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Python Data Analysis

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Python Data Analysis, 9781787127487 (1787127486), Packt Publishing, 2017

Key Features

  • Find, manipulate, and analyze your data using the Python 3.5 libraries
  • Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code
  • An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects.

Book Description

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.

What you will learn

  • Install 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
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Python Data Science Essentials: A practitioner's guide covering essential data science principles, tools, and techniques, 3rd Edition
Python Data Science Essentials: A practitioner's guide covering essential data science principles, tools, and techniques, 3rd Edition

Gain useful insights from your data using popular data science tools

Key Features

  • A one-stop guide to Python libraries such as pandas and NumPy
  • Comprehensive coverage of data science operations such as data cleaning and data manipulation
  • Choose scalable...
Python Network Programming: Conquer all your networking challenges with the powerful Python language
Python Network Programming: Conquer all your networking challenges with the powerful Python language

Power up your network applications with Python programming

Key Features

  • Master Python skills to develop powerful network applications
  • Grasp the fundamentals and functionalities of SDN
  • Design multi-threaded, event-driven architectures for echo and chat...
Learn to Program with Python 3: A Step-by-Step Guide to Programming
Learn to Program with Python 3: A Step-by-Step Guide to Programming

Move from zero knowledge of programming to comfortably writing small to medium-sized programs in Python. Fully updated for Python 3, with code and examples throughout, the book explains Python coding with an accessible, step-by-step approach designed to bring you comfortably into the world of software development.

...

Python Data Analytics: With Pandas, NumPy, and Matplotlib
Python Data Analytics: With Pandas, NumPy, and Matplotlib
Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. 

This revision is fully updated with new content on social media data analysis, image
...
Python for Data Mining Quick Syntax Reference
Python for Data Mining Quick Syntax Reference
?Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.

Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data
Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data

Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications.

Key Features

  • Get up and running with the Jupyter ecosystem and some example datasets
  • Learn about key machine...
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