Python for data science for dummies /
Mueller, John Paul
Python for data science for dummies / Python for data science by John Paul Mueller and Luca Massaron. - 2nd ed. - 496 pages : illustrations ; 24 cm - For dummies .
Includes index.
pt. I. Getting started with Python for data science -- Discovering the match between data science and Python -- Introducing Python's capabilities and wonders -- Setting up Python for data science -- Reviewing basic Python -- pt. II. Getting your hands dirty with data -- Working with real data -- Conditioning your data -- Shaping data -- Putting what you know in action -- pt. III. Visualizing the invisible -- Getting a crash course in MatPlotLib -- Visualizing the data -- Understanding the tools -- pt. IV. Wrangling data -- Stretching Python's capabilities -- Exploring data analysis -- Reducing dimensionality -- Clustering -- Detecting outliers in data -- pt. V. Learning from data -- Exploring four simple and effective algorithms -- Performing cross-validation, selection, and optimization -- Increasing complexity with linear and nonlinear tricks -- Understanding the power of the many -- pt. VI. The part of tens -- Ten essential data science resource collections -- Ten data challenges you should take.
9788126524938
Python (Computer program language)
Programming languages (Electronic computers)
Data mining.
Data structures (Computer science)
Data mining.
Data structures (Computer science)
Programming languages (Electronic computers)
Python (Computer program language)
QA76.73.P98 / M376 2015
005.133 / MUP
Python for data science for dummies / Python for data science by John Paul Mueller and Luca Massaron. - 2nd ed. - 496 pages : illustrations ; 24 cm - For dummies .
Includes index.
pt. I. Getting started with Python for data science -- Discovering the match between data science and Python -- Introducing Python's capabilities and wonders -- Setting up Python for data science -- Reviewing basic Python -- pt. II. Getting your hands dirty with data -- Working with real data -- Conditioning your data -- Shaping data -- Putting what you know in action -- pt. III. Visualizing the invisible -- Getting a crash course in MatPlotLib -- Visualizing the data -- Understanding the tools -- pt. IV. Wrangling data -- Stretching Python's capabilities -- Exploring data analysis -- Reducing dimensionality -- Clustering -- Detecting outliers in data -- pt. V. Learning from data -- Exploring four simple and effective algorithms -- Performing cross-validation, selection, and optimization -- Increasing complexity with linear and nonlinear tricks -- Understanding the power of the many -- pt. VI. The part of tens -- Ten essential data science resource collections -- Ten data challenges you should take.
9788126524938
Python (Computer program language)
Programming languages (Electronic computers)
Data mining.
Data structures (Computer science)
Data mining.
Data structures (Computer science)
Programming languages (Electronic computers)
Python (Computer program language)
QA76.73.P98 / M376 2015
005.133 / MUP