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finance_python

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Elementary Jupyter Notebook Samples for Finance

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# Jupyter Notebook Samples for Finance
 
## Overview
 
This is a series of studies of Jupyter Notebook for Finance.

## Jupyter Notebook

1. `How to get cumulative return for your asset and portfolio in Python.ipynb`
2. `How to calculate historical volatility and sharpe ratio in Python.ipynb`
3. `How to get a distribution of returns and draw a probability plot for the distribution in Python.ipynb`
4. `Mastering DataFrame - how to aggregate OHLCV data in a different time period.ipynb` 
5. `How to compute price correlation for financial data in Python.ipynb` 
6. `How to build Sentiment Analysis with NLTK and Sciki-learn in Python.ipynb` 
7. `How to draw a candle stick chart with DataFrame in Python (mplfinance, plotly and bokeh).ipynb` 
8. `How to draw 4 most common trend indicators in matplotlib in Python.ipynb` 
9. `How to draw a trend line with DataFrame in Python.ipynb` 
10. `How to draw support and resistence lines with DataFrame in Python.ipynb`
11. `Coefficient variable for crypto assets.ipynb` 
12. `3 ways to do test of normality with Scipy library in Python.ipynb` 
13. `What are standarization and normalization? Test with iris data set in Scikit-learn.ipynb` 
14. `Scikit-learn LinearRegression vs Numpy Polyfit.ipynb`
15. `3 ways to do dimensional reduction techniques in Scikit-learn.ipynb`
  
## License
 
This code is licensed under the MIT License.

finance_python

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