July 2019
Beginner to intermediate
740 pages
16h 52m
English
Content preview from Hands-On Data Analysis with Pandas
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Summary
In this chapter, we saw how building Python packages for our analysis applications can make it very easy for others to carry out their own analyses and reproduce ours. The stock_analysis package we created in this chapter contained classes for gathering stock data from the Internet (StockReader); visualizing individual assets or groups of them (Visualizer family); calculating metrics for single assets or groups of them for comparisons (StockAnalyzer and AssetGroupAnalyzer, respectively); and time series modeling with decomposition, ARIMA, and linear regression (StockModeler). We also got our first look at using the statsmodels package in the StockModeler class. This chapter showed us how the pandas, matplotlib, seaborn, and numpy ...
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