Mastering pandas : master the features and capabilities of pandas, a data analysis toolkit for Python /
Anthony, Femi,
Mastering pandas : master the features and capabilities of pandas, a data analysis toolkit for Python / Femi Anthony. - 1 online resource (1 volume) : illustrations - Community experience distilled . - Community experience distilled. .
Includes index.
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to pandas and Data Analysis; Motivation for data analysis; We live in a big data world; 4 V's of big data; Volume of big data; Velocity of big data; Variety of big data; Veracity of big data; So much data, so little time for analysis; The move towards real-time analytics; How Python and pandas fit into the data analytics mix; What is pandas; Benefits of using pandas; Summary; Chapter 2: Installation of pandas and Supporting Software Selecting a version of Python to usePython installation; Linux; Installing Python from compressed tarball; Windows; Core Python installation; Third-party Python software install; Mac OS/X; Installation using a package manager; Installation of Python and pandas from a third-party vendor; Continuum Analytics Anaconda; Installing Anaconda; Linux; Mac OS/X; Windows; Final step for all platforms; Other numeric or analytics-focused Python distributions; Downloading and installing pandas; Linux; Ubuntu/Debian; Red Hat; Ubuntu/Debian; Fedora; OpenSuse; Mac; Source installation; Binary installation WindowsBinary Installation; Source installation; IPython; IPython Notebook; IPython installation; Linux; Windows; Mac OS/X; Install via Anaconda (for Linux/Mac OS/X); Wakari by Continuum Analytics; Virtualenv; Virtualenv installation and usage; Summary; Chapter 3: The pandas Data Structures; NumPy ndarrays; NumPy array creation; NumPy arrays via numpy.array; NumPy array via numpy.arange; NumPy array via numpy.linspace; NumPy array via various other functions; NumPy datatypes; NumPy indexing and slicing; Array slicing; Array masking; Complex indexing; Copies and views; Operations Basic operationsReduction operations; Statistical operators; Logical operators; Broadcasting; Array shape manipulation; Flattening a multi-dimensional array; Reshaping; Resizing; Adding a dimension; Array sorting; Data structures in pandas; Series; Series creation; Operations on Series; DataFrame; DataFrame Creation; Operations; Panel; Using 3D NumPy array with axis labels; Using a Python dictionary of DataFrame objects; Using the DataFrame.to_panel method; Other operations; Summary; Chapter 4: Operations in Pandas, Part I -- Indexing and Selecting; Basic indexing Accessing attributes using dot operatorRange slicing; Label, integer, and mixed indexing; Label-oriented indexing; Selection using a Boolean array; Integer-oriented indexing; The .iat and .at operators; Mixed indexing with the .ix operator; Multi-indexing; Swapping and re-ordering levels; Cross-sections; Boolean indexing; The is in and any all methods; Using the where method; Operations on indexes; Summary; Chapter 5: Operations in pandas, Part II -- Grouping, Merging, and Reshaping of Data; Grouping of data; The groupby operation; Using groupby with a MultiIndex; Using the aggregate method
This book is intended for Python programmers, mathematicians, and analysts who already have a basic understanding of Python and wish to learn about its data analysis capabilities in depth.
9781783981977 (electronic bk.) 1783981970 (electronic bk.)
CL0500000614 Safari Books Online
018006900 Uk
Python (Computer program language)
Data structures (Computer science)
Statistics--Computer programs.
Quantitative research.
Python (Langage de programmation)
Structures de données (Informatique)
Statistique--Logiciels.
Recherche quantitative.
COMPUTERS--Programming Languages--C#
COMPUTERS--Programming Languages--Java.
COMPUTERS--Programming Languages--Pascal.
Data structures (Computer science)
Python (Computer program language)
Quantitative research.
Statistics--Computer programs.
Electronic books.
QA76.73.P98
005.133
Mastering pandas : master the features and capabilities of pandas, a data analysis toolkit for Python / Femi Anthony. - 1 online resource (1 volume) : illustrations - Community experience distilled . - Community experience distilled. .
Includes index.
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to pandas and Data Analysis; Motivation for data analysis; We live in a big data world; 4 V's of big data; Volume of big data; Velocity of big data; Variety of big data; Veracity of big data; So much data, so little time for analysis; The move towards real-time analytics; How Python and pandas fit into the data analytics mix; What is pandas; Benefits of using pandas; Summary; Chapter 2: Installation of pandas and Supporting Software Selecting a version of Python to usePython installation; Linux; Installing Python from compressed tarball; Windows; Core Python installation; Third-party Python software install; Mac OS/X; Installation using a package manager; Installation of Python and pandas from a third-party vendor; Continuum Analytics Anaconda; Installing Anaconda; Linux; Mac OS/X; Windows; Final step for all platforms; Other numeric or analytics-focused Python distributions; Downloading and installing pandas; Linux; Ubuntu/Debian; Red Hat; Ubuntu/Debian; Fedora; OpenSuse; Mac; Source installation; Binary installation WindowsBinary Installation; Source installation; IPython; IPython Notebook; IPython installation; Linux; Windows; Mac OS/X; Install via Anaconda (for Linux/Mac OS/X); Wakari by Continuum Analytics; Virtualenv; Virtualenv installation and usage; Summary; Chapter 3: The pandas Data Structures; NumPy ndarrays; NumPy array creation; NumPy arrays via numpy.array; NumPy array via numpy.arange; NumPy array via numpy.linspace; NumPy array via various other functions; NumPy datatypes; NumPy indexing and slicing; Array slicing; Array masking; Complex indexing; Copies and views; Operations Basic operationsReduction operations; Statistical operators; Logical operators; Broadcasting; Array shape manipulation; Flattening a multi-dimensional array; Reshaping; Resizing; Adding a dimension; Array sorting; Data structures in pandas; Series; Series creation; Operations on Series; DataFrame; DataFrame Creation; Operations; Panel; Using 3D NumPy array with axis labels; Using a Python dictionary of DataFrame objects; Using the DataFrame.to_panel method; Other operations; Summary; Chapter 4: Operations in Pandas, Part I -- Indexing and Selecting; Basic indexing Accessing attributes using dot operatorRange slicing; Label, integer, and mixed indexing; Label-oriented indexing; Selection using a Boolean array; Integer-oriented indexing; The .iat and .at operators; Mixed indexing with the .ix operator; Multi-indexing; Swapping and re-ordering levels; Cross-sections; Boolean indexing; The is in and any all methods; Using the where method; Operations on indexes; Summary; Chapter 5: Operations in pandas, Part II -- Grouping, Merging, and Reshaping of Data; Grouping of data; The groupby operation; Using groupby with a MultiIndex; Using the aggregate method
This book is intended for Python programmers, mathematicians, and analysts who already have a basic understanding of Python and wish to learn about its data analysis capabilities in depth.
9781783981977 (electronic bk.) 1783981970 (electronic bk.)
CL0500000614 Safari Books Online
018006900 Uk
Python (Computer program language)
Data structures (Computer science)
Statistics--Computer programs.
Quantitative research.
Python (Langage de programmation)
Structures de données (Informatique)
Statistique--Logiciels.
Recherche quantitative.
COMPUTERS--Programming Languages--C#
COMPUTERS--Programming Languages--Java.
COMPUTERS--Programming Languages--Pascal.
Data structures (Computer science)
Python (Computer program language)
Quantitative research.
Statistics--Computer programs.
Electronic books.
QA76.73.P98
005.133