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electricsheepafrica/africa-south-sudan-humanitarian-access-constraints-due-to-covid-19-pandemic-6ca89071

Humanitarian Access Constraints Due to Covid 19 Pandemic | Africa (OCHA HQ) 1,127 rows - 1 Africa country/area - 2020 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 1,127 rows from OCHA HQ, covering Humanitarian Access Constraints Due to Covid 19 Pandemic. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-humanitarian-access-constraints-due-to-covid-19-pandemic-6ca89071.

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Humanitarian Access Constraints Due to Covid 19 Pandemic | Africa (OCHA HQ)

1,127 rows - 1 Africa country/area - 2020 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 1,127 rows from OCHA HQ, covering Humanitarian Access Constraints Due to Covid 19 Pandemic. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Climate and environment datasets help analysts study exposure, resource conditions, environmental pressure, and climate-related trends.

Source-provided context: The new/ emerging access constraints that people are currently experiencing because of the COVID-19 outbreak as at July 2020

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: not detected.
  • —Time coverage basis: source metadata.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows1,127
Countries/areas1
First period2020
Last period2020
Indicators0
Columns26
Source formatXLSX

Geographic Coverage

Top areas shown below, sorted by row count when available:

AreaRowsFirst yearLast yearName
SSD1,12720202020South Sudan

Indicators, Variables, Or Resource Contents

  • —This repo preserves one source tabular resource with its usable columns kept together.

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.fcac1714-eb7d-4c51-a640-906a12597eeb:general:0
country_iso3dictionary<values=string, indices=int8, ordered=0>ISO3 country or area code.SSD
country_namedictionary<values=string, indices=int8, ordered=0>Country or area name.South Sudan
source_sheetstringSource column from the original resource.General
datestringObservation date.2020-07-14 00:00:00
regionstringSource column from the original resource.Asia and the Pacific
admin0_codestringSource column from the original resource.AF
countrystringSource column from the original resource.Afghanistan
mitigation_indstringSource column from the original resource.yes
source_period_start_yearint64Start year inferred from source metadata.2020
source_period_end_yearint64End year inferred from source metadata.2020
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2020
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.OCHA HQ
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Humanitarian Access Constraints due to COVID-19 Pandemic
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.Humanitarian Access July 2020.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.85c33a03-4968-418e-b01b-ce81880f7cdc
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.fcac1714-eb7d-4c51-a640-906a12597eeb
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.humdata.org/dataset/85c33a03-4968-418e-b01b-ce81880f7cdc...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.cc-by
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-10T18:18:23Z
admin0stringSource column from the original resource.``
constraintstringSource column from the original resource.``
type_of_constraintsstringSource column from the original resource.``
scoredoubleSource column from the original resource.``
impactstringSource column from the original resource.``
mitigationstringSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-humanitarian-access-constraints-due-to-covid-19-pandemic-6ca89071")
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"] == "SSD"]

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

  • —No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
  • —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

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

  • —Analyze seasonal or annual patterns
  • —Join with agriculture or health data
  • —Map geographic exposure
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_south_sudan_humanitarian_access_constraints_due_to_covid_19_pandemic_6ca8_2020,
  title        = {Humanitarian Access Constraints Due to Covid 19 Pandemic | Africa (OCHA HQ)},
  author       = {OCHA HQ},
  year         = {2020},
  url          = {https://data.humdata.org/dataset/constraints-faced-by-people-due-to-covid-19-outbreak},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-humanitarian-access-constraints-due-to-covid-19-pandemic-6ca89071}}
}

License

Released under CC BY 4.0.

Original data is published by OCHA HQ. 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 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/constraints-faced-by-people-due-to-covid-19-outbreak