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Description

This Python tool contains a small analysis pipeline for a NASA dataset on Extravehicular Activity (EVA).

The core script eva_data_analysis.py reads the JSON dataset, cleans it, computes duration_hours and crew_size, exports a CSV, and renders a cumulative EVA-time plot to results/.

Pre-requisites

  • Python 3.8+ (virtual environment recommended)
  • Pandas 2.3
  • Matplotlib 3.10
  • Pytest 9 and Pytest-cov 7 (to run unit tests)

Install project dependencies from requirements.txt:

pip install -r requirements.txt

Usage

Run the analysis with defaults (uses data/eva-data.json and writes to results/):

python eva_data_analysis.py

Or supply input and output paths:

python eva_data_analysis.py data/eva-data.json results/eva-data.csv

Generated files include results/eva-data.csv and results/cumulative_eva_graph.png.

Running Tests

Unit tests are provided in the tests/ folder and cover basic helpers such as text_to_duration and calculate_crew_size.

Run tests with:

pytest tests/

Run tests with coverage (requires pytest-cov):

pytest --cov=eva_data_analysis tests/

Maintainers

S.Omebody s.omebody@someemailaddress.com

Licence

This code is licensed under the MIT licence, which can be found in the LICENSE file.

Authors

The original authors of this fabricated example software project are:

Acknowledgements

Original Source Code

The original repository that this is based on can be found at https://github.com/carpentries-incubator/bbrs-software-project.

Data

The data used on in this project is open data provided by NASA and obtained as follows.

Data source: https://data.nasa.gov/Raw-Data/Extra-vehicular-Activity-EVA-US-and-Russia/9kcy-zwvn/about_data.

Either export data from the above page using the Export button or download in JSON format from command line as:

curl https://data.nasa.gov/resource/eva.json --output eva-data.json

Note: the original data has been modified for the purposes of this tutorial by inserting a semicolon separator after each name in the crew field.

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