# 📒 Accounting and Finance

### Bokeh

* **Description**: An interactive visualization library for modern web browsers.
* **Use Case**: Creating interactive charts and plots for financial data analysis and reporting.
* **Documentation**: [Bokeh Documentation](https://docs.bokeh.org/en/latest/)
* **GitHub Repository**: [Bokeh GitHub](https://github.com/bokeh/bokeh)

### Dash by Plotly

* **Description**: A Python framework for building analytical web applications.
* **Use Case**: Developing interactive web-based dashboards for financial data visualization.
* **Documentation**: [Dash Documentation](https://plotly.com/dash/)
* **GitHub Repository**: [Dash GitHub](https://github.com/plotly/dash)

### FinancePy

* **Description**: A library focused on financial markets and products, particularly derivatives pricing and risk management.
* **Use Case**: Pricing and analyzing financial derivatives, fixed income products, and risk management.
* **Documentation**: [FinancePy Documentation](https://github.com/domokane/FinancePy)
* **GitHub Repository**: [FinancePy GitHub](https://github.com/domokane/FinancePy)

### Matplotlib

* **Description**: A plotting library for creating static, animated, and interactive visualizations in Python.
* **Use Case**: Generating a wide range of static and interactive plots and charts for financial data.
* **Documentation**: [Matplotlib Documentation](https://matplotlib.org/)
* **GitHub Repository**: [Matplotlib GitHub](https://github.com/matplotlib/matplotlib)
* **Managed by**: NumFOCUS

### NumPy

* **Description**: The fundamental package for scientific computing with Python.
* **Use Case**: Handling numerical calculations in financial modeling and quantitative finance.
* **Documentation**: [NumPy Documentation](https://numpy.org/doc/)
* **GitHub Repository**: [NumPy GitHub](https://github.com/numpy/numpy)

### Pandas

* **Description**: A data analysis and manipulation library.
* **Use Case**: Data analysis and manipulation in finance, especially useful for time-series financial data.
* **Documentation**: [Pandas Documentation](https://pandas.pydata.org/)
* **GitHub Repository**: [Pandas GitHub](https://github.com/pandas-dev/pandas)

### Plotly

* **Description**: A graphing library that makes interactive, publication-quality graphs online.
* **Use Case**: Creating interactive financial charts and dashboards.
* **Documentation**: [Plotly Documentation](https://plotly.com/python/)
* **GitHub Repository**: [Plotly GitHub](https://github.com/plotly/plotly.py)

### PyAlgoTrade

* **Description**: A Python Algorithmic Trading Library with focus on backtesting and support for paper-trading and live-trading.
* **Use Case**: Algorithmic trading strategy development and testing.
* **Documentation**: [PyAlgoTrade Documentation](http://gbeced.github.io/pyalgotrade/)
* **GitHub Repository**: [PyAlgoTrade GitHub](https://github.com/gbeced/pyalgotrade)

### Pyfolio

* **Description**: A Python library for performance and risk analysis of financial portfolios.
* **Use Case**: Portfolio performance analysis, including risk and return metrics.
* **Documentation**: [Pyfolio Documentation](https://quantopian.github.io/pyfolio/)
* **GitHub Repository**: [Pyfolio GitHub](https://github.com/quantopian/pyfolio)

### PyRisk

* **Description**: A financial risk analysis library.
* **Use Case**: Performing various financial risk assessments including market, credit, and liquidity risk.
* **GitHub Repository**: [PyRisk GitHub](https://github.com/PyRisk/PyRisk)

### QuantLib

* **Description**: A library for quantitative finance.
* **Use Case**: Modeling, trading, and risk management in real-life, particularly for derivatives pricing.
* **Documentation**: [QuantLib Documentation](https://www.quantlib.org/docs.shtml)
* **GitHub Repository**: [QuantLib GitHub](https://github.com/lballabio/QuantLib)
* **Managed by**: NumFOCUS

### Quandl

* **Description**: A platform for financial, economic, and alternative data.
* **Use Case**: Fetching financial and economic datasets for analysis.
* **Documentation**: [Quandl Documentation](https://www.quandl.com/tools/python)
* **GitHub Repository**: [Quandl GitHub](https://github.com/quandl/quandl-python)

### scikit-learn

* **Description**: Machine learning in Python.
* **Use Case**: Predictive modeling and data analysis in finance.
* **Documentation**: [Scikit-learn Documentation](https://scikit-learn.org/stable/)
* **GitHub Repository**: [Scikit-learn GitHub](https://github.com/scikit-learn/scikit-learn)
* **Managed by**: NumFOCUS

### Se

aborn

* **Description**: A statistical data visualization library based on Matplotlib.
* **Use Case**: Creating attractive and informative statistical graphics in finance.
* **Documentation**: [Seaborn Documentation](https://seaborn.pydata.org/)
* **GitHub Repository**: [Seaborn GitHub](https://github.com/mwaskom/seaborn)

### Statsmodels

* **Description**: Statistical modeling and econometrics in Python.
* **Use Case**: Econometric analysis, statistical modeling, and hypothesis testing in finance.
* **Documentation**: [Statsmodels Documentation](https://www.statsmodels.org/stable/index.html)
* **GitHub Repository**: [Statsmodels GitHub](https://github.com/statsmodels/statsmodels)

### Zipline

* **Description**: An open-source algorithmic trading simulator.
* **Use Case**: Backtesting and developing trading algorithms using historical data.
* **Documentation**: [Zipline Documentation](http://www.zipline.io/)
* **GitHub Repository**: [Zipline GitHub](https://github.com/quantopian/zipline)