Distribution of Things Analysis

Background

This repository hosts the analysis and visualizations of various social trends, topics, and phenomena featured on the website Distribution of Things. Each project delves into a unique dataset to uncover insights, highlight patterns, and tell compelling stories about the world around us. The analyses are designed to be accessible, engaging, and informative, showcasing the power of data in understanding complex societal dynamics.

Process

The data is analyzed using Python, leveraging the following libraries:

• Pandas: for data manipulation and cleaning.
• Matplotlib and Seaborn: for data visualization.

Repository Structure

distributionofthings.analysis/
├── 1_olympic_participation/
│   ├── data/           # Raw and processed datasets related to Olympic participation
│   ├── notebooks/      # Jupyter notebooks with exploratory analysis and visualizations
│   ├── results/        # Generated results such as graphs, tables, and summary reports
│
├── 2_military_expenditure/
│   ├── data/           # Datasets related to global military spending
│   ├── notebooks/      # Analysis notebooks
│   ├── results/        # Visualizations and analysis outputs
│
├── 3_nobel_prize/
│   ├── data/           # Nobel Prize laureates data
│   ├── notebooks/      # Notebooks analyzing trends and statistics
│   ├── results/        # Generated figures and conclusions
│
├── 4_good_reads/
│   ├── data/           # Data sourced from Goodreads
│   ├── notebooks/      # Exploratory analysis and insights
│   ├── results/        # Outputs such as visualizations and key findings
│
├── 5_mobile_data/
│   ├── data/           # Mobile data usage datasets
│   ├── notebooks/      # Analysis of trends in mobile data consumption
│   ├── results/        # Plots, charts, and analysis summaries
│
├── 6_conflict_media/
│   ├── data/           # Data linking media coverage and conflict statistics
│   ├── notebooks/      # Analysis of media coverage trends
│   ├── results/        # Generated figures and summary reports
│
├── 7_christmas_advent/
│   ├── data/           # Data for creating Christmas-themed visualizations
│   ├── notebooks/      # Jupyter notebooks with the advent calendar visualizations
│   ├── results/        # Final outputs for each day of the advent calendar
│
├── TEMPLATE.ipynb      # A template notebook for consistent structure across projects
├── requirements.txt    # Python package dependencies