Author Description

Leverage the power of Python to clean, scrape, analyze, and visualize your data About This Book • Clean, format, and explore your data using the popular Python libraries and get valuable insights from it • Analyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and more • Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended. What You Will Learn • Understand the importance of data analysis and master its processing steps • Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy • Clean and transform your data and apply advanced statistical analysis to create attractive visualizations • Analyze images and time series data • Mine text and analyze social networks • Perform web scraping and work with different databases, Hadoop, and Spark • Use statistical models to discover patterns in data • Detect similarities and differences in data with clustering • Work with Jupyter Notebook to produce publication-ready figures to be included in reports In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further,