Data Processing Using Python
от партнера
Data Processing Using Python
Nanjing University
Об этом курсе
4.4
Оценки: 93
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.
Приобретаемые навыки
Python ProgrammingNumpyPandasWxpython
Программа курса: что вы изучите
Week
1Welcome 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 видео (всего 4 мин.), 2 материалов для самостоятельного изучения
1 видео
Promotion Video3мин
2 материала для самостоятельного изучения
Teaching Methods10мин
FAQ10мин
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 видео (всего 145 мин.), 3 материалов для самостоятельного изучения, 3 тестов
15 видео
2 The First Python Program15мин
3 Basics of Python Syntax11мин
4 Data Types of Python9мин
5 Basic Operations of Python10мин
6 Functions, Modules and Packages of Python7мин
1 Conditions10мин
2 range5мин
3 Loops6мин
4 break, continue and else in Loops11мин
5 Self-defined Functions14мин
6 Recursion7мин
7 Scope of Variable4мин
A1: Standard Library Functions14мин
A2: Exceptions10мин
3 материала для самостоятельного изучения
1.1 References10мин
1.1 Programming exercises(Not Graded)10мин
1.2 Control structure & function exercises(9 questions)10мин
2 практического упражнения
Walk into Python quiz20мин
More About Python quiz24мин
Week
2Data 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 видео (всего 79 мин.), 5 материалов для самостоятельного изучения, 1 тест
6 видео
2 Network Data Retrieval21мин
1 Sequence8мин
2 String17мин
3 List9мин
4 Tuple7мин
5 материала для самостоятельного изучения
2.1 References(re)10мин
2.1 Internet Data Retrival Programming exercise(Not Graded)10мин
2.1 code snippets for reference only10мин
Sequence fuctions practice10мин
Sequences and Files Programming Exercise(8 questions)10мин
1 практическое упражнение
Data Acquisition and Presentation quiz30мин
Week
3Powerful 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 видео (всего 70 мин.), 6 материалов для самостоятельного изучения, 1 тест
7 видео
2 Dictionary Use12мин
3 Set11мин
1 Extension Library SciPy6мин
2 ndarray12мин
3 Series7мин
4 DataFrame7мин
6 материала для самостоятельного изучения
3.1 Programming exercise(Not Graded)10мин
3.1 Classic dict programming(2 questions)10мин
3.2 References10мин
3.2 Programming exercise for DataFrame(Not Graded)10мин
3.2 Modify the DataFrames10мин
Word Frequency Counter10мин
1 практическое упражнение
Powerful Data Structures and Python Extension Libraries quiz28мин
Week
4Python 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 видео (всего 110 мин.), 12 материалов для самостоятельного изучения, 3 тестов
14 видео
2 Data Preparations6мин
3 Data Display4мин
4 Data Selection8мин
5 Simple Statistics and Processing8мин
6 Grouping4мин
7 Merge8мин
1 Cluster12мин
2 Basics of Matplotlib Plotting7мин
3 Control of Matplotlib Image Attributes9мин
4 Plotting with pandas6мин
5 Data Access4мин
6 Applications of Python into Science and Engineering Fields7мин
7 Applications into Humanities and Social Sciences Fields7мин
12 материала для самостоятельного изучения
4.1 References10мин
4.1.1 code snippets for reference only10мин
4.1.2 code snippets for reference only10мин
Web API - TuShare and Data Analysis ta30мин
4.2 Programming exercise for comparing the stock data(No Graded)10мин
4.2 code snippets for reference only10мин
4.2.1 Extension: Scikit-learn Machine Learning Basics10мин
4.2.4&4.2.5: Analyze test results using Box-plot10мин
4.2.6 Extension: Introduction to WAV audio processing10мин
4.2.7 Learn More about NLTK10мин
4.2.1K-means algorithm10мин
Copy of 4.2.1 Extension: Scikit-learn Machine Learning Basics10мин
2 практического упражнения
Basic Data Statistics of Python quiz16мин
Advanced Data Processing and Visualization of Python quiz20мин
4.4
Лучшие рецензии
автор: JL•Sep 12th 2017
It's a basic Python lesson, but providing some data analysis and GUI concepts, which needs you to explore after this class or in the future.
автор: SM•Jun 6th 2018
Very nice course. Could be extended to 12 weeks with more detailed coverage of packages. Please upload English audio tracks.
Преподаватель
ZHANG Li
associate professorDepartment of Computer Science
О 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.
Часто задаваемые вопросы
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
Остались вопросы? Посетите Центр поддержки учащихся.
Coursera делает лучшее в мире образование доступным каждому, предлагая онлайн-курсы от ведущих университетов и организаций.
© Coursera Inc., 2018 Все права защищены.
