Acerca de este curso: 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 has been updated. Updates in the new version are : 1) the whole course has moved from Python 2.x to Python 3.x 2) Added manual webpage fetching and parsing. Web API is also added. 3) Improve the content order and enrich details of some content especially for some practice projects.

Creada por: Universidad de Nankín

Enseñado por: ZHANG Li, associate professor
Department of Computer Science

Nivel	Beginner
Compromiso	3-5 hours/week
Idioma	English
Cómo aprobar	Aprueba todas las tareas calificadas para completar el curso.
Calificaciones del usuario	4.3 estrellas Calificación promedio del usuario 4.3Ve los que los estudiantes dijeron

Programa

SEMANA 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 based on SciPy, Requests, Beautiful Soup libraries etc. 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

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!

15 videos, 3 readings

Vídeo: 2 The First Python Program
Vídeo: 3 Basics of Python Syntax
Vídeo: 4 Data Types of Python
Vídeo: 5 Basic Operations of Python
Vídeo: 6 Functions, Modules and Packages of Python
Reading: 1.1 References
Reading: 1.1 Programming exercises(Not Graded)
Vídeo: 1 Conditions
Vídeo: 2 range
Vídeo: 3 Loops
Vídeo: 4 break, continue and else in Loops
Vídeo: 5 Self-defined Functions
Vídeo: 6 Recursion
Vídeo: 7 Scope of Variable
Reading: 1.2 Coding and programs reading(Not Graded)
Vídeo: A1: Standard Library Functions
Vídeo: A2: Exceptions
Discussion Prompt: the characteristic of recursive algorithm

Calificado: Walk into Python quiz

Calificado: More About Python quiz

Calificado: find out the 6-th Monisen number(3 points)

SEMANA 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

Vídeo: 2 Network Data Retrieval
Reading: 2.1 References(re)
Reading: 2.1 Internet Data Retrival Programming exercise(Not Graded)
Reading: 2.1 code snippets for reference only
Vídeo: 1 Sequence
Vídeo: 2 String
Vídeo: 3 List
Vídeo: 4 Tuple
Reading: Sequence fuctions practice
Discussion Prompt: KO Math Whiz
Reading: Sequences and Files Programming Exercise(No Graded)

Calificado: Data Acquisition and Presentation quiz

SEMANA 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, 5 readings

Vídeo: 2 Dictionary Use
Vídeo: 3 Set
Reading: 3.1 Programming exercise(Not Graded)
Vídeo: 1 Extension Library SciPy
Vídeo: 2 ndarray
Vídeo: 3 Series
Vídeo: 4 DataFrame
Reading: 3.2 References
Discussion Prompt: ufunc functions
Reading: 3.2 Programming exercise for DataFrame(Not Graded)
Reading: 3.2 Modify the DataFrames
Reading: Word Frequency Counter

Calificado: Powerful Data Structures and Python Extension Libraries quiz

SEMANA 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, 11 readings

Vídeo: 2 Data Preparations
Vídeo: 3 Data Display
Vídeo: 4 Data Selection
Vídeo: 5 Simple Statistics and Processing
Vídeo: 6 Grouping
Vídeo: 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
Vídeo: 1 Cluster
Vídeo: 2 Basics of Matplotlib Plotting
Vídeo: 3 Control of Matplotlib Image Attributes
Vídeo: 4 Plotting with pandas
Vídeo: 5 Data Access
Vídeo: 6 Applications of Python into Science and Engineering Fields
Vídeo: 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
Reading: 4.2.7 Learn More about NLTK
Reading: 4.2.1K-means algorithm

Calificado: Basic Data Statistics of Python quiz

Calificado: Advanced Data Processing and Visualization of Python quiz

Calificado: Movies review programming exerciese(4 points)

SEMANA 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

Vídeo: 2 Abstraction
Vídeo: 3 Inheritance
Vídeo: 1 Basic Framework of GUI
Vídeo: 2 Common Components of GUI
Vídeo: 3 Layout Management
Vídeo: 4 Other GUI Libraries
Vídeo: 5 Comprehensive Applications
Reading: 5.2 Comprehensive practice project
Reading: 5 code snippets for reference only

Calificado: Object Orientation and Graphical User Interface quiz

Calificado: Examination

Preguntas Frecuentes

When will I have access to the lectures and assignments?

What if I need additional time to complete the course?

What will I get if I pay for this course?

Can I take this course for free?

¿Cuál es la política de reembolsos?

¿Hay ayuda económica disponible?

Cómo funciona

Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creadores

Universidad de Nankín

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.

Calificaciones y revisiones

Calificado 4.3 de 5 76 calificaciones

Nice course.

讲的很好，入门课程，重要的是老师很可爱，哈哈哈哈。

The course is very interesting and good, but very short and not detailed, especially 4-th week. There are a lot of real big data as a advantage of this course and bonus is learning GUI.