# ananyo-sen-b2530066/ml-sales-prediction architecture

> Architecture diagram of the GitHub repository ananyo-sen-b2530066/ml-sales-prediction, 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/ananyo-sen-b2530066/ml-sales-prediction
- Repository: https://github.com/ananyo-sen-b2530066/ml-sales-prediction

## Overview

ML Sales Prediction is a Python analysis project for exploring video-game sales data and estimating global sales. Users can run EDA or either of two standalone regression scripts. Each regression workflow loads and prepares the dataset, encodes features, trains several regressors, evaluates validation/test predictions, and visualizes results. The enhanced workflow additionally uses a log-transformed target and adds regional-sales features. Both scripts are self-contained; the available evidence does not show one calling the other. Regression details are based on the provided excerpts, so unsampled implementation specifics are not inferred.

Main entry points: [`game_regression_original.py`](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py) (Original pipeline), [`game_regression_all.py`](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py) (Enhanced pipeline), [`game_data_eda.py`](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_data_eda.py) (EDA analysis), [`vgsales.csv`](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/vgsales.csv) (Sales dataset)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_exploration["Data exploration"]
  node_eda["EDA analysis<br/>[game_data_eda.py]"]
end

subgraph group_regression["Sales prediction"]
  node_original["Original pipeline"]
  node_original_prep["Clean and engineer"]
  node_original_encode["Split and encode"]
  node_original_models["Regressor models"]
  node_original_eval["Evaluate predictions"]
  node_enhanced["Enhanced pipeline"]
  node_enhanced_prep["Sales feature engineering"]
  node_enhanced_encode["Split and encode"]
  node_enhanced_models["Regressor models"]
  node_enhanced_eval["Log-scale evaluation"]
end

subgraph group_outputs["Analysis outputs"]
  node_eda_outputs["EDA charts<br/>[game_data_eda.py]"]
  node_original_viz["Model visualizations"]
  node_enhanced_viz["Model visualizations"]
end

node_user(("Analyst"))
node_sales_data[("Sales dataset<br/>[vgsales.csv]")]

node_user -->|"runs"| node_eda
node_user -->|"runs"| node_original
node_user -->|"runs"| node_enhanced
node_eda -->|"reads"| node_sales_data
node_eda -->|"plots"| node_eda_outputs
node_original -->|"reads"| node_sales_data
node_original -->|"prepares"| node_original_prep
node_original -->|"splits and encodes"| node_original_encode
node_original -->|"trains"| node_original_models
node_original -->|"evaluates"| node_original_eval
node_original -->|"plots results"| node_original_viz
node_enhanced -->|"reads"| node_sales_data
node_enhanced -->|"engineers features"| node_enhanced_prep
node_enhanced -->|"splits and encodes"| node_enhanced_encode
node_enhanced -->|"trains"| node_enhanced_models
node_enhanced -->|"evaluates"| node_enhanced_eval
node_enhanced -->|"plots results"| node_enhanced_viz

click node_sales_data "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/vgsales.csv"
click node_eda "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_data_eda.py"
click node_eda_outputs "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_data_eda.py"
click node_original "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py"
click node_original_prep "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py"
click node_original_encode "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py"
click node_original_models "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py"
click node_original_eval "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py"
click node_original_viz "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py"
click node_enhanced "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py"
click node_enhanced_prep "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py"
click node_enhanced_encode "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py"
click node_enhanced_models "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py"
click node_enhanced_eval "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py"
click node_enhanced_viz "https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py"

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_eda toneBlue
class node_original,node_original_prep,node_original_encode,node_original_models,node_original_eval,node_enhanced,node_enhanced_prep,node_enhanced_encode,node_enhanced_models,node_enhanced_eval,node_sales_data toneAmber
class node_eda_outputs,node_original_viz,node_enhanced_viz toneMint
class node_user toneIndigo
```

## Components

### Data exploration

- [EDA analysis](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_data_eda.py): `game_data_eda.py`

### Sales prediction

- [Original pipeline](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py): `game_regression_original.py`
- [Clean and engineer](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py): `game_regression_original.py`
- [Split and encode](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py): `game_regression_original.py`
- [Regressor models](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py): `game_regression_original.py`
- [Evaluate predictions](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py): `game_regression_original.py`
- [Enhanced pipeline](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py): `game_regression_all.py`
- [Sales feature engineering](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py): `game_regression_all.py`
- [Split and encode](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py): `game_regression_all.py`
- [Regressor models](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py): `game_regression_all.py`
- [Log-scale evaluation](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py): `game_regression_all.py`

### Analysis outputs

- [EDA charts](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_data_eda.py): `game_data_eda.py`
- [Model visualizations](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_original.py): `game_regression_original.py`
- [Model visualizations](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/game_regression_all.py): `game_regression_all.py`

### Other components

- **Analyst**
- [Sales dataset](https://github.com/ananyo-sen-b2530066/ml-sales-prediction/blob/main/vgsales.csv): `vgsales.csv`

## Connections

- Analyst → EDA analysis: runs (evidence: `README.md`)
- Analyst → Original pipeline: runs (evidence: `README.md`)
- Analyst → Enhanced pipeline: runs (evidence: `README.md`)
- EDA analysis → Sales dataset: reads (evidence: `game_data_eda.py`)
- EDA analysis → EDA charts: plots (evidence: `game_data_eda.py`)
- Original pipeline → Sales dataset: reads (evidence: `game_regression_original.py`)
- Original pipeline → Clean and engineer: prepares (evidence: `game_regression_original.py`)
- Original pipeline → Split and encode: splits and encodes (evidence: `game_regression_original.py`)
- Original pipeline → Regressor models: trains (evidence: `game_regression_original.py`)
- Original pipeline → Evaluate predictions: evaluates (evidence: `game_regression_original.py`)
- Original pipeline → Model visualizations: plots results (evidence: `game_regression_original.py`)
- Enhanced pipeline → Sales dataset: reads (evidence: `game_regression_all.py`)
- Enhanced pipeline → Sales feature engineering: engineers features (evidence: `game_regression_all.py`)
- Enhanced pipeline → Split and encode: splits and encodes (evidence: `game_regression_all.py`)
- Enhanced pipeline → Regressor models: trains (evidence: `game_regression_all.py`)
- Enhanced pipeline → Log-scale evaluation: evaluates (evidence: `game_regression_all.py`)
- Enhanced pipeline → Model visualizations: plots results (evidence: `game_regression_all.py`)