Key FeaturesGet comfortable using pandas and Python as an effective data exploration and analysis toolExplore pandas through a framework of data analysis, with an explanation of how pandas is well suited for the various stages in a data analysis processA comprehensive guide to pandas with many of clear and practical examples to help you get up and using pandasBook DescriptionYou will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.What you will learnUnderstand how data analysts and scientists think about of the processes of gathering and understanding dataLearn how pandas can be used to support the end-to-end process of data analysisUse pandas Series and DataFrame objects to represent single and multivariate dataSlicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sourcesHow to access data from external sources such as files, databases, and web servicesRepresent and manipulate time-series data and the many of the intricacies involved with this type of dataHow to visualize statistical informationHow to use pandas to solve several common data representation and analysis problems within financeAbout the AuthorMichael Heydt is a technologist, entrepreneur, and educator with decades of professional software development and financial and commodities trading experience. He has worked extensively on Wall Street specializing in the development of distributed, actor-based, highperformance, and high-availability trading systems. He is currently founder of Micro Trading Services, a company that focuses on creating cloud and micro service-based software solutions for finance and commodities trading. He holds a masters in science in mathematics and computer science from Drexel University, and an executive masters of technology management from the University of Pennsylvania School of Applied Science and the Wharton School of Business.Table of Contentspandas and Data Science and AnalysisUp and running with pandasRepresenting univariate data with the SeriesRepresenting tabular and multivariate data with the DataFrameManipulation and indexing of DataFrame objectsIndexing DataCategorical DataNumeric and Statistical MethodsGrouping and Aggregating DataTidying Up Your DataCombining, Relating and Reshaping DataData AggregationTime-Series ModellingVisualizationApplications to Finance
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