About this course: This course (The English copy of "用Python玩转数据" <https://www.coursera.org/learn/hipython/home/welcome>) is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level. This course, as a whole, based on Finance data and through establishment of popular cases one after another, enables learners to more vividly feel the simplicity, elegance and robustness of Python. Also, it discusses the fast, convenient and efficient data processing capacity of Python in humanities and social sciences fields like literature, sociology and journalism and science and engineering fields like mathematics and biology, in addition to business fields. Similarly, it may also be flexibly applied into other fields. The course is being updated and expected to be available before August 23th. Updates in the new version : 1) the whole course has moved from Python 2.x to Python 3.x 2) Added manual webpage fetching and parsing. WebAPI is also added. 3) Improve the content order and enrich details of some content especially for some practice projects.
Created by: Nanjing University
Taught by: ZHANG Li, associate professor
Department of Computer Science
| Level | Beginner |
| Commitment | 3-5 hours/week |
| Language | English, Subtitles: Chinese (Simplified) |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Welcome to learn Data Processing Using Python!
Hi, guys, welcome to learn “Data Processing Using Python”(The English version of "用Python玩转数据", url is https://www.coursera.org/learn/hipython/home/welcome)!In this course, I tell in a manner that enables non-computer majors to understand how to utilize this simple and easy programming language – Python to rapidly acquire, express, analyze and present data. Many cases are provided to enable you to easily and happily learn how to use Python to process data in many fields.
1 video, 2 readings
- Video: Promotion Video
- Reading: Teaching Methods
- Reading: FAQ
Basics of Python
Hi, guys, welcome to learn Module 01 “Basics of Python”! I’ll first guide you to have a glimpse of its simplicity for learning as well as elegance and robustness. Less is more: the author of Python must know this idea well. After learning this module, you can master the basic language structures, data types, basic operations, conditions, loops, functions and modules in Python. With them, we can write some useful programs!
13 videos, 3 readings
- Video: 1 Introduction to Python
- Video: 2 The First Python Program
- Video: 3 Basics of Python Syntax
- Video: 4 Data Types of Python
- Video: 5 Basic Operations of Python
- Video: 6 Functions, Modules and Packages of Python
- Reading: 1.1 References
- Reading: 1.1 Programming exercises(Not Graded)
- Video: 1 Conditions
- Video: 2 range and xrange
- Video: 3 Loops
- Video: 4 break, continue and else in Loops
- Video: 5 Self-defined Functions
- Video: 6 Recursion
- Video: 7 Scope of Variable
- Reading: 1.2 Coding and programs reading(Not Graded)
- Discussion Prompt: the characteristic of recursive algorithm
Graded: Walk into Python quiz
Graded: More About Python quiz
WEEK 2
Data Acquisition and Presentation
Welcome to learn Module 02 “Data Acquisition and Presentation”! After learning this module, you can master the modes of acquiring local data and network data in Python and use the basic and yet very powerful data structure sequence, string, list and tuple in Python to fast and effectively present data and simply process data.
6 videos, 5 readings
- Video: 1 Local Data Acquisition
- Video: 2 Network Data Acquisition
- Reading: 2.1 References(re)
- Reading: 2.1 Internet Data Retrival Programming exercise(Not Graded)
- Reading: 2.1 code snippets for reference only
- Video: 1 Sequence
- Video: 2 String
- Video: 3 List
- Video: 4 Tuple
- Reading: Sequence fuctions practice
- Discussion Prompt: KO Math Whiz
- Reading: Sequences and Files Programming Exercise(No Graded)
Graded: Data Acquisition and Presentation quiz
WEEK 3
Powerful Data Structures and Python Extension Libraries
Welcome to learn Module 03 “Powerful Data Structures and Python Extension Libraries”! Have you felt you are closer to using Python to process data? After learning this module, you can master the intermediate-level and advanced uses of Python: data structure dictionaries and sets. In some applications, they can be very convenient. What’s special here is that, you can also feel the charm of such concise and efficient data structures: ndarray, Series and DataFrame in the most famous and widely applied scientific computing package SciPy in Python.
7 videos, 3 readings
- Video: 1 Why Are Dictionaries Needed
- Video: 2 Dictionary Use
- Video: 3 Set
- Reading: 3.1 Programming exercise(Not Graded)
- Video: 1 Extension Library SciPy
- Video: 2 ndarray
- Video: 3 Series(Variable-length Dictionary Series)
- Video: 4 DataFrame
- Reading: 3.2 References
- Discussion Prompt: ufunc functions
- Reading: 3.2 Programming exercise for DataFrame(Not Graded)
Graded: Powerful Data Structures and Python Extension Libraries quiz
WEEK 4
Python Data Statistics and Visualization
Welcome to learn Module 04 “Python Data Statistics and Visualization”! In this module, I will show you, over the entire process of data processing, the unique advantages of Python in data processing and analysis, and use many cases familiar to and loved by us to learn about and master methods and characteristics. After learning this module, you can fast and effectively mine your desired or expected or unknown results from a large amount of data, and can also present those data in various images. In addition, the data statistics modes of all third party packages in Python are extraordinarily and surprisingly strong, but we, as average persons, can still understand and possess them.
14 videos, 9 readings
- Video: 1 Convenient and Fast Data Acquisition
- Video: 2 Data Preparations
- Video: 3 Data Display
- Video: 4 Data Selection
- Video: 5 Simple Statistics and Processing
- Video: 6 Grouping
- Video: 7 Merge
- Reading: 4.1 References
- Reading: 4.1.1 code snippets for reference only
- Reading: 4.1.2 code snippets for reference only
- Reading: Chinese Web API - TuShare
- Video: 1 Cluster
- Video: 2 Basics of Matplotlib Plotting
- Video: 3 Control of Matplotlib Image Attributes
- Video: 4 Plotting with pandas
- Video: 5 Data Access
- Video: 6 Applications of Python into Science and Engineering Fields
- Video: 7 Applications into Humanities and Social Sciences Fields
- Reading: 4.2 Programming exercise for comparing the stock data(No Graded)
- Reading: 4.2 code snippets for reference only
- Reading: 4.2.1 Extension: Scikit-learn Machine Learning Basics
- Reading: 4.2.4&4.2.5: Analyze test results using Box-plot
- Reading: 4.2.6 Extension: Introduction to WAV audio processing
- Ungraded Programming: Movies review programming exerciese(4 points)
Graded: Basic Data Statistics of Python quiz
Graded: Advanced Data Processing and Visualization of Python quiz
WEEK 5
Object Orientation and Graphical User Interface
Welcome to Module 05 “Object Orientation and Graphical User Interface”! In this module, I will guide you to understand what object orientation is and the relationship between graphical user interface and object orientation. Learners are only required to understand the concepts so that you can more freely and easily pick up various new functions in future. No program writing is required here. Besides, you also need to master the basic framework of GUI, common components and layout management. After learning them, you will find development with GUI is actually not remote. It has an Easter egg, too ~~~
8 videos, 2 readings
- Video: 1 GUI and Object Orientation
- Video: 2 Abstraction
- Video: 3 Inheritance
- Video: 1 Basic Framework of GUI
- Video: 2 Common Components of GUI
- Video: 3 Layout Management
- Video: 4 Other GUI Libraries
- Video: 5 Comprehensive Applications
- Reading: 5.2 Comprehensive practice project
- Reading: 5 code snippets for reference only
Graded: Object Orientation and Graphical User Interface quiz
Graded: Examination
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Nanjing University
Nanjing University (NJU) is committed to excellence in teaching and research. Located on the prosperous eastern coast of China, NJU provides a dynamic environment that nurtures learning, creativity, and discovery on one of the most beautiful campuses in the country. Taking NJU's university offerings on Coursera will be a rewarding experience for learners from every corner of the world.
Ratings and Reviews
谢谢老师，我是一名就读在华南理工大学的非计算机专业学生，谢谢老师的这个课程让我学习到了如何使用python进行数据分析
Very good. Keep it up
Good Course
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RW
In sum I liked the course, because the material was presented in detail. The professor mentioned many little things, which are often overlooked or simply not mentioned in similar courses. Furthermore, I liked the stocks examples. Unfortunately, a large part of the presented stock code is broken, because of a recent breaking change of Yahoo Finance's API. Some questions in the quizzes are, in my opinion, not easy to understand, I guess because of an errorneous translation from the Chinese language.