# <i class="fas fa-book fa-fw"></i> Pandas

Topics:  
* [DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/frame.html)  
* [Series](https://pandas.pydata.org/pandas-docs/stable/reference/series.html)    
* TODO: Melt and Pivot  
* TODO: Consider combining Pandas & Numpy
* TODO: Cheatsheet of popular methods
    * loc, iloc, take, nlargest, idxmax, groupby, items(), reset_index, 
    * read_csv(index_col, na_values, thousands, usecols, dtype)


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