--- license: cc-by-sa-4.0 language: - en task_categories: - tabular-classification - tabular-regression multilinguality: multilingual size_categories: - n<1K tags: - "tabular" - "africa" - "open-data" - "official-statistics" - "mauritius" - "mdpa" - "economics" - "finance-and-trade" - "budget" - "cib" - "cisd" - "mtci" - "itsu" configs: - config_name: default data_files: - split: train path: data/train-00000-of-00001.parquet pretty_name: "Budget Data Ministry of Technology Communication and Innov | Africa (MDPA)" --- # Budget Data Ministry of Technology Communication and Innov | Africa (MDPA) **236 rows** - **1 Africa country/area** - **2017** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)* ![rows](https://img.shields.io/badge/rows-236-blue) ![countries](https://img.shields.io/badge/countries-1-green) ![period](https://img.shields.io/badge/period-2017-orange) ![indicators](https://img.shields.io/badge/indicators-0-purple) ![license](https://img.shields.io/badge/license-cc--by--sa--4.0-lightgrey) ## TL;DR This dataset contains **236 rows** from **MDPA**, covering **Budget Data Ministry of Technology Communication and Innov**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. ## What This Dataset Measures Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change. Source-provided context: Budget Data for years 2016-2017, 2017-2018, 2018-2019 for MTCI, CISD, CIB and ITSU ## How To Read This Dataset - **One row means:** one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available. - **Primary geography column:** `country_iso3`. - **Best time column:** `year`. - **Time coverage basis:** year. - **Recommended join keys:** `country_iso3` where available plus source-specific keys. ## Coverage | Dimension | Value | |---|---:| | Rows | 236 | | Countries/areas | 1 | | First period | 2017 | | Last period | 2017 | | Indicators | 0 | | Columns | 24 | | Source format | XLSX | ## Geographic Coverage Top areas shown below, sorted by row count when available: | Area | Rows | First year | Last year | Name | |------|-----:|-----------:|----------:|------| | `MU` | 236 | 2017 | 2017 | `Mauritius` | ## Indicators, Variables, Or Resource Contents - This repo preserves one source tabular resource with its usable columns kept together. ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `source_record_id` | `string` | Stable row identifier assigned during Electric Sheep Africa engineering. | `d333faef-d9ab-40c6-bab7-ff26c8fa49eb:sheet1:0` | | `country_iso3` | `dictionary` | ISO3 country or area code. | `MU` | | `country_name` | `dictionary` | Country or area name. | `Mauritius` | | `source_sheet` | `string` | Source column from the original resource. | `Sheet1` | | `year` | `int64` | Observation year. | `2017` | | `d_21110` | `double` | Source column from the original resource. | `0.001` | | `personal_emoluments` | `string` | Source column from the original resource. | `Basic Salary` | | `in_post_mar_17` | `double` | Source column from the original resource. | `` | | `funded_2017_18` | `double` | Source column from the original resource. | `` | | `d_56940000` | `double` | Source column from the original resource. | `44960000.0` | | `d_55930000` | `double` | Source column from the original resource. | `45440000.0` | | `d_61735000` | `double` | Source column from the original resource. | `50935000.0` | | `d_62935000` | `double` | Source column from the original resource. | `51935000.0` | | `source_period_start_year` | `int64` | Start year inferred from source metadata. | `2017` | | `source_period_end_year` | `int64` | End year inferred from source metadata. | `2017` | | `source_period_label` | `dictionary` | Source column from the original resource. | `2017` | | `source_provider` | `dictionary` | Publishing organization. | `MDPA` | | `source_dataset` | `dictionary` | Source dataset or package title. | `Budget Data Ministry of Technology, Communication and Innovation` | | `source_resource` | `dictionary` | Source resource title, table name, or file name. | `SOURCE_Budget_Data_MTCI_2017_18_0.xlsx` | | `source_package_id` | `dictionary` | Source package identifier. | `15b1c856-4065-4d61-a838-2bbc4e03c2b7` | | `source_resource_id` | `dictionary` | Source resource identifier. | `d333faef-d9ab-40c6-bab7-ff26c8fa49eb` | | `source_url` | `dictionary` | Original source URL or download URL. | `https://data.govmu.org/dataset/15b1c856-4065-4d61-a838-2bbc4e03c2b7/r...` | | `license_id` | `dictionary` | Source license identifier. | `CC-BY-SA-4.0` | | `retrieved_at` | `dictionary` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-08-08T16:26:20Z` | ## Usage ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-mauritius-budget-data-ministry-of-technology-communication-and-innov-6866de02") df = ds["train"].to_pandas() print(df.head()) ``` ### Inspect Columns ```python print(df.info()) print(df.head()) ``` ### Filter By Geography ```python if "country_iso3" in df.columns: sample = df[df["country_iso3"] == "MU"] ``` ### Time-Series Pattern ```python if "value" in df.columns and "year" in df.columns: trend = df.sort_values("year") ``` ### Pivot For Analysis ```python if {"indicator_id", "year", "value"}.issubset(df.columns): matrix = df.pivot_table(index="year", columns="indicator_id", values="value") print(matrix.tail()) ``` ## Data Quality Notes - Canonical time field: `year`. - Missing values are preserved rather than silently imputed. - Column names are standardized for machine use; source meanings are preserved where known. - Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use. ## Source And Provenance - **Source:** [MDPA](https://data.govmu.org/dataset/budget-data-ministry-technology-communication-and-innovation) - **Publisher:** MDPA - **Portal:** [https://data.govmu.org](https://data.govmu.org) - **Resource:** [SOURCE_Budget_Data_MTCI_2017_18_0.xlsx](https://data.govmu.org/dataset/15b1c856-4065-4d61-a838-2bbc4e03c2b7/resource/d333faef-d9ab-40c6-bab7-ff26c8fa49eb/download/source_budget_data_mtci_2017_18_0.xlsx) - **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) - **Retrieved/generated:** `2026-08-08T16:28:30Z` - **Hugging Face repo:** [electricsheepafrica/africa-mauritius-budget-data-ministry-of-technology-communication-and-innov-6866de02](https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-ministry-of-technology-communication-and-innov-6866de02) ## Transformations Applied - Converted the source table to Parquet for efficient analytics and ML workflows. - Added or preserved source provenance columns where available. - Standardized README metadata, dataset loading configuration, schema documentation, and citation format. - Preserved source-reported values without analytical imputation. ## Suggested Analyses - Build time-series dashboards - Compare economic indicators - Join with population or sector data - Build time-series views and period-over-period comparisons - Check missingness before modeling - Use `country_iso3` as the safest geography join key when present ## Citation ```bibtex @misc{electric_sheep_africa_africa_mauritius_budget_data_ministry_of_technology_communication_and_innov_6866_2017, title = {Budget Data Ministry of Technology Communication and Innov | Africa (MDPA)}, author = {MDPA}, year = {2017}, url = {https://data.govmu.org/dataset/budget-data-ministry-technology-communication-and-innovation}, publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa}, howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-budget-data-ministry-of-technology-communication-and-innov-6866de02}} } ``` ## License Released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/). Original data is published by MDPA. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used. ## About Electric Sheep Africa Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face. --- Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/budget-data-ministry-technology-communication-and-innovation