Hands-on data analysis with NumPy and Pandas : implement Python packages from data manipulation to processing

Hands-on data analysis with NumPy and Pandas implement Python packages from data manipulation to processing

Get to grips with the most popular Python packages that make data analysis possible About This Book Explore the tools you need to become a data analyst Discover practical examples to help you grasp data processing concepts Walk through hierarchical indexing and grouping for data analysis Who This Bo...

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Detalles Bibliográficos
Otros Autores: Miller, Curtis, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, UK ; Mumbai : Packt 2016.
Edición:1st edition
Materias:
Numerical analysis > Data processing.
Python (Computer program language)
Information visualization.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630448206719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright and Credits
  • Packt Upsell
  • Contributors
  • Table of Contents
  • Preface
  • Chapter 1: Setting Up a Python Data Analysis Environment
  • What is Anaconda?
  • Installing Anaconda
  • Exploring Jupyter Notebooks
  • Exploring alternatives to Jupyter
  • Spyder
  • Rodeo
  • ptpython
  • Package management with Conda
  • What is Conda?
  • Conda environment management
  • Managing Python
  • Package management
  • Setting up a database
  • Installing MySQL
  • MySQL connectors
  • Creating a database
  • Summary
  • Chapter 2: Diving into NumPY
  • NumPy arrays
  • Special numeric values
  • Creating NumPy arrays
  • Creating ndarray
  • Summary
  • Chapter 3: Operations on NumPy Arrays
  • Selecting elements explicitly
  • Slicing arrays with colons
  • Advanced indexing
  • Expanding arrays
  • Arithmetic and linear algebra with arrays
  • Arithmetic with two equal-shaped arrays
  • Broadcasting
  • Linear algebra
  • Employing array methods and functions
  • Array methods
  • Vectorization with ufuncs
  • Custom ufuncs
  • Summary
  • Chapter 4: pandas are Fun! What is pandas?
  • What does pandas do?
  • Exploring series and DataFrame objects
  • Creating series
  • Creating DataFrames
  • Adding data
  • Saving DataFrames
  • Subsetting your data
  • Subsetting a series
  • Indexing methods
  • Slicing a DataFrame
  • Summary
  • Chapter 5: Arithmetic, Function Application, and Mapping with pandas
  • Arithmetic
  • Arithmetic with DataFrames
  • Vectorization with DataFrames
  • DataFrame function application
  • Handling missing data in a pandas DataFrame
  • Deleting missing information
  • Filling missing information
  • Summary
  • Chapter 6: Managing, Indexing, and Plotting
  • Index sorting
  • Sorting by values
  • Hierarchical indexing
  • Slicing a series with a hierarchical index
  • Plotting with pandas
  • Plotting methods
  • Summary.
  • Other Books You May Enjoy
  • Index.

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