Fandango Armando. Python Data Analysis

2nd Ed. — Packt Publishing, 2017. — 351 p. — ISBN10: 1787127486, ISBN13: 978-1787127487.
Code filesWith this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis.
The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.What you will learnInstall open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms
Prepare and clean your data, and use it for exploratory analysis
Manipulate your data with Pandas
Retrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and.