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Learning pandas

You're reading from   Learning pandas High performance data manipulation and analysis using Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787123137
Length 446 pages
Edition 2nd Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (16) Chapters Close

Preface 1. pandas and Data Analysis FREE CHAPTER 2. Up and Running with pandas 3. Representing Univariate Data with the Series 4. Representing Tabular and Multivariate Data with the DataFrame 5. Manipulating DataFrame Structure 6. Indexing Data 7. Categorical Data 8. Numerical and Statistical Methods 9. Accessing Data 10. Tidying Up Your Data 11. Combining, Relating, and Reshaping Data 12. Data Aggregation 13. Time-Series Modelling 14. Visualization 15. Historical Stock Price Analysis

Reading and writing HDF5 format files

HDF5 is a data model, library, and file format to store and manage data. It is commonly used in scientific computing environments. It supports an unlimited variety of data types, and is designed for flexible and efficient I/O, and for high volume and complex data.

HDF5 is portable and extensible, allowing applications to evolve in their use of HDF5. The HDF5 Technology Suite includes tools and applications to manage, manipulate, view, and analyze data in the HDF5 format. HDF5 is:

  • A versatile data model that can represent very complex data objects and a wide variety of metadata
  • A completely portable file format with no limit on the number or size of data objects in the collection
  • A software library that runs on a range of computational platforms, from laptops to massively parallel systems, and implements a high-level API with C, C++, Fortran...
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