Getting Started with Python Data Analysis

Cover
Preface
Copyright
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Table of Contents
Chapter 1: Introducing Data Analysis and Libraries
Data analysis and processing
An overview of the libraries in data analysis
Python libraries in data analysis
NumPy
Pandas
Matplotlib
PyMongo
The scikit-learn library
Summary
Chapter 2: NumPy Arrays and Vectorized Computation
NumPy arrays
Data types
Array creation
Indexing and slicing
Fancy indexing
Numerical operations on arrays
Array functions
Data processing using arrays
Loading and saving data
Saving an array
Loading an array
Linear algebra with NumPy
NumPy random numbers
Summary
Chapter 3: Data Analysis with Pandas
An overview of the Pandas package
The Pandas data structure
Series
The DataFrame
The essential basic functionality
Reindexing and altering labels
Head and tail
Binary operations
Functional statistics
Function application
Sorting
Indexing and selecting data
Computational tools
Working with missing data
Advanced uses of Pandas for data analysis
Hierarchical indexing
The Panel data
Summary
Chapter 4: Data Visualization
The matplotlib API primer
Line properties
Figures and subplots
Exploring plot types
Scatter plots
Bar plots
Contour plots
Histogram plots
Legends and annotations
Plotting functions with Pandas
Additional Python data visualization tools
Bokeh
MayaVi
Summary
Chapter 5: Time series
Time series primer
Working with date and time objects
Resampling time series
Downsampling time series data
Upsampling time series data
Time zone handling
Timedeltas
Time series plotting
Summary
Chapter 6: Interacting With Databases
Interacting with data in text format
Reading data from text format
Writing data to text format
Interacting with data in binary format
HDF5
Interacting with data in MongoDB
Interacting with data in Redis
The simple value
List
Set
Ordered set
Summary
Chapter 7: Data Analysis Application Examples
Data munging
Cleaning data
Filtering
Merging data
Reshaping data
Data aggregation
Grouping data
Summary
Chapter 8: Machine Learning Models with scikit-learn
An overview of machine learning models
The scikit-learn modules for different models
Data representation in scikit-learn
Supervised learning – classification and regression
Unsupervised learning – clustering and dimensionality reduction
Measuring prediction performance
Summary
Index