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Pharos Data

Domaine:

digital infrastructuregeospatial

Type de record:

softwaredataset
Créateur:
Tho
Hôte:avatar

Introduction

This data repository includes the cleaned dataset for the Pharos application 2023-2024 data collection period (May 2023-March 2024). This dataset includes the full recurring network measurement (RNM), landmark (LM) datasets, as well as the county geographies used for the study catchment area. Also included in this dataset are the necessary software files to clean and visualize the collected data replicating the methods used in our published analysis.

Figures Generated by This Repository

Running the Python scripts in this repository generates the following manuscript figures:

  • Figure 2 - Upload/download success counts and duration distributions by carrier
  • Figure 5 (top panel) - Count of datapoints per county (log scale)
  • Figure 5 (bottom panel) - Temporal trends for Kisumu county (radar plots by carrier)
  • Figure S2A - Temporal trends for Siaya county
  • Figure S2B - Temporal trends for Migori county
  • Figure S2C - Temporal trends for Homa Bay county

Setup and Execution Instructions for Reproduction

Prerequisites

  • Python 3.9.16 (likely compatible, but untested with Python >3.7)
  • pip (Python package installer)

Files Included

  • _main.py - Main execution script
  • _clean_df.py - Data cleaning module
  • _make_viz.py - Visualization module
  • _clean_lms.csv - Landmark data
  • _clean_rnms.csv - Recurring network measurement data
  • _Counties_WesternKenya.json - Geographic boundaries for Western Kenya counties
  • requirements.txt - Python package dependencies
  • ArcGIS Figures Reproducibility Steps.pdf/.docx - Instructions for reproducing ArcGIS-generated figures

Installation and Execution

  1. Create a virtual environment (recommended, but not required)
    python3 -m venv venv
  2. Activate the virtual environment (recommended, but not required)
    source venv/bin/activate
  3. Install required packages
    pip install -r requirements.txt
  4. Run the analysis
    python _main.py
    The script will generate PNG files for Figures 2, 5, S2A, S2B, and S2C at 300 DPI resolution, suitable for publication.
  5. Deactivate virtual environment when done (if used)
    deactivate

Reproducing Other Manuscript Figures

Other figures in the manuscript (Figure 4, Figure 6, Figure 7, Figure S1, Figure S3, and Figure S4) were created using ArcGIS Pro with the same RNM and LM datasets included in this repository. Step-by-step instructions for reproducing these ArcGIS-generated figures are provided in the included files: ArcGIS Figures Reproducibility Steps.pdf and ArcGIS Figures Reproducibility Steps.docx.