# alimov2008/pharma-sales-data-analysis---roadmap.sh-project architecture

> Architecture diagram of the GitHub repository alimov2008/pharma-sales-data-analysis---roadmap.sh-project, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-23). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project
- Repository: https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project

## Overview

This is a notebook-based pharmaceutical sales analysis. The user runs the notebook against the historical sales CSV to explore category sales, identify top-selling drugs for periods, examine 2017 sales frequency, compare category averages, and analyze monthly R03 sales. Pandas and Matplotlib are documented analysis tools; the notebook source was not sampled, so specific implementation steps and data-flow details cannot be verified.

Main entry points: [`pharmaceutical_sales.ipynb`](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb) (Sales notebook), [`data/salesdaily.csv`](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/data/salesdaily.csv) (Daily sales CSV)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_analysis["Sales analysis"]
  node_notebook["Sales notebook"]
  node_category["Category sales"]
  node_top_drugs["Top drugs"]
  node_frequency["2017 frequency"]
  node_averages["Daily averages"]
  node_respiratory["R03 monthly sales"]
  node_results["Analysis results"]
end

subgraph group_inputs["Input data"]
  node_sales_data["Daily sales CSV<br/>[salesdaily.csv]"]
end

subgraph group_tools["Analysis tools"]
  node_pandas["Pandas"]
  node_matplotlib["Matplotlib"]
end

node_user(("Analyst"))

node_user -->|"runs"| node_notebook
node_notebook -->|"reads"| node_sales_data
node_notebook -->|"uses"| node_pandas
node_notebook -->|"uses"| node_matplotlib
node_notebook -->|"analyzes"| node_category
node_notebook -->|"identifies"| node_top_drugs
node_notebook -->|"examines"| node_frequency
node_notebook -->|"compares"| node_averages
node_notebook -->|"analyzes"| node_respiratory
node_notebook -->|"produces"| node_results

click node_notebook "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb"
click node_category "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb"
click node_top_drugs "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb"
click node_frequency "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb"
click node_averages "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb"
click node_respiratory "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb"
click node_sales_data "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/data/salesdaily.csv"
click node_results "https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.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_notebook,node_category,node_top_drugs,node_frequency,node_averages,node_respiratory,node_results toneBlue
class node_sales_data toneAmber
class node_pandas,node_matplotlib toneMint
class node_user toneIndigo
```

## Components

### Sales analysis

- [Sales notebook](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`
- [Category sales](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`
- [Top drugs](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`
- [2017 frequency](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`
- [Daily averages](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`
- [R03 monthly sales](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`
- [Analysis results](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/pharmaceutical_sales.ipynb): `pharmaceutical_sales.ipynb`

### Input data

- [Daily sales CSV](https://github.com/alimov2008/pharma-sales-data-analysis---roadmap.sh-project/blob/master/data/salesdaily.csv): `data/salesdaily.csv`

### Analysis tools

- **Pandas**
- **Matplotlib**

### Other components

- **Analyst**

## Connections

- Analyst → Sales notebook: runs
- Sales notebook → Daily sales CSV: reads
- Sales notebook → Pandas: uses
- Sales notebook → Matplotlib: uses
- Sales notebook → Category sales: analyzes
- Sales notebook → Top drugs: identifies
- Sales notebook → 2017 frequency: examines
- Sales notebook → Daily averages: compares
- Sales notebook → R03 monthly sales: analyzes
- Sales notebook → Analysis results: produces