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Title Page
Copyright and Credits
Hands-On Data Analysis with NumPy and pandas
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Contributors
About the author
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Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Conventions used
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Reviews
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
Diving into NumPY
NumPy arrays
Special numeric values
Creating NumPy arrays
Creating ndarray
Summary
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
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
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
Managing, Indexing, and Plotting
Index sorting
Sorting by values
Hierarchical indexing
Slicing a series with a hierarchical index
Plotting with pandas
Plotting methods
Summary
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