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

PythonAnywhere Cloud


PythonAnywhere is a Cloud service for Python development. The interface is completely web-based and simulates the Bash, Python, and IPython consoles. The preinstalled Python libraries in the PythonAnywhere environment are listed at https://www.pythonanywhere.com/batteries_included/.

The software version may lag a little behind the latest stable versions available. At the time of writing, installing Python software from the PythonAnywhere Bash console appears a bit problematic and is not recommended.

When you first visit the URL https://www.pythonanywhere.com/login/, you will see the following screen to log into the PythonAnywhere environment:

After you submit your login name and password, you will see the following web application screen:

It is recommended that you upload Python source files instead of using the PythonAnywhere environment, as it is less responsive than our local environment. Upload the files by clicking on the Files tab in the web application. Upload...