Python data analysis : learn how to apply powerful data analysis techniques with popular open source Python modules

Packt Publishing, 2014. — 348 p. — ISBN: 1783553359, 9781783553358 Dive deeper into data analysis with the flexibility of Python and learn how its extensive range of scientific and mathematical libraries can be used to solve some of the toughest challenges in data analysis. Build your confidence and expertise and develop valuable skills in high demand in a world driven by Big Data with this expert data analysis book. This data science tutorial will help you learn how to effectively retrieve, clean, manipulate, and visualize data and establish a successful data analysis workflow. Apply the impressive functionality of Python's data mining tools and scientific and numerical libraries to a range of the most important tasks within data analysis and data science, and develop strategies and ideas to take control your own data analysis projects. Get to grips with statistical analysis using NumPy and SciPy, visualize data with Matplotlib, and uncover sophisticated insights through predictive analytics and machine learning with SciKit-Learn. You will also learn how to use the tools needed to work with databases and find out how Python can be used to analyze textual and social media data, as you work through this essential data science tutorial. Python Data Analysis makes the difficult challenges of data analysis easier, offering you practical guidance that doesn't reduce the complexity of the tasks and technology at hand but instead makes them much more manageable. Learn how to find, manipulate, and analyze data using Python Perform advanced, high performance linear algebra and mathematical calculations with clean and efficient Python code Explore predictive analytics and machine learning using SciKit-Learn with this Python machine learning tutorial Learn cluster and regression analysis Gain insights into textual data and social media with NLTK Create effective visualizations to present your data using Matplotlib Do more with your databases and explore the relationship between MongoDB and PyMongo Discover techniques and tricks for performance tuning and concurrency Learn how to apply powerful data analysis techniques with popular open source Python modulesPython is a multi-paradigm programming language well suited for both object-oriented application development as well as functional design patterns. Python has become the language of choice for data scientists for data analysis, visualization, and machine learning. It will give you velocity and promote high productivity.This book will teach novices about data analysis with Python in the broadest sense possible, covering everything from data retrieval, cleaning, manipulation, visualization, and storage to complex analysis and modeling. It focuses on a plethora of open source Python modules such as NumPy, SciPy, matplotlib, pandas, IPython, Cython, scikit-learn, and NLTK. In later chapters, the book covers topics such as data visualization, signal processing, and time-series analysis, databases, predictive analytics and machine learning. This book will turn you into an ace data analyst in no time.

Python is a multi-paradigm programming language well suited for both object-oriented application development as well as functional design patterns. Python has become the language of choice for data scientists for data analysis, visualization, and machine learning. It will give you velocity and promote high productivity.

This book will teach novices about data analysis with Python in the broadest sense possible, covering everything from data retrieval, cleaning, manipulation, visualization, and storage to complex analysis and modeling. It focuses on a plethora of open source Python modules such as NumPy, SciPy, matplotlib, pandas, IPython, Cython, scikit-learn, and NLTK. In later chapters, the book covers topics such as data visualization, signal processing, and time-series analysis, databases, predictive analytics and machine learning. This book will turn you into an ace data analyst in no time.

Python is a multi-paradigm programming language well suited for both object-oriented application development as well as functional design patterns. Python has become the language of choice for data scientists for data analysis, visualization, and machine learning. It will give you velocity and promote high productivity. This book will teach novices about data analysis with Python in the broadest sense possible, covering everything from data retrieval, cleaning, manipulation, visualization, and storage to complex analysis and modeling. It focuses on a plethora of open source Python modules such as NumPy, SciPy, matplotlib, pandas, IPython, Cython, scikit-learn, and NLTK. In later chapters, the book covers topics such as data visualization, signal processing, and time-series analysis, databases, predictive analytics and machine learning. This book will turn you into an ace data analyst in no time This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.