Merge pull request #187 from tianzedavid/master

chore: fix some typos 
merged
tks

README.md

@@ -277,7 +277,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 
 - [xts](https://github.com/joshuaulrich/xts) - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
 - [data.table](https://github.com/Rdatatable/data.table) - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
-- [sparseEigen](https://github.com/dppalomar/sparseEigen) - Sparse pricipal component analysis.
+- [sparseEigen](https://github.com/dppalomar/sparseEigen) - Sparse principal component analysis.
 - [TSdbi](http://tsdbi.r-forge.r-project.org/) - Provides a common interface to time series databases.
 - [tseries](https://cran.r-project.org/web/packages/tseries/index.html) - Time Series Analysis and Computational Finance.
 - [zoo](https://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
@@ -498,7 +498,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [Quantitative-Notebooks](https://github.com/LongOnly/Quantitative-Notebooks) - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
 - [QuantEcon](https://quantecon.org/) - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks
 - [FinanceHub](https://github.com/Finance-Hub/FinanceHub) - Resources for Quantitative Finance
-- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
+- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
 - [python-training](https://github.com/jpmorganchase/python-training) - J.P. Morgan's Python training for business analysts and traders.
 - [Stock_Analysis_For_Quant](https://github.com/LastAncientOne/Stock_Analysis_For_Quant) - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.
 - [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.
@@ -535,4 +535,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [book_irds3](https://github.com/attack68/book_irds3) - Code repository for Pricing and Trading Interest Rate Derivatives.
 - [Autoencoder-Asset-Pricing-Models](https://github.com/RichardS0268/Autoencoder-Asset-Pricing-Models) - Reimplementation of Autoencoder Asset Pricing Models ([GKX, 2019](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3335536)).
 - [Finance](https://github.com/shashankvemuri/Finance) - 150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data.
-- [101_formulaic_alphas](https://github.com/ram-ki/101_formulaic_alphas) - Implemention of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.
+- [101_formulaic_alphas](https://github.com/ram-ki/101_formulaic_alphas) - Implementation of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.

site/index.qmd

@@ -268,7 +268,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 
 - [xts](https://github.com/joshuaulrich/xts) - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
 - [data.table](https://github.com/Rdatatable/data.table) - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
-- [sparseEigen](https://github.com/dppalomar/sparseEigen) - Sparse pricipal component analysis.
+- [sparseEigen](https://github.com/dppalomar/sparseEigen) - Sparse principal component analysis.
 - [TSdbi](http://tsdbi.r-forge.r-project.org/) - Provides a common interface to time series databases.
 - [tseries](https://cran.r-project.org/web/packages/tseries/index.html) - Time Series Analysis and Computational Finance.
 - [zoo](https://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
@@ -489,7 +489,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [Quantitative-Notebooks](https://github.com/LongOnly/Quantitative-Notebooks) - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
 - [QuantEcon](https://quantecon.org/) - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks
 - [FinanceHub](https://github.com/Finance-Hub/FinanceHub) - Resources for Quantitative Finance
-- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
+- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
 - [python-training](https://github.com/jpmorganchase/python-training) - J.P. Morgan's Python training for business analysts and traders.
 - [Stock_Analysis_For_Quant](https://github.com/LastAncientOne/Stock_Analysis_For_Quant) - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.
 - [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.
@@ -526,4 +526,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants
 - [book_irds3](https://github.com/attack68/book_irds3) - Code repository for Pricing and Trading Interest Rate Derivatives.
 - [Autoencoder-Asset-Pricing-Models](https://github.com/RichardS0268/Autoencoder-Asset-Pricing-Models) - Reimplementation of Autoencoder Asset Pricing Models ([GKX, 2019](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3335536)).
 - [Finance](https://github.com/shashankvemuri/Finance) - 150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data.
-- [101_formulaic_alphas](https://github.com/ram-ki/101_formulaic_alphas) - Implemention of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.
+- [101_formulaic_alphas](https://github.com/ram-ki/101_formulaic_alphas) - Implementation of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.

site/projects.csv

@@ -205,7 +205,7 @@ finvizfinance,Python > Visualization,2023-11-02,https://github.com/lit26/finvizf
 market-analy,Python > Visualization,2023-12-06,https://github.com/maread99/market_analy,Analysis and interactive charting using [market-prices](https://github.com/maread99/market_prices) and bqplot.,True,False,maread99/market_analy
 xts,R > Numerical Libraries & Data Structures,2024-02-06,https://github.com/joshuaulrich/xts,"eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.",True,False,joshuaulrich/xts
 data.table,R > Numerical Libraries & Data Structures,2024-02-17,https://github.com/Rdatatable/data.table,"Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.",True,False,Rdatatable/data.table
-sparseEigen,R > Numerical Libraries & Data Structures,2018-12-22,https://github.com/dppalomar/sparseEigen,Sparse pricipal component analysis.,True,False,dppalomar/sparseEigen
+sparseEigen,R > Numerical Libraries & Data Structures,2018-12-22,https://github.com/dppalomar/sparseEigen,Sparse principal component analysis.,True,False,dppalomar/sparseEigen
 TSdbi,R > Numerical Libraries & Data Structures,,http://tsdbi.r-forge.r-project.org/,Provides a common interface to time series databases.,False,False,
 tseries,R > Numerical Libraries & Data Structures,,https://cran.r-project.org/web/packages/tseries/index.html,Time Series Analysis and Computational Finance.,False,True,
 zoo,R > Numerical Libraries & Data Structures,,https://cran.r-project.org/web/packages/zoo/index.html,S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).,False,True,
@@ -349,7 +349,7 @@ fecon235,"Reproducing Works, Training & Books",2018-12-03,https://github.com/rsv
 Quantitative-Notebooks,"Reproducing Works, Training & Books",2020-07-02,https://github.com/LongOnly/Quantitative-Notebooks,"Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy",True,False,LongOnly/Quantitative-Notebooks
 QuantEcon,"Reproducing Works, Training & Books",,https://quantecon.org/,"Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks",False,False,
 FinanceHub,"Reproducing Works, Training & Books",2021-05-25,https://github.com/Finance-Hub/FinanceHub,Resources for Quantitative Finance,True,False,Finance-Hub/FinanceHub
-Python_Option_Pricing,"Reproducing Works, Training & Books",2017-07-26,https://github.com/dedwards25/Python_Option_Pricing,"An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.",True,False,dedwards25/Python_Option_Pricing
+Python_Option_Pricing,"Reproducing Works, Training & Books",2017-07-26,https://github.com/dedwards25/Python_Option_Pricing,"An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.",True,False,dedwards25/Python_Option_Pricing
 python-training,"Reproducing Works, Training & Books",2023-11-27,https://github.com/jpmorganchase/python-training,J.P. Morgan's Python training for business analysts and traders.,True,False,jpmorganchase/python-training
 Stock_Analysis_For_Quant,"Reproducing Works, Training & Books",2024-02-13,https://github.com/LastAncientOne/Stock_Analysis_For_Quant,"Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.",True,False,LastAncientOne/Stock_Analysis_For_Quant
 algorithmic-trading-with-python,"Reproducing Works, Training & Books",2021-06-01,https://github.com/chrisconlan/algorithmic-trading-with-python,Source code for Algorithmic Trading with Python (2020) by Chris Conlan.,True,False,chrisconlan/algorithmic-trading-with-python