Personality-Distribution-Analysis-in-AequorTechCTRL-by-Fozan-Ahmed-Memon

Personality Distribution Analysis — Volunteers at AequorTech CTRL

This project analyzes MBTI personality types for volunteering participants at AequorTech CTRL using a curated CSV dataset. The previous synthetic employee-based method has been removed; the analysis now strictly uses the provided participant data.

Dataset

• File: PersonalityAnalysis/participants_mbti.csv
• Columns: Name, Age, Gender, City, Country, MBTI, Occupation
• MBTI codes are normalized to uppercase.

Outputs

• Script: PersonalityAnalysis/participants_personality_distribution.png
• Notebook: PersonalityAnalysis/notebook_participants_personality_distribution.png

Quick Start (Windows, Python 3.12)

• Install Python: winget install -e --id Python.Python.3.12 --accept-package-agreements --accept-source-agreements --silent
• Upgrade tooling: "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe" -m pip install --upgrade pip setuptools wheel
• Install deps: "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe" -m pip install -r PersonalityAnalysis/requirements.txt

Run Options

• Script (generate plot): "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe" PersonalityAnalysis/app.py
• Notebook (EDA): "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe" -m notebook PersonalityAnalysis/MBTI_Personality_Analysis.ipynb
• Headless notebook: "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe" -m notebook PersonalityAnalysis/MBTI_Personality_Analysis.ipynb --no-browser --port 8890

AI Research Context

• Goal: Describe MBTI distribution for volunteers to inform team design, engagement, and role alignment.
• Method: EDA-first pipeline — ingest CSV → normalize MBTI → compute counts/percentages → visualize.
• Utilities: Lookup by name and list participants by MBTI in app.py.
• Reproducibility: Deterministic analysis from CSV; reruns yield the same results.

Ethics & Limitations

• Small convenience sample; insights are descriptive, not generalizable.
• MBTI is a self-report typology; avoid stereotyping or prescriptive decisions.
• Maintain voluntariness, privacy, and transparency when expanding the dataset.

Extend the Research

• Add features (e.g., department, tenure, interests) to enable richer analysis.
• Explore cross-tabs (MBTI × Gender/Occupation) and age distributions.
• Build an interactive dashboard (e.g., Streamlit) or add modeling (clustering, prediction) when more features are available.

Advanced Notebook — Percent Heatmaps and Grouped Occupations

• Notebook: PersonalityAnalysis/MBTI_Personality_Analysis_Advanced.ipynb
• Adds grouped occupation categories and percent-based cross-tabs for MBTI × Occupation and MBTI × Gender; includes age-by-MBTI boxplot.

Run Options

• Jupyter UI (serve PersonalityAnalysis/):
  • If python is on PATH:
    • python -m jupyter notebook --no-browser --port 8891 --notebook-dir PersonalityAnalysis
  • Using Python 3.12 path on Windows:
    • & "C:\Users\Fozan\AppData\Local\Programs\Python\Python312\python.exe" -m jupyter notebook --no-browser --port 8891 --notebook-dir "c:\Users\Fozan\Desktop\Personality-Distribution-Analysis-in-AequorTechCTRL-by-Fozan-Ahmed-Memon-main\PersonalityAnalysis"
• Headless execution (generates an executed copy and images):
  • If python is on PATH:
    • python -m jupyter nbconvert --to notebook --execute PersonalityAnalysis/MBTI_Personality_Analysis_Advanced.ipynb --output PersonalityAnalysis/MBTI_Personality_Analysis_Advanced_executed.ipynb --ExecutePreprocessor.timeout=300
  • Using Python 3.12 path on Windows:
    • & "C:\Users\Fozan\AppData\Local\Programs\Python\Python312\python.exe" -m jupyter nbconvert --to notebook --execute "c:\Users\Fozan\Desktop\Personality-Distribution-Analysis-in-AequorTechCTRL-by-Fozan-Ahmed-Memon-main\PersonalityAnalysis\MBTI_Personality_Analysis_Advanced.ipynb" --output "MBTI_Personality_Analysis_Advanced_executed.ipynb" --output-dir "c:\Users\Fozan\Desktop\Personality-Distribution-Analysis-in-AequorTechCTRL-by-Fozan-Ahmed-Memon-main\PersonalityAnalysis" --ExecutePreprocessor.timeout=300

New Outputs

• PersonalityAnalysis/advanced_mbti_occupation_group_heatmap.png
• PersonalityAnalysis/advanced_mbti_occupation_group_colpct_heatmap.png
• PersonalityAnalysis/advanced_mbti_occupation_group_rowpct_heatmap.png
• PersonalityAnalysis/advanced_mbti_gender_heatmap.png
• PersonalityAnalysis/advanced_mbti_gender_colpct_heatmap.png
• PersonalityAnalysis/advanced_mbti_gender_rowpct_heatmap.png
• PersonalityAnalysis/advanced_age_by_mbti.png
• Executed notebook: PersonalityAnalysis/MBTI_Personality_Analysis_Advanced_executed.ipynb

Notes & Tips

• MBTI codes are normalized to uppercase; Age is parsed as numeric where present.
• Occupation grouping uses simple keywords (e.g., engineering/tech, design/creative, student/trainee). You can refine categories as data grows.
• If nbconvert is missing: python -m pip install nbconvert. If jupyter is missing: python -m pip install notebook.

Visual Gallery

• Script output — Distribution:
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• Advanced notebook — Gender:
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• Advanced notebook — Occupation (raw):
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• Advanced notebook — Occupation Group:
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• Advanced notebook — Age:
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