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

Scatter plots


A scatter plot shows the relationship between two variables in a Cartesian coordinate system. The position of each data point is determined by the values of these two variables. The scatter plot can provide hints of any correlation between the variables under study. An upward trending pattern suggests positive correlation. A bubble chart is an extension of the scatter plot. In a bubble chart, the value of a third variable is represented by the relative size of the bubble surrounding a data point, hence the name.

At http://en.wikipedia.org/wiki/Transistor_count#GPUs, there is a table with transistor counts for Graphical Processor Units (GPUs).

GPUs are specialized circuits used to display graphics efficiently. Because of the way modern display hardware works, GPUs can process data with highly parallel operations. GPUs are a new development in computing. In the gpu_transcount.csv file in this book's code bundle, you will notice that we don't have many data points. Dealing with...