Data Processing Using Python
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Data Processing Using Python
Nanjing University
Acerca de este Curso
4.3
89 ratings
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.
Habilidades que obtendrás
Python ProgrammingNumpyPandasWxpython
Programa - Qué aprenderás en este curso
1
Sección
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 (Total: 4 min), 2 readings
1 video
2 lecturas
Teaching Methods10m
FAQ10m
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 (Total: 145 min), 3 readings, 3 quizzes
15 videos
2 The First Python Program15m
3 Basics of Python Syntax11m
4 Data Types of Python9m
5 Basic Operations of Python10m
6 Functions, Modules and Packages of Python7m
1 Conditions10m
2 range5m
3 Loops6m
4 break, continue and else in Loops11m
5 Self-defined Functions14m
6 Recursion7m
7 Scope of Variable4m
A1: Standard Library Functions14m
A2: Exceptions10m
3 lecturas
1.1 References10m
1.1 Programming exercises(Not Graded)10m
1.2 Control structure & function exercises(9 questions)10m
2 ejercicios de práctica
Walk into Python quiz20m
More About Python quiz24m
2
Sección
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 (Total: 79 min), 5 readings, 1 quiz
6 videos
2 Network Data Retrieval21m
1 Sequence8m
2 String17m
3 List9m
4 Tuple7m
5 lecturas
2.1 References(re)10m
2.1 Internet Data Retrival Programming exercise(Not Graded)10m
2.1 code snippets for reference only10m
Sequence fuctions practice10m
Sequences and Files Programming Exercise(No Graded)10m
1 ejercicio de práctica
Data Acquisition and Presentation quiz30m
3
Sección
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 (Total: 70 min), 5 readings, 1 quiz
7 videos
2 Dictionary Use12m
3 Set11m
1 Extension Library SciPy6m
2 ndarray12m
3 Series7m
4 DataFrame7m
5 lecturas
3.1 Programming exercise(Not Graded)10m
3.2 References10m
3.2 Programming exercise for DataFrame(Not Graded)10m
3.2 Modify the DataFrames10m
Word Frequency Counter10m
1 ejercicio de práctica
Powerful Data Structures and Python Extension Libraries quiz28m
4
Sección
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 (Total: 110 min), 11 readings, 3 quizzes
14 videos
2 Data Preparations6m
3 Data Display4m
4 Data Selection8m
5 Simple Statistics and Processing8m
6 Grouping4m
7 Merge8m
1 Cluster12m
2 Basics of Matplotlib Plotting7m
3 Control of Matplotlib Image Attributes9m
4 Plotting with pandas6m
5 Data Access4m
6 Applications of Python into Science and Engineering Fields7m
7 Applications into Humanities and Social Sciences Fields7m
11 lecturas
4.1 References10m
4.1.1 code snippets for reference only10m
4.1.2 code snippets for reference only10m
Chinese Web API - TuShare10m
4.2 Programming exercise for comparing the stock data(No Graded)10m
4.2 code snippets for reference only10m
4.2.1 Extension: Scikit-learn Machine Learning Basics10m
4.2.4&4.2.5: Analyze test results using Box-plot10m
4.2.6 Extension: Introduction to WAV audio processing10m
4.2.7 Learn More about NLTK10m
4.2.1K-means algorithm10m
2 ejercicios de práctica
Basic Data Statistics of Python quiz16m
Advanced Data Processing and Visualization of Python quiz20m
4.3
Principales revisiones
por 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.
por SM•Jun 6th 2018
Very nice course. Could be extended to 12 weeks with more detailed coverage of packages. Please upload English audio tracks.
Instructor
ZHANG Li
associate professorDepartment of Computer Science
Acerca de 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.
Preguntas Frecuentes
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?
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