Index

A

• Anaconda
  • Python, installing with / Installing Python with Anaconda
  • downloading / Downloading Anaconda
  • installing / Installing Anaconda
  • terminal, opening / Opening a terminal
  • home directory, finding / Finding your home directory
  • system's PATH, manipulating / Manipulating your system path
  • installation, testing / Testing your installation
  • environments, managing / Managing environments
  • conda commands / Common conda commands
  • references / References
  • notebooks, downloading / Downloading the notebooks
• arguments / Functions
• array manipulation routines
  • references / Basic array manipulations
• arrays
  • creating / Creating arrays
  • references / Creating arrays
  • loading, from files / Loading arrays from files
  • basic array manipulations / Basic array manipulations
  • computing / Computing with NumPy arrays
  • selection / Selection and indexing
  • indexing / Selection and indexing
  • boolean operations / Boolean operations on arrays
  • mathematical operations / Mathematical operations on arrays
  • density map, with NumPy / A density map with NumPy

B

• Basemap
  • about / The matplotlib Basemap toolkit
  • references / The matplotlib Basemap toolkit
• Bokeh
  • about / Bokeh
  • references / Bokeh
• boolean operations
  • on arrays / Boolean operations on arrays
• brew
  • URL / Using IPython as an extended shell
• broadcasting
  • about / Basic array manipulations
• brownian motion / Random walk

C

• C
  • writing in Python, Cython used / Writing C in Python with Cython
• C++
  • URL / C/C++ with Python
• C/C++, with Python
  • about / C/C++ with Python
  • Cython / C/C++ with Python
  • SWIG / C/C++ with Python
  • weave / C/C++ with Python
  • ctypes / C/C++ with Python
  • cffi / C/C++ with Python
• C compiler
  • installing / Installing Cython and a C compiler for Python
• chaining syntax / Joins
• code cell, Notebook / Structure of a notebook cell, Code cells
• column-major order (Fortran-order)
  • about / How an ndarray is stored in memory
• computing, techniques
  • about / Further high-performance computing techniques
  • Message Passing Interace (MPI) / MPI
  • distributed computing / Distributed computing
  • C/C++, with Python / C/C++ with Python
  • Graphics Processing Units (GPUs) / GPU computing
  • PyPy / PyPy
  • Julia / Julia
• conda / Installing Python with Anaconda
  • commands / Common conda commands
• conditional branches / Conditional branches
• ctypes / C/C++ with Python
• Cython
  • used, for writing C in Python / Writing C in Python with Cython
  • installing / Installing Cython and a C compiler for Python
  • Eratosthenes Sieve, implementing / Implementing the Eratosthenes Sieve in Python and Cython
  • URL / Implementing the Eratosthenes Sieve in Python and Cython, C/C++ with Python
  • user guide, URL / Implementing the Eratosthenes Sieve in Python and Cython
  • tutorials, URL / Implementing the Eratosthenes Sieve in Python and Cython

D

• 3D visualization libraries
  • about / 3D visualization
  • Mayavi / Mayavi
  • VisPy / VisPy
• data
  • manipulating / Manipulating data
  • selecting / Selecting data
  • columns, selecting / Selecting columns
  • rows, selecting / Selecting rows
  • boolean indexing, filtering with / Filtering with boolean indexing
  • numbers, computing with / Computing with numbers
  • text, working with / Working with text
  • dates and times, working with / Working with dates and times
  • missing data, handling / Handling missing data
• Data-Driven Documents (D3)
  • about / Displaying rich HTML elements in the Notebook
  • references / JavaScript and D3 in the Notebook
• dataset, in Notebook
  • exploring / Exploring a dataset in the Notebook
  • data subset / Provenance of the data
  • URL / Provenance of the data
  • references / Provenance of the data
  • public datasets / Provenance of the data
  • downloading / Downloading and loading a dataset
  • loading / Downloading and loading a dataset
  • plots creating, matplotlib used / Making plots with matplotlib
  • descriptive statistics, with pandas and seaborn / Descriptive statistics with pandas and seaborn
• decorators
  • about / Functional programming
  • URL / Functional programming
• density map
  • computing / A density map with NumPy
• distributed computing
  • Apache Spark / Distributed computing
  • Dask / Distributed computing
  • xray / Distributed computing
  • Bolt / Distributed computing

E

• Eratosthenes Sieve
  • implementing, in Python / Implementing the Eratosthenes Sieve in Python and Cython
  • implementing, in Cython / Implementing the Eratosthenes Sieve in Python and Cython
• expit function
  • about / A density map with NumPy

F

• functional programming / Functional programming
• functions / Functions

G

• General-Purpose GPU computing (GPUGPU) / GPU computing
• GeoPandas
  • about / GeoPandas
• Git Distributed Version Control System (DVCS) / Downloading the notebooks
• GitHub / Downloading the notebooks
• GNU C Compiler (gcc) / Installing Cython and a C compiler for Python
• Graphics Processing Units (GPUs)
  • about / GPU computing
• group-by operation
  • about / Group-by
• GUI event loop support
  • URL / GUI toolkits

H

• high-level plotting libraries
  • about / High-level plotting
  • Bokeh / Bokeh
  • Vincent and Vega / Vincent and Vega
  • Plotly / Plotly
• HTML elements
  • displaying, in Notebook / Displaying rich HTML elements in the Notebook

I

• IJulia kernel
  • URL / Julia
• image processing
  • about / Image processing
• indentation / Indentation
• InteractiveShell instance
  • URL / Creating a custom magic command in an IPython extension
• IPython
  • about / Jupyter and IPython
  • references / References, Other topics
  • features / Ten Jupyter/IPython essentials
  • display system, URL / Displaying SVG in the Notebook
• IPython, features
  • IPython, using as extended shell / Using IPython as an extended shell
  • magic commands / Learning magic commands
  • tab completion / Mastering tab completion
  • Markdown cell, in Notebook / Writing interactive documents in the Notebook with Markdown
  • interactive widgets, creating in Notebook / Creating interactive widgets in the Notebook
  • Python scripts, running from IPython / Running Python scripts from IPython
  • Python objects, introspecting / Introspecting Python objects
  • Python code, debugging / Debugging Python code
  • Python code, benchmarking / Benchmarking Python code
  • Python code, profiling / Profiling Python code
• IPython.parallel
  • about / Distributing tasks on several cores with IPython.parallel
  • direct interface / Direct interface
  • load-balanced interface / Load-balanced interface
  • documentation, URL / Load-balanced interface
• IPython 4.0
  • URL / Jupyter and IPython
• IPython Cookbook
  • URL / What this book covers, Writing C in Python with Cython
• IPython extension
  • custom magic command, creating / Creating a custom magic command in an IPython extension
  • about / Creating a custom magic command in an IPython extension

J

• JavaScript
  • used, for customizing Notebook interface / Customizing the Notebook interface with JavaScript
• JavaScript extensions
  • URL / Customizing the Notebook interface with JavaScript
• joins
  • about / Joins
• Julia
  • about / Julia
• Jupyter
  • about / Jupyter and IPython
  • Notebook, URL / Jupyter and IPython
  • URL / Jupyter and IPython
  • features / Ten Jupyter/IPython essentials
• Jupyter kernel
  • writing / Writing a new Jupyter kernel
  • references / Writing a new Jupyter kernel
• Jupyter Notebook
  • launching / Launching the Jupyter Notebook
• Just-In-Compiler (JIT) / Accelerating Python code with Numba

K

• kernel / The Notebook dashboard
• keyword arguments / Positional and keyword arguments

L

• Leaflet
  • about / Leaflet wrappers: folium and mplleaflet
  • folium / Leaflet wrappers: folium and mplleaflet
  • mplleaflet / Leaflet wrappers: folium and mplleaflet
  • references / Leaflet wrappers: folium and mplleaflet
• libdynd
  • URL / GPU computing
• list comprehension / Loops
• loops / Loops

M

• magic commands
  • about / Using IPython as an extended shell, Learning magic commands
  • creating, in IPython extension / Creating a custom magic command in an IPython extension
• manipulation functions
  • reference link / A density map with NumPy
• maps
  • creating / Maps and geometry
  • matplotlib Basemap toolkit / The matplotlib Basemap toolkit
  • GeoPandas / GeoPandas
  • Leaflet / Leaflet wrappers: folium and mplleaflet
• Markdown cell, Notebook / Markdown cells
  • about / Structure of a notebook cell, Markdown cells
  • references / Writing interactive documents in the Notebook with Markdown
• mathematical functions, NumPy
  • URL / Mathematical operations on arrays
• mathematical operations
  • on arrays / Mathematical operations on arrays
• Math Kernel Library (MKL)
  • about / Why operations on ndarrays are fast
• matplotlib
  • about / matplotlib and seaborn essentials
  • plots with / Common plots with matplotlib
  • figures, customizing / Customizing matplotlib figures
  • gallery, URL / Customizing matplotlib figures
  • figures, in Notebook / Interacting with matplotlib figures in the Notebook
  • references / Interacting with matplotlib figures in the Notebook
  • high-level plotting, with seaborn / High-level plotting with seaborn
• Mayavi / Mayavi
• Message Passing Interace (MPI)
  • about / MPI
  • URL / MPI
  • with IPython, URL / MPI
• Microsoft Visual C++ Compiler for Python 2.7
  • URL / Installing Cython and a C compiler for Python
• MinGW
  • URL / Creating a custom magic command in an IPython extension
• Miniconda
  • URL / Installing Python with Anaconda
• modal interface, Notebook
  • about / The Notebook modal interface
  • keyboard shortcuts, in both modes / Keyboard shortcuts available in both modes
  • keyboard shortcuts, in edit mode / Keyboard shortcuts available in the edit mode
  • keyboard shortcuts, in command mode / Keyboard shortcuts available in the command mode
• multidimensional array
  • about / Multidimensional arrays

N

• ndarray
  • about / Multidimensional arrays, The ndarray
  • dimensions / The ndarray
  • shape / The ndarray
  • strides / The ndarray
  • data type (dtype) / The ndarray
  • vector operations / Vector operations on ndarrays
  • storing, in memory / How an ndarray is stored in memory
• nopython mode / Random walk
  • URL / Random walk
• Notebook
  • about / Jupyter and IPython, Introducing the Notebook, The Notebook dashboard
  • references / References, References
  • IPython console, launching / Launching the IPython console
  • Jupyter Notebook launching / Launching the Jupyter Notebook
  • dashboard / The Notebook dashboard
  • user interface / The Notebook user interface
  • cell, structure / Structure of a notebook cell
  • modal interface / The Notebook modal interface
  • dataset, exploring / Exploring a dataset in the Notebook
  • HTML elements, displaying / Displaying rich HTML elements in the Notebook
  • Scalable Vector Graphics (SVG), displaying / Displaying SVG in the Notebook
  • JavaScript / JavaScript and D3 in the Notebook
  • D3 / JavaScript and D3 in the Notebook
• Notebook interface
  • customizing, JavaScript used / Customizing the Notebook interface with JavaScript
• Numba
  • Python code, accelerating with / Accelerating Python code with Numba
  • URL / Random walk
  • documentation, URL / Random walk
• numexpr
  • URL / Universal functions
• NumPy
  • arrays / Creating and loading arrays
  • references / Loading arrays from files
  • density map, computing / A density map with NumPy
  • versus pandas / A density map with NumPy
• NumPy universal functions (ufuncs)
  • URL / Universal functions

O

• Object-oriented programming (OOP) / Object-oriented programming
• operations
  • complex operations / Complex operations
  • group-by operation / Group-by
  • joins / Joins

P

• pandas
  • versus NumPy / A density map with NumPy
• Partial Differential Equation (PDE)
  • about / Multidimensional arrays
• passage by assignment / Passage by assignment
• Plotly
  • about / Plotly
• plots
  • about / Choosing a plotting backend
  • inline plots / Inline plots
  • exported figures / Exported figures
  • plt.savefig(), URL / Exported figures
  • GUI toolkits / GUI toolkits
  • dynamic inline plots / Dynamic inline plots
  • web-based visualization / Web-based visualization
  • D3.js, URL / Web-based visualization
  • mpld3, URL / Web-based visualization
  • customization options, URL / Common plots with matplotlib
• positional arguments / Positional and keyword arguments
• Powershell
  • URL / Opening a terminal
• pure function / Passage by assignment
• PyCuda
  • URL / GPU computing
• pylab mode
  • URL / matplotlib and seaborn essentials
• PyOpenCL
  • URL / GPU computing
• PyPy
  • URL / PyPy
  • about / PyPy
• Python
  • about / What are Python, IPython, and Jupyter?
  • competitors / What are Python, IPython, and Jupyter?
  • installing, with Anaconda / Installing Python with Anaconda
  • special characters, URL / String escaping
  • C compiler, installing / Installing Cython and a C compiler for Python
  • Cython, installing / Installing Cython and a C compiler for Python
  • Eratosthenes Sieve, implementing / Implementing the Eratosthenes Sieve in Python and Cython
• Python, code
  • debugging / Debugging Python code
  • benchmarking / Benchmarking Python code
  • profiling / Profiling Python code
• Python, fundamentals
  • about / A crash course on Python
  • Hello world / Hello world
  • variables / Variables
  • string escaping / String escaping
  • lists / Lists
  • loops / Loops
  • indentation / Indentation
  • conditional branches / Conditional branches
  • functions / Functions
  • keyword arguments / Positional and keyword arguments
  • positional arguments / Positional and keyword arguments
  • passage by assignment / Passage by assignment
  • errors / Errors
  • Object-oriented programming (OOP) / Object-oriented programming
  • functional programming / Functional programming
  • Python 2 and 3 / Python 2 and 3
  • references / Going beyond the basics
• Python 2 and 3 / Python 2 and 3
• Python code
  • accelerating, with Numba / Accelerating Python code with Numba, Random walk
  • random walk / Random walk
• Python Package Index (PyPI)
  • about / Common conda commands
  • references / Common conda commands

Q

• Qt console
  • URL / Launching the IPython console

R

• record arrays
  • about / The ndarray
• relational database management systems (RDBMS)
  • about / Complex operations
• row-major order (C-order)
  • about / How an ndarray is stored in memory

S

• Scalable Vector Graphics (SVG)
  • about / Displaying SVG in the Notebook
  • displaying, in Notebook / Displaying SVG in the Notebook
• scikit-image
  • about / Image processing
  • references / Image processing
• seaborn
  • about / matplotlib and seaborn essentials
  • high-level plotting with / High-level plotting with seaborn
• sequential locality
  • about / Why operations on ndarrays are fast
• statistical functions, NumPy
  • URL / Mathematical operations on arrays
• strides
  • about / How an ndarray is stored in memory
• structured arrays
  • about / The ndarray
  • reference link / The ndarray
• Structured Query Language (SQL)
  • about / Complex operations
• SWIG / C/C++ with Python

U

• universal functions
  • about / Universal functions
  • references / Universal functions

V

• variables / Variables
• vector (or vectorized) operations
  • on ndarrays / Vector operations on ndarrays
  • comparing / Why operations on ndarrays are fast
• vector computing
  • about / A primer to vector computing
  • multidimensional array / Multidimensional arrays
  • ndarray / The ndarray
  • vector operations, on ndarray / Vector operations on ndarrays
  • in NumPy / How fast are vector computations in NumPy?
• vectorization / Computing with numbers
• Vega
  • about / Vincent and Vega
  • references / Vincent and Vega
• Vincent
  • about / Vincent and Vega
  • references / Vincent and Vega
• VisPy
  • about / VisPy
  • references / VisPy

W

• Wakari
  • URL / Installing Python with Anaconda
• weave / C/C++ with Python
• web technologies
  • references / JavaScript and D3 in the Notebook