# sifat192/covid19-analysis architecture

> Architecture diagram of the GitHub repository sifat192/covid19-analysis, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-30). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sifat192/covid19-analysis
- Repository: https://github.com/sifat192/covid19-analysis

## Overview

This repository is a notebook-based analysis of COVID-19 infection trends and their relationship to World Happiness indicators. The documented workflow cleans and aggregates infection data, computes country-level maximum infection rates, combines those results with happiness data, then analyzes and visualizes relationships. The notebook itself was not sampled, so the internal stages and their ordering are based on the README rather than inspected implementation; no unverified code-level details are inferred.

Main entry points: [`covid19 data analysis notebook.ipynb`](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb) (Clean and Aggregate), [`Datasets/covid19_Confirmed_dataset.csv`](https://github.com/sifat192/covid19-analysis/blob/main/Datasets/covid19_Confirmed_dataset.csv) (COVID Dataset), [`Datasets/worldwide_happiness_report.csv`](https://github.com/sifat192/covid19-analysis/blob/main/Datasets/worldwide_happiness_report.csv) (Happiness Dataset)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_covid["COVID Data"]
  node_covid_csv["COVID Dataset"]
  node_covid_prep["Clean and Aggregate"]
  node_growth["Infection Growth"]
  node_max_rate["Maximum Infection Rate"]
end

subgraph group_happiness["Happiness Data"]
  node_happiness_csv["Happiness Dataset"]
  node_happiness_prep["Process Indicators"]
end

subgraph group_analysis["Analysis"]
  node_merge["Country Merge"]
  node_correlation["Correlation Analysis"]
  node_visualize["Relationship Plots"]
end

node_analyst(("Analyst"))

node_analyst -.->|"runs analysis"| node_covid_prep
node_covid_csv -->|"loads and cleans"| node_covid_prep
node_covid_prep -->|"aggregates for"| node_growth
node_growth -->|"computes maxima"| node_max_rate
node_happiness_csv -->|"processes"| node_happiness_prep
node_max_rate -->|"merges by country"| node_merge
node_happiness_prep -->|"merges by country"| node_merge
node_merge -->|"analyzes correlation"| node_correlation
node_correlation -->|"visualizes relationships"| node_visualize

click node_covid_csv "https://github.com/sifat192/covid19-analysis/blob/main/Datasets/covid19_Confirmed_dataset.csv"
click node_covid_prep "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"
click node_growth "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"
click node_max_rate "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"
click node_happiness_csv "https://github.com/sifat192/covid19-analysis/blob/main/Datasets/worldwide_happiness_report.csv"
click node_happiness_prep "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"
click node_merge "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"
click node_correlation "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"
click node_visualize "https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_covid_csv,node_covid_prep,node_growth,node_max_rate toneBlue
class node_happiness_csv,node_happiness_prep toneAmber
class node_merge,node_correlation,node_visualize toneMint
class node_analyst toneIndigo
```

## Components

### COVID Data

- [COVID Dataset](https://github.com/sifat192/covid19-analysis/blob/main/Datasets/covid19_Confirmed_dataset.csv): `Datasets/covid19_Confirmed_dataset.csv`
- [Clean and Aggregate](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`
- [Infection Growth](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`
- [Maximum Infection Rate](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`

### Happiness Data

- [Happiness Dataset](https://github.com/sifat192/covid19-analysis/blob/main/Datasets/worldwide_happiness_report.csv): `Datasets/worldwide_happiness_report.csv`
- [Process Indicators](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`

### Analysis

- [Country Merge](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`
- [Correlation Analysis](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`
- [Relationship Plots](https://github.com/sifat192/covid19-analysis/blob/main/covid19%20data%20analysis%20notebook.ipynb): `covid19 data analysis notebook.ipynb`

### Other components

- **Analyst**

## Connections

- Analyst → Clean and Aggregate: runs analysis
- COVID Dataset → Clean and Aggregate: loads and cleans (evidence: `README.md`)
- Clean and Aggregate → Infection Growth: aggregates for (evidence: `README.md`)
- Infection Growth → Maximum Infection Rate: computes maxima (evidence: `README.md`)
- Happiness Dataset → Process Indicators: processes (evidence: `README.md`)
- Maximum Infection Rate → Country Merge: merges by country (evidence: `README.md`)
- Process Indicators → Country Merge: merges by country (evidence: `README.md`)
- Country Merge → Correlation Analysis: analyzes correlation (evidence: `README.md`)
- Correlation Analysis → Relationship Plots: visualizes relationships (evidence: `README.md`)