This course is divided into 5 modules (8 weeks of actual hours):
Module 01:python Basics
This module mainly discusses Python's basic language structure, data types, basic operations, conditions and loops, functions and modules and so on, so that they can write some useful programs!
MODULE 02: Data Acquisition and representation
This module focuses on Python's approach to local data and network data acquisition, using Python's basic but powerful data structure sequences, strings, lists, tuples to quickly and efficiently represent and do simple data processing.
MODULE 03: Powerful data structures and Python extension libraries
This module focuses on Python's advanced data structure dictionaries and collections, as well as the concise and efficient scipy in Ndarray, series, and Dataframe in Python's most widely used scientific computing package.
MODULE 04:python Data statistics and visualization
This module allows learners to quickly and efficiently dig out desired or expected or unknown results from a stack of data, and can be represented by a variety of images. Data statistics for some third-party packages in Python are also discussed.
MODULE 05: Object-oriented and graphical user interface
This module mainly discusses the object-oriented, graphical user interface and object-oriented relationship, this part of the content only requires the understanding of concepts, in the future can be used in a variety of new functions more easily and easier to ground hands, do not require writing programs. In addition, the basic framework of graphical user interface, common building and layout management is also the focus of discussion issues, focusing on the GUI perceptual understanding.
1
Grammar Basics
Data type
Basic operations
function modules and Packages
Conditions
Range and Xrange
Recursive
Variable scope
2
Local Data acquisition
Network data acquisition
Cycle
Break continue and else in the loop
Custom functions
Data representation-Sequence
Data representation--string
Data Representation--list
Meta-group
3
Powerful data Structures-dictionaries
Use of dictionaries
Collection
SciPy
Ndarray
Series
Dataframe
4
Convenient data acquisition
Preparation of data
Data display
Data selection
Simple statistics and processing
Grouping
Merge
Cluster analysis
Matplot Drawing Basics
Matplotlib Image Property Control
Pandas drawing
Data access
The application of Python in science and technology
Python's humanities and social sciences applications
5
GUI Object-oriented
Abstract (Class)
Inherited
Basic framework of GUI
Common GUI Components
Layout management
Other GUI libraries
Comprehensive application
: Baidu Network Disk
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