docs

Author: Krzysztof Joachimiak

README.md

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 > Probably the best curated list of data science software in Python
 
-## Contents
+## Contents {docsify-ignore}
 * [Machine Learning](#ml)
 * [Deep Learning](#dl)
 * [Data Manipulation](#data-man)
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 * [Veles](https://github.com/Samsung/veles) - Distributed machine learning platform.
 * [Jubatus](https://github.com/jubatus/jubatus) - Framework and Library for Distributed Online Machine Learning.
 * [DMTK](https://github.com/Microsoft/DMTK) - Microsoft Distributed Machine Learning Toolkit.
-* [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) - PArallel Distributed Deep LEarning
+* [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) - PArallel Distributed Deep LEarning.
 * [dask-ml](https://github.com/dask/dask-ml) - Distributed and parallel machine learning. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [Distributed](https://github.com/dask/distributed) - Distributed computation in Python.
 
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 ## Statistics
 * [pandas_summary](https://github.com/mouradmourafiq/pandas-summary) - Extension to pandas dataframes describe function. <img height="20" src="img/pandas_big.png" alt="pandas compatible">
 * [Pandas Profiling](https://github.com/pandas-profiling/pandas-profiling) - Create HTML profiling reports from pandas DataFrame objects. <img height="20" src="img/pandas_big.png" alt="pandas compatible">
-* [statsmodels](https://github.com/statsmodels/statsmodels) - Statistical modeling and econometrics in Python
+* [statsmodels](https://github.com/statsmodels/statsmodels) - Statistical modeling and econometrics in Python.
 * [stockstats](https://github.com/jealous/stockstats) - Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.
 * [weightedcalcs](https://github.com/jsvine/weightedcalcs) - pandas-based utility to calculate weighted means, medians, distributions, standard deviations, and more.
 * [scikit-posthocs](https://github.com/maximtrp/scikit-posthocs) - Pairwise Multiple Comparisons Post-hoc Tests.