` | Free on Board value in USD | Float64 |
+| `cif_value` | Cost, Insurance, and Freight value in USD | Float64 |
+| `freight` | Freight charges | Float64 |
+| `insurance` | Insurance charges | Float64 |
+| `arrastre` | Arrastre (cargo handling) charges in PHP | Float64 |
+| `wharfage` | Wharfage fees in PHP | Float64 |
+| `duty` | Customs duty paid in PHP | Float64 |
+| `vat_base` | Base amount for VAT computation in PHP | Float64 |
+| `vat` | Value Added Tax paid in PHP | Float64 |
+| `excise_ad_valorem` | Ad valorem excise tax paid in PHP | Float64 |
+| `duties_taxes_total` | Total duties and taxes paid in PHP | Float64 |
+| `other_tax` | Other taxes paid in PHP | Float64 |
+| `fines_penalties` | Fines and penalties assessed in PHP | Float64 |
+| `preference_code` | Preferential trade agreement code (e.g., AFTA, ACFTA, JPEPA, AKFTA, AANZFTA) | String |
+| `port` | Port of entry code | String |
+| `subport` | Subport of entry code | String |
 
 ### Data Splits
 
-The dataset is provided as yearly splits without predefined train/validation/test splits to allow researchers flexibility in their analysis:
-
-| Year | File | Size | Transactions |
-|------|------|------|--------------|
-| 2012 | boc_lite_2012.csv | 196 MB | 1,193,628 |
-| 2013 | boc_lite_2013.csv | 206 MB | 1,225,431 |
-| 2014 | boc_lite_2014.csv | 260 MB | 1,421,241 |
-| 2015 | boc_lite_2015.csv | 471 MB | 2,236,612 |
-| 2016 | boc_lite_2016.csv | 657 MB | 3,140,436 |
-| 2017 | boc_lite_2017.csv | 717 MB | 3,490,131 |
-| 2018 | boc_lite_2018.csv | 644 MB | 3,753,118 |
-| 2019 | boc_lite_2019.csv | 671 MB | 3,794,763 |
-| **Total** | | **3.8 GB** | **20,255,360** |
+The complete unified dataset spans 2012-2025 with yearly distribution:
+
+| Year | Transactions | Percentage |
+|------|--------------|------------|
+| 2012 | 1,193,628 | 1.83% |
+| 2013 | 1,225,431 | 1.88% |
+| 2014 | 1,421,241 | 2.18% |
+| 2015 | 2,236,612 | 3.43% |
+| 2016 | 3,140,436 | 4.82% |
+| 2017 | 3,490,131 | 5.36% |
+| 2018 | 3,753,118 | 5.76% |
+| 2019 | 3,794,763 | 5.82% |
+| 2020 | 3,173,563 | 4.87% |
+| 2021 | 6,813,301 | 10.46% |
+| 2022 | 8,031,537 | 12.33% |
+| 2023 | 8,467,089 | 12.99% |
+| 2024 | 8,992,137 | 13.80% |
+| 2025 | 9,430,481 | 14.47% |
+| **Total** | **65,163,468** | **100%** |
+
+**Original Source Data:**
+- 2012-2019: 8 CSV files totaling 3.8 GB with 20,255,360 transactions
+- 2020-2025: 6 yearly partitioned Parquet files totaling 44,908,108 transactions
 
 ### Parquet Files
 
-The dataset is also available in Apache Parquet format for improved query performance and reduced storage. Two formats are provided:
+The dataset is available in Apache Parquet format for improved query performance and reduced storage.
 
-#### Single Combined File
+#### Unified Combined File (2012-2025)
 
-`boc_lite_combined.parquet` contains all 20+ million transactions in a single file (~1.4 GB).
+`combined.parquet` contains all 65+ million transactions with a unified schema in a single file (4.92 GB).
 
-**Best for:** Full dataset queries, cross-year analysis, and environments where a single file is preferred.
+**Best for:** Full dataset queries, cross-year analysis, and comprehensive research requiring all historical data.
 
 ```python
 # Python - Polars
 import polars as pl
-df = pl.read_parquet('boc_lite_combined.parquet')
+df = pl.read_parquet('combined.parquet')
 
 # Python - Pandas
 import pandas as pd
-df = pd.read_parquet('boc_lite_combined.parquet')
+df = pd.read_parquet('combined.parquet')
 
 # DuckDB
-SELECT * FROM 'boc_lite_combined.parquet' WHERE ty = 2015 LIMIT 10;
+SELECT * FROM 'combined.parquet' WHERE year = 2024 LIMIT 10;
 ```
 
-#### Yearly Parquet Files
-
-`boc_lite_partitioned/` contains separate parquet files for each year.
-
-| File | Size |
-|------|------|
-| 2012.parquet | 86 MB |
-| 2013.parquet | 89 MB |
-| 2014.parquet | 105 MB |
-| 2015.parquet | 156 MB |
-| 2016.parquet | 222 MB |
-| 2017.parquet | 252 MB |
-| 2018.parquet | 268 MB |
-| 2019.parquet | 273 MB |
-
-**Best for:** Year-specific queries, incremental processing, and memory-constrained environments.
+**Key Statistics:**
+- Total rows: 65,163,468
+- Total columns: 37
+- Unique HS codes: 20,639
+- Date range: 2012-2025
+- Total dutiable value: ₱103 trillion
+- Total duties & taxes: ₱15.3 trillion
+
+#### Yearly Partitioned Files
+
+`yearly/parquet/` contains separate files for each year:
+
+| File | Size | Transactions |
+|------|------|--------------|
+| 2012.parquet | 86 MB | 1,193,628 |
+| 2013.parquet | 89 MB | 1,225,431 |
+| 2014.parquet | 105 MB | 1,421,241 |
+| 2015.parquet | 156 MB | 2,236,612 |
+| 2016.parquet | 222 MB | 3,140,436 |
+| 2017.parquet | 252 MB | 3,490,131 |
+| 2018.parquet | 268 MB | 3,753,118 |
+| 2019.parquet | 273 MB | 3,794,763 |
+| 2020.parquet | - | 3,173,563 |
+| 2021.parquet | - | 6,813,301 |
+| 2022.parquet | - | 8,031,537 |
+| 2023.parquet | - | 8,467,089 |
+| 2024.parquet | - | 8,992,137 |
+| 2025.parquet | - | 9,430,481 |
 
 ```python
 # Read all years
-df = pl.read_parquet('boc_lite_partitioned/*.parquet')
+df = pl.read_parquet('yearly/parquet/*.parquet')
 
 # Read specific year
-df_2015 = pl.read_parquet('boc_lite_partitioned/2015.parquet')
+df_2024 = pl.read_parquet('yearly/parquet/2024.parquet')
 ```
 
 ## Dataset Creation
@@ -172,32 +211,89 @@ df_2015 = pl.read_parquet('boc_lite_partitioned/2015.parquet')
 
 The data was extracted from the Bureau of Customs' electronic2mobile (e2m) system, which is the official electronic customs processing system in the Philippines.
 
+**2012-2019 Data:** Original dataset published by Ken Abante (2020), containing 20,255,360 transactions extracted from the e2m system.
+
+**2020-2025 Data:** Extended dataset obtained from the Bureau of Customs via their OneDrive repository at https://customsph-my.sharepoint.com/personal/delakrusj_customs_gov_ph/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fdelakrusj%5Fcustoms%5Fgov%5Fph%2FDocuments%2FImport%20Entries&ga=1, containing 44,908,108 additional transactions.
+
 ### Annotations
 
-This dataset does not contain additional annotations beyond the original customs declaration data.
+#### Data Enrichment and Unification
+
+To create a unified dataset spanning 2012-2025, the following transformations and annotations were applied:
+
+**2020-2025 Data Processing:**
+- **Year and month extraction:** Year and month columns were extracted from the original Excel filenames (format: YYYY-MM) and added as separate columns to enable temporal analysis
+- **Source format:** Original data provided as Excel (.xlsx) files, one per month, converted to Parquet format
+- **Schema standardization:** Column names and data types were standardized to match the unified 37-column schema
+
+**Schema Unification (2012-2025):**
+- Columns from both data sources (2012-2019 and 2020-2025) were mapped to a common schema with 37 unified columns
+- Column name standardization: Original column names were converted to snake_case format (e.g., `dutiablevaluephp` → `dutiable_value_php`)
+- Data type normalization: All numeric fields standardized to Float64, temporal fields to Int32, and identifiers to String
+- Country code handling: Both ISO 3166-1 alpha-3 codes and full country names are preserved in `country_origin` and `country_export` fields
+- Missing column handling: Columns present in one dataset but not the other are filled with null values
+
+**Column Mappings:**
+- 2012-2019: `ty` → `year`, `tm` → `month`, `tq` → `quarter`
+- 2012-2019: `hscode` → `hs_code`, `goodsdescription` → `goods_description`
+- 2012-2019: `countryorigin_iso3` → `country_origin`, `countryexport_iso3` → `country_export`
+- 2012-2019: `p` → `unit_price`, `q` → `quantity`
+- 2012-2019: `dutypaid` → `duty`, `vatpaid` → `vat`, `vatbase` → `vat_base`
+- 2012-2019: `m_fob` → `fob_value`, `m_cif` → `cif_value`
+- 2012-2019: `dutiestaxes` → `duties_taxes_total`, `prefcode` → `preference_code`
+- 2012-2019: `finesandpenalties` → `fines_penalties`, `othertax` → `other_tax`
+
 ### Parquet Aggregation
 
-The Parquet files were generated from the original CSV files using Polars (>=0.20.0) with the following process:
+#### Unified Dataset Generation
+
+The unified Parquet file (`combined.parquet`) was generated using Polars (>=0.20.0) with the following process:
+
+1. **Multi-source ingestion:**
+   - 2012-2019 data: Read from 8 CSV files
+   - 2020-2025 data: Read from yearly partitioned Parquet files with year/month metadata extracted from source Excel filenames
 
-1. **Schema normalization:** Explicit schema overrides ensure consistent data types across all years, addressing discrepancies in how columns were typed in different yearly files:
-   - Numeric fields (`p`, `q`, `m_fob`, `m_cif`, `dutiablevalueforeign`, `exchangerate`, `dutiablevaluephp`, `dutypaid`, `exciseadvalorem`, `arrastre`, `wharfage`, `vatbase`, `vatpaid`, `othertax`, `finesandpenalties`, `dutiestaxes`) are normalized to `Float64`
-   - The `hscode` field is kept as `String` to preserve leading zeros in tariff codes
-   - The `ty` (transaction year) field is normalized to `Int64`
+2. **Schema unification:** All source data mapped to a common 37-column schema:
+   - Numeric fields standardized to `Float64` (prices, values, duties, taxes, quantities, masses)
+   - Temporal fields standardized to `Int32` (year, month, quarter)
+   - Text fields standardized to `String` (codes, descriptions, country identifiers)
+   - HS codes preserved as `String` to maintain leading zeros in tariff codes
 
-2. **Character encoding:** UTF-8 lossy encoding is applied to handle invalid byte sequences present in some source records, replacing malformed characters rather than failing on read
+3. **Column mapping and renaming:**
+   - Legacy column names (e.g., `ty`, `dutypaid`, `vatpaid`) mapped to unified names (e.g., `year`, `duty`, `vat`)
+   - Snake_case naming convention applied consistently across all columns
+   - Missing columns in either source filled with null values
 
-3. **Ragged line handling:** Lines with inconsistent column counts are truncated to match the expected schema, ensuring robust parsing of the source data
+4. **Data quality handling:**
+   - UTF-8 lossy encoding applied to handle invalid byte sequences
+   - Ragged line handling for inconsistent column counts in CSV sources
+   - Null value preservation for missing or incomplete data
 
-4. **Streaming aggregation:** Lazy evaluation and streaming writes (`sink_parquet`) are used to process the full dataset without loading all 20+ million rows into memory
+5. **Streaming aggregation:** Lazy evaluation and streaming operations used to process 65+ million rows without exceeding memory constraints
 
-5. **Compression:** Snappy compression is applied, achieving approximately 63% size reduction compared to the original CSV files (from ~3.8 GB to ~1.4 GB)
+6. **Compression:** Snappy compression applied to the unified file (4.92 GB total size)
 
-6. **Partitioning:** For the partitioned output, data is filtered by transaction year (`ty`) and written to separate yearly files (`YYYY.parquet`)
+7. **Statistics:** Column statistics embedded in Parquet metadata to enable query optimization and predicate pushdown
 
-7. **Statistics:** Column statistics are embedded in the Parquet files to enable predicate pushdown and query optimization
+#### Yearly Parquet Generation
+
+The yearly Parquet files were generated with:
+- Schema normalization ensuring consistent data types across years
+- Snappy compression reducing storage requirements
+- Yearly partitioning for efficient year-specific queries
 
 ## Additional Information
 
 ### Citation Information
 
-Abante, Ken. (2020). An Open Data Set of Twenty Million Import Transactions from the Bureau of Customs of the Philippines (2012-2019). 10.13140/RG.2.2.24053.73444.
+**For the unified dataset (2012-2025):**
+
+Bureau of Customs of the Philippines. (2012-2025). Import Transaction Records. Combined and unified dataset.
+
+**For the original 2012-2019 dataset:**
+
+Abante, Ken. (2020). An Open Data Set of Twenty Million Import Transactions from the Bureau of Customs of the Philippines (2012-2019). doi:10.13140/RG.2.2.24053.73444.
+
+**Data Sources:**
+- 2012-2019: Abante, K. (2020) via ResearchGate
+- 2020-2025: Bureau of Customs of the Philippines OneDrive Repository (https://customsph-my.sharepoint.com/personal/delakrusj_customs_gov_ph/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fdelakrusj%5Fcustoms%5Fgov%5Fph%2FDocuments%2FImport%20Entries&ga=1)

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