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electricsheepafrica/africa-chad-covid-19-high-frequency-indicators-bbc35e39

Covid 19 High Frequency Indicators | Africa (World Bank Group) 44,556 rows - 1 Africa country/area - 2020 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 44,556 rows from World Bank Group, covering Covid 19 High Frequency Indicators. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures Official statistics… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-chad-covid-19-high-frequency-indicators-bbc35e39.

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Covid 19 High Frequency Indicators | Africa (World Bank Group)

44,556 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 44,556 rows from World Bank Group, covering Covid 19 High Frequency Indicators. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: High-frequency monitoring data

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

DimensionValue
Rows44,556
Countries/areas1
First period2020
Last period2020
Indicators0
Columns61
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
TCD44,55620202020Chad

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.f7389016-00fb-48d6-b4be-ab0db2c17b77:1-countries-included:0
country_iso3dictionary<values=string, indices=int8, ordered=0>ISO3 country or area code.TCD
country_namedictionary<values=string, indices=int8, ordered=0>Country or area name.Chad
source_sheetstringSource column from the original resource.1. Countries Included
total_of_countriesdoubleSource column from the original resource.8.0
regionstringSource column from the original resource.East Asia Pacific
list_of_codestringSource column from the original resource.IDN LAO MMR MNG PNG PHL SLB KHM
source_period_start_yearint64Start year inferred from source metadata.``
source_period_end_yearint64End year inferred from source metadata.``
source_period_labelstringSource column from the original resource.``
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.World Bank Group
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.COVID-19 High-Frequency indicators
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.COVID19DashboardDataLatest.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.0d94e0ba-2fe1-403f-a25a-9efb03b50594
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.f7389016-00fb-48d6-b4be-ab0db2c17b77
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.humdata.org/dataset/0d94e0ba-2fe1-403f-a25a-9efb03b50594...
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.2026-08-10T22:51:43Z
row_iddoubleSource column from the original resource.``
codestringSource column from the original resource.``
wavestringSource column from the original resource.``
monthdoubleSource column from the original resource.``
level_datastringSource column from the original resource.``
indicatorstringSource column from the original resource.``
indicator_valdoubleSource column from the original resource.``
urban_ruralstringSource column from the original resource.``
industrystringSource column from the original resource.``
current_lsectorstringSource column from the original resource.``
sample_subsetdoubleSource column from the original resource.``
sample_totaldoubleSource column from the original resource.``
yeardoubleObservation year.``
countrystringSource column from the original resource.``
region_codestringSource column from the original resource.``
fcsstringSource column from the original resource.``
income_groupstringSource column from the original resource.``
lending_categorystringSource column from the original resource.``
indicator_topicstringSource column from the original resource.``
indicator_descriptionstringSource column from the original resource.``
indicator_displaystringSource column from the original resource.``
unit_measurestringSource column from the original resource.``
measure_typestringSource column from the original resource.``
headline_indicatordoubleSource column from the original resource.``
gdp_pcdoubleSource column from the original resource.``
ln_gdp_pcdoubleSource column from the original resource.``
many_wavesdoubleSource column from the original resource.``
weight_typestringSource column from the original resource.``
footnotestringSource column from the original resource.``
survey_producerstringSource column from the original resource.``
survey_linkstringSource column from the original resource.``
last_updatedstringSource column from the original resource.``
indicator_labelstringSource column from the original resource.``
indicator_val_oldstringSource column from the original resource.``
indicator_val_newstringSource column from the original resource.``
reasonstringSource column from the original resource.``
datestringObservation date.``
data_in_dashboard_new_countrydoubleSource column from the original resource.``
data_in_dashboard_no_changedoubleSource column from the original resource.``
data_in_dashboard_new_wavedoubleSource column from the original resource.``
survey_in_progessdoubleSource column from the original resource.``
flag_new_countrydoubleSource column from the original resource.``
flag_new_wavedoubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-chad-covid-19-high-frequency-indicators-bbc35e39")
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"] == "TCD"]

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

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

  • —Profile the distribution of values
  • —Compare categories or geographies
  • —Join with complementary public datasets
  • —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_chad_covid_19_high_frequency_indicators_bbc35e39_2020,
  title        = {Covid 19 High Frequency Indicators | Africa (World Bank Group)},
  author       = {World Bank Group},
  year         = {2020},
  url          = {https://data.humdata.org/dataset/covid-19-high-frequency-indicators},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-covid-19-high-frequency-indicators-bbc35e39}}
}

License

Released under CC BY 4.0.

Original data is published by World Bank Group. 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.humdata.org/dataset/covid-19-high-frequency-indicators