Accounts Payable Analysis Project

This repository contains:

• Raw AP data
• Processed outputs
• Notebooks
• Source code

📊 AP Analysis (Dynamics 365 Style) — End-to-End Data Pipeline + Streamlit Dashboard

This project delivers a complete Accounts Payable (AP) analytics workflow, inspired by Microsoft Dynamics 365 Finance & Operations.
It includes full data cleaning, KPI calculations, automated CSV reports, and an interactive Streamlit dashboard for real-time analysis.

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🚀 Live Demo (Streamlit Web App)

Access the live deployed dashboard here:

🔗 https://ap-analysis-d365-mitvjtrfz5m5vzhs2nyw8a.streamlit.app/

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📁 Project Structure

ap-analysis-d365/ │ ├── app.py # Streamlit dashboard ├── ap_cleaning.py # Data cleaning pipeline ├── ap_kpis.py # KPI calculations ├── ap_reports.py # Automated reports (aging, vendors, cashflow) │ ├── data/ │ ├── raw/ # Raw Excel input files (ignored by git) │ └── processed/ # Cleaned & transformed CSV output │ ├── reports/ # Dashboard screenshots & charts │ ├── requirements.txt └── README.md

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🧼 Data Cleaning Rules

The cleaning logic follows standard enterprise AP validation rules (similar to D365):

✅ Remove rows with missing APID
✅ Remove zero or negative Amount
✅ Convert all dates to valid datetime
✅ Drop rows with invalid date formats
✅ Remove rows where DueDate < InvoiceDate
✅ Keep only valid currencies: USD, EUR, GBP, CAD, AUD, JPY
✅ Detect and remove duplicates using a composite key:
APID + Vendor + InvoiceDate + Amount
✅ Save cleaned data as: data/processed/ap_clean.csv

Cleaning implementation lives in:

ap_cleaning.py

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📈 Key Performance Indicators (KPIs)

The project computes a complete AP KPI suite:

Core KPIs

• Total Invoices
• Total Spend
• Open Invoices
• Overdue Invoices
• Overdue Amount
• Average Days Past Due (Avg DPD)
• Maximum DPD
• Vendor Count
• Currency Breakdown
• Open vs Paid distribution

Generated via:

ap_kpis.py

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📑 Automated Reports

Running ap_reports.py generates structured CSV reports:

File	Description
aging_open.csv	Aging summary for open invoices
top_vendors.csv	Top 10 vendors ranked by spend
cash_weekly.csv	Weekly cash-out forecast based on DueDate

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🎛 Streamlit Dashboard

The dashboard includes:

✅ Vendor filter
✅ Currency filter
✅ Invoice date range picker
✅ KPI cards
✅ AP Aging chart
✅ Top Vendors bar chart
✅ Weekly Cash Outflow chart
✅ Filtered data preview
✅ One-click CSV export

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🖼 Screenshots

AP Aging (Open Invoices)

Top Vendors

Weekly Cash Outflow

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🛠 Local Execution

1) Create virtual environment

conda create -n ap-d365 python=3.10 -y
conda activate ap-d365
pip install -r requirements.txt
2) Place your raw Excel files here:
data/raw/

3) Run cleaning pipeline
python ap_cleaning.py

4) Generate KPIs
python ap_kpis.py

5) Generate reports
python ap_reports.py

6) Launch Streamlit dashboard
streamlit run app.py

🌐 Deployment (Streamlit Cloud)

Deployment settings:

Repository: <your-username>/ap-analysis-d365
Branch: main
Main file path: app.py

✅ Technologies Used

Python 3.10

Pandas

NumPy

Streamlit

OpenPyXL

Matplotlib (optional for visuals)

Git / GitHub

📄 License

MIT License — Free to use for learning, portfolio, and commercial projects.

👤 Author

[REYHANEH HAJILI]
Data Engineer & Data Analyst – Python & Microsoft Dynamics 365 Integration