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Python Data Science Cookbook
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Python Data Science Cookbook
by Gopi Subramanian
Python Data Science Cookbook
Python Data Science Cookbook
Table of Contents
Python Data Science Cookbook
Credits
About the Author
About the Reviewer
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Preface
What this book covers
What you need for this book
Who this book is for
Sections
Getting ready
How to do it…
How it works…
There's more…
See also
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
1. Python for Data Science
Introduction
Using dictionary objects
Getting ready
How to do it…
How it works…
There's more…
See also
Working with a dictionary of dictionaries
Getting ready
How to do it…
How it works…
See also
Working with tuples
Getting ready
How to do it…
How it works…
There's more…
See also
Using sets
Getting ready
How to do it…
How it works…
There's more…
Writing a list
Getting ready
How to do it…
How it works…
There's more…
Creating a list from another list - list comprehension
Getting ready
How to do it…
How it works…
There's more…
Using iterators
Getting ready
How to do it…
How it works…
There's more…
Generating an iterator and a generator
Getting ready
How it do it…
How it works…
There's more…
Using iterables
Getting ready
How to do it…
How it works..
See also
Passing a function as a variable
Getting ready
How to do it…
How it works…
Embedding functions in another function
Getting ready
How to do it…
How it works…
Passing a function as a parameter
Getting ready
How to do it…
How it works…
Returning a function
Getting ready
How to do it…
How it works…
There's more…
Altering the function behavior with decorators
Getting ready
How to do it…
How it works…
Creating anonymous functions with lambda
Getting ready
How to do it…
How it works…
Using the map function
Getting ready
How to do it…
How it works…
There's more…
Working with filters
Getting ready
How to do it…
How it works…
Using zip and izip
Getting ready
How to do it…
How it works…
There's more…
See also
Processing arrays from the tabular data
Getting ready
How to do it…
How it works…
There's more…
Preprocessing the columns
Getting ready
How to do it…
How it works…
There's more…
Sorting lists
Getting ready
How to do it…
How it works…
There's more…
Sorting with a key
Getting ready
How to do it…
How it works…
There's more…
Working with itertools
Getting ready
How to do it…
How it works…
2. Python Environments
Introduction
Using NumPy libraries
Getting ready
How to do it…
How it works…
There's more…
See also
Plotting with matplotlib
Getting ready
How to do it…
How it works…
There's more…
Machine learning with scikit-learn
Getting ready
How to do it…
How it works…
There's more…
See also
3. Data Analysis – Explore and Wrangle
Introduction
Analyzing univariate data graphically
Getting ready
How to do it…
How it works…
See also
Grouping the data and using dot plots
Getting ready
How to do it…
How it works…
See also
Using scatter plots for multivariate data
Getting ready
How to do it…
How it works…
See also
Using heat maps
Getting ready
How to do it…
How it works…
There's more...
See also
Performing summary statistics and plots
Getting ready
How to do it…
How it works…
See also
Using a box-and-whisker plot
Getting ready
How to do it…
How it works…
There's more…
Imputing the data
Getting ready
How to do it…
How it works…
There's more…
See also
Performing random sampling
Getting ready
How to do it…
How it works…
There's more…
Stratified sampling
Progressive sampling
Scaling the data
Getting ready
How to do it…
How it works…
There's more…
Standardizing the data
Getting ready
How to do it…
How it works…
There's more…
Performing tokenization
Getting ready
How to do it…
How it works…
There's more…
See also
Removing stop words
How to do it…
How it works…
There's more…
See also
Stemming the words
Getting ready
How to do it…
How it works…
There's more…
See also
Performing word lemmatization
Getting ready
How to do it…
How it works…
There's more…
See also
Representing the text as a bag of words
Getting ready
How to do it…
How it works…
There's more…
See also
Calculating term frequencies and inverse document frequencies
Getting ready
How to do it…
How it works…
There's more…
4. Data Analysis – Deep Dive
Introduction
Matrix Decomposition:
Extracting the principal components
Getting ready
How to do it…
How it works…
There's more…
See also
Using Kernel PCA
Getting ready
How to do it…
How it works…
There's more…
Extracting features using singular value decomposition
Getting ready
How to do it…
How it works…
There's more…
Reducing the data dimension with random projection
Getting ready
How to do it…
How it works…
There's more…
See also
Decomposing the feature matrices using non-negative matrix factorization
Getting ready
How to do it…
How it works…
There's more…
See also
5. Data Mining – Needle in a Haystack
Introduction
Working with distance measures
Getting ready
How to do it…
How it works…
There's more...
See also
Learning and using kernel methods
Getting ready
How to do it…
How it works…
There's more...
See also
Clustering data using the k-means method
Getting ready
How to do it…
How it works…
There's more...
See also
Learning vector quantization
Getting ready
How to do it…
How it works…
There's more...
See also
Finding outliers in univariate data
Getting ready
How to do it…
How it works…
There's more…
See also
Discovering outliers using the local outlier factor method
Getting ready
How to do it…
How it works…
There's more…
6. Machine Learning 1
Introduction
Preparing data for model building
Getting ready
How to do it…
How it works…
There's more...
Finding the nearest neighbors
Getting ready
How to do it…
How it works…
There's more…
See also
Classifying documents using Naïve Bayes
Getting ready
How to do it…
How it works…
There's more…
See also
Building decision trees to solve multiclass problems
Getting ready
How to do it…
How it works…
There's more…
See also
7. Machine Learning 2
Introduction
Predicting real-valued numbers using regression
Getting ready
How to do it…
How it works…
There's more...
See also
Learning regression with L2 shrinkage – ridge
Getting ready
How to do it…
How it works…
There's more…
See also
Learning regression with L1 shrinkage – LASSO
Getting ready
How to do it…
How it works…
There's more…
See also
Using cross-validation iterators with L1 and L2 shrinkage
Getting ready
How to do it…
How it works…
There's more…
See also
8. Ensemble Methods
Introduction
Understanding Ensemble – Bagging Method
Getting ready…
How to do it
How it works…
There's more…
See also
Understanding Ensemble – Boosting Method
Getting Started…
How to do it
How it works…
There's more…
See also
Understanding Ensemble – Gradient Boosting
Getting Started…
How to do it
How it works…
There's more…
See also
9. Growing Trees
Introduction
Going from trees to Forest – Random Forest
Getting ready
How to do it...
How it works…
There's more…
See also
Growing Extremely Randomized Trees
Getting ready…
How to do it...
How it works…
There's more…
See also
Growing Rotational Forest
Getting ready…
How to do it...
How it works…
There's more…
See also
10. Large-Scale Machine Learning – Online Learning
Introduction
Using perceptron as an online learning algorithm
Getting ready
How to do it…
How it works…
There's more…
See also
Using stochastic gradient descent for regression
Getting ready
How to do it…
How it works…
There's more…
See also
Using stochastic gradient descent for classification
Getting ready
How to do it…
How it works…
There's more…
See also
Index
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