Chinese Python Notes
Version: 0.0.1
Author: Li Jin Email: [email protected]
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Introduction
Most of the content comes from the Internet.
Python 2.7 is installed by default, as well as related third-party packages ipython , numpy , scipy , and pandas .
life is short. use python.
It is recommended to use Anaconda, this IDE integrates most commonly used packages.
Note content is displayed using jupyter notebook .
After installing Python and the corresponding packages, you can enter:
to enter jupyter notebook .
Basic environment configuration
conda update conda
conda update anaconda
refer to
- Enthought Training on Demand
- Computational Statistics in Python
- scipy.org
- Deep Learning Tutorials
- High Performance Scientific Computing
- Scipy Lectures
- pandas.org
Table of contents
You can open generate static files.ipynb in Notebook, or run the code generate_static_files.py in the command line to generate static HTML files.
- 01. Python tools
- 01.01 Introduction to Python
- 01.02 Ipython interpreter
- 01.03 Ipython notebook
- 01.04 Using Anaconda
- 02. Python basics
- 02.01 Python Getting Started Demo
- 02.02 Python data types
- 02.03 Number
- 02.04 String
- 02.05 Indexing and Sharding
- 02.06 List
- 02.07 Mutable and Immutable Types
- 02.08 Tuple
- 02.09 Speed comparison of lists and tuples
- 02.10 Dictionary
- 02.11 Collection
- 02.12 Immutable collections
- 02.13 Python assignment mechanism
- 02.14 Judgment statement
- 02.15 Loop
- 02.16 List comprehensions
- 02.17 Function
- 02.18 Modules and Packages
- 02.19 Exception
- 02.20 Warning
- 02.21 File reading and writing
- 03. Numpy
- 03.01 Introduction to Numpy
- 03.02 Matplotlib Basics
- 03.03 Numpy arrays and their indexes
- 03.04 Array type
- 03.05 Array methods
- 03.06 Array sorting
- 03.07 Array Shape
- 03.08 Diagonal
- 03.09 Conversion between array and string
- 03.10 Summary of array attribute methods
- 03.11 Functions that generate arrays
- 03.12 Matrix
- 03.13 General functions
- 03.14 Vectorized functions
- 03.15 Binary operations
- 03.16 ufunc object
- 03.17 choose function implements conditional filtering
- 03.18 Array broadcast mechanism
- 03.19 Array reading and writing
- 03.20 Structured Array
- 03.21 Record array
- 03.22 Memory mapping
- 03.23 From Matlab to Numpy
- 04. Scipy
- 04.01 Introduction to SCIentific PYthon
- 04.02 Interpolation
- 04.03 Probabilistic and statistical methods
- 04.04 Curve Fitting
- 04.05 Minimization function
- 04.06 Points
- 04.07 Solve differential equations
- 04.08 Sparse Matrix
- 04.09 Linear Algebra
- 04.10 Linear algebra of sparse matrices
- 05. Python Advanced
- 05.01 Introduction to sys module
- 05.02 Interacting with the operating system: the os module
- 05.03 CSV files and csv module
- 05.04 Regular expressions and re module
- 05.05 datetime module
- 05.06 SQL Database
- 05.07 Object-relational mapping
- 05.08 Function advancement: parameter passing, higher-order functions, lambda anonymous functions, global variables, recursion
- 05.09 Iterator
- 05.10 Generator
- 05.11 with statement and context manager
- 05.12 Modifiers
- 05.13 Use of modifiers
- 05.14 operator, functools, itertools, toolz, fn, funcy modules
- 05.15 Scope
- 05.16 Dynamic compilation
- 06. Matplotlib
- 06.01 Pyplot Tutorial
- 06.02 Use style to configure pyplot style
- 06.03 Processing text (basics)
- 06.04 Processing text (mathematical expressions)
- 06.05 Image Basics
- 06.06 Notes
- 06.07 Tags
- 06.08 figures, subplots, axes and ticks objects
- 06.09 Don’t be superstitious about default settings
- 06.10 Various drawing examples
- 07. Expand with other languages
- 07.01 Introduction
- 07.02 Python extension modules
- 07.03 Cython: Cython basics, convert source code into extension modules
- 07.04 Cython: Cython syntax, calling other C libraries
- 07.05 Cython: class and cdef class, using C++
- 07.06 Cython: Typed memoryviews
- 07.07 Generate compilation comments
- 07.08 ctypes
- 08. Object-oriented programming
- 08.01 Introduction
- 08.02 Modeling forest fires using OOP
- 08.03 What is an object?
- 08.04 Define class
- 08.05 Special methods
- 08.06 Properties
- 08.07 Forest Fire Simulation
- 08.08 Inheritance
- 08.09 super() function
- 08.10 Redefining Forest Fire Simulation
- 08.11 Interface
- 08.12 Public, private and special methods and properties
- 08.13 Multiple inheritance
- 09. Theano Basics
- 09.01 Introduction to Theano and its installation
- 09.02 Theano Basics
- 09.03 Theano configuration on Windows
- 09.04 Theano symbolic graph structure
- 09.05 Theano configuration and compilation mode
- 09.06 Theano conditional statements
- 09.07 Theano loop: scan (detailed explanation)
- 09.08 Theano Example: Linear Regression
- 09.09 Theano Example: Logistic Regression
- 09.10 Theano Example: Softmax Regression
- 09.11 Theano Example: Artificial Neural Network
- 09.12 Theano random number flow variable
- 09.13 Theano Example: More Complex Networks
- 09.14 Theano Example: Convolutional Neural Network
- 09.15 Theano tensor module: basics
- 09.16 Theano tensor module: index
- 09.17 Theano tensor module: operators and element-wise operations
- 09.18 Theano tensor module: nnet submodule
- 09.19 Theano tensor module: conv submodule
- 10. Interesting third-party modules
- 10.01 Use basemap to draw maps
- 10.02 Use cartopy to draw maps
- 10.03 Explore NBA Data
- 10.04 Jin Yong’s martial arts world
- 11. Useful Tools
- 11.01 pprint module: Print Python objects
- 11.02 pickle, cPickle module: Serializing Python objects
- 11.03 json module: processing JSON data
- 11.04 glob module: file pattern matching
- 11.05 shutil module: advanced file operations
- 11.06 gzip, zipfile, tarfile modules: processing compressed files
- 11.07 logging module: logging
- 11.08 string module: string processing
- 11.09 collections module: more data structures
- 11.10 requests module: HTTP for Human
- 12.Pandas
- 12.01 Get started with Pandas in ten minutes
- 12.02 One-dimensional data structure: Series
- 12.03 Two-dimensional data structure: DataFrame
