Book Image

Python Data Analysis - Second Edition

By : Ivan Idris
Book Image

Python Data Analysis - Second Edition

By: Ivan Idris

Overview of this book

Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With 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.
Table of Contents (22 chapters)
Python Data Analysis - Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Key Concepts
Online Resources

Using Fortran code through f2py


Fortran (derived from Formula Translation) is a mature programming language mostly used for scientific computing. It was developed in the 1950s with newer versions emerging, such as Fortran 77, Fortran 90, Fortran 95, Fortran 2003, and Fortran 2008 (refer to http://en.wikipedia.org/wiki/Fortran). Each version added features and new programming paradigms. We will need a Fortran compiler for this example. The gfortran compiler is a GNU Fortran compiler, and can be downloaded from http://gcc.gnu.org/wiki/GFortranBinaries.

The NumPy f2py module serves as an interface between Fortran and Python. If a Fortran compiler is present, we can create a shared library from Fortran code using this module. We will write a Fortran subroutine that is intended to sum the rain amount values as given in the previous examples. Define the subroutine and store it in a Python string. After that, we can call the f2py.compile() function to produce a shared library from the Fortran code...