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.
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Data Processing Using Python
Université de Nanjing
À propos de ce cours
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Compétences que vous acquerrez
Python ProgrammingNumpyPandasWxpython
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Niveau débutant
Approx. 27 heures pour terminer
Recommandé : 3-5 hours/week
Anglais
Sous-titres : Anglais
Offert par
Université de Nanjing
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.
Programme du cours : ce que vous apprendrez dans ce cours
24 minutes pour terminer
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. 【Nov 18, 2019 @ @ @ @ @ @ @ Hi, all! The content is planned to be updated in the last two months. This update is relatively large, including practical operation and explanation of Python based cases, vector operation and broadcast ideas of numpy package and common applications, multiple links of data exploration and preprocessing (including in module 4), data analysis and data mining cases based on pandas, some of which are directly modified on the original video Some of them are presented in the form of expanded videos, especially the newly recorded videos, which have a lot of content to say, take a long time, and will be a little hard to learn. I have completed all the updates on Dec 16, 2019. Thank you for your patience. I hope you will enjoy the new version.】
24 minutes pour terminer
1 vidéo (Total 4 min), 2 lectures
1 vidéo
Promotion Video3 min
2 lectures
Teaching Methods10 min
FAQ10 min
7 heures pour terminer
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!
7 heures pour terminer
16 vidéos (Total 170 min), 5 lectures, 3 quiz
16 vidéos
2 The First Python Program16 min
3 Basics of Python Syntax15 min
4 Data Types of Python9 min
5 Basic Operations of Python10 min
6 Functions, Modules and Packages of Python8 min
1.1 Extension: Build a Python Environment4 min
1 Conditions12 min
2 range5 min
3 Loops15 min
4 break, continue and else in Loops11 min
5 Self-defined Functions14 min
6 Recursion11 min
7 Scope of Variable4 min
A1: Standard Library Functions14 min
A2: Exceptions10 min
5 lectures
1.1 Walk into Python slides10 min
1.1 References10 min
1.1 Programming exercises(Not Graded)10 min
1.2 Multi-dimensional View of Python slides10 min
1.2 Control structure & function exercises(9 questions)10 min
2 exercices pour s'entraîner
Walk into Python quiz20 min
More About Python quiz24 min
4 heures pour terminer
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.
4 heures pour terminer
10 vidéos (Total 139 min), 5 lectures, 1 quiz
10 vidéos
1 Local Data Acquisition22 min
2 Network Data Retrieval20 min
2.1 Extension: RE introduction16 min
2.1 Extension: Dynamic web crawling example5 min
1 Sequence8 min
2 String17 min
3 List14 min
4 Tuple7 min
2.2 Extension: IO&functional programming15 min
2.2 Extension: Mutable objects modify issue9 min
5 lectures
2 Data Retrieval and Represent slides10 min
2.1 Internet Data Retrival Programming exercise(Not Graded)10 min
2.1 code snippets for reference only10 min
Sequence fuctions practice10 min
Sequences and Files Programming Exercise(8 questions)10 min
1 exercice pour s'entraîner
Data Acquisition and Presentation quiz30 min
3 heures pour terminer
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.
3 heures pour terminer
9 vidéos (Total 109 min), 5 lectures, 1 quiz
9 vidéos
2 Dictionary Use15 min
3 Set11 min
3.1 Extension: dict and set programming examples12 min
1 Extension Library SciPy6 min
2 ndarray18 min
3 Series7 min
4 DataFrame8 min
3.2 Extension: Common numpy applications16 min
5 lectures
3 Powerful Data Structure and Software Ecosystem slides10 min
3.1 Programming exercise(Not Graded)10 min
3.1 Classic dict programming(1 question)10 min
3.2 Programming exercise for DataFrame(Not Graded)10 min
3.2 Modify the DataFrames10 min
1 exercice pour s'entraîner
Powerful Data Structures and Python Extension Libraries quiz28 min
10 heures pour terminer
Python Data Statistics and Mining
Welcome to learn Module 04 “Python data statistics and mining”! 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 preprocess the data and 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.
10 heures pour terminer
12 vidéos (Total 222 min), 13 lectures, 3 quiz
12 vidéos
2 Fundamentals of Python Plotting23 min
3 Data Clean of Data Exploration and Preprocessing20 min
4 Data Transformation of Data Precessing22 min
5 Data Reduction of Data Preproccessing18 min
1 Basic Data Characteristics Analysis of Data Exploration24 min
2 Data Statistics and Analysis Based on pandas27 min
3 Cluster Analysis14 min
4 Aplications of Python into Science and Engineering Fields7 min
5 Applications into Humanities and Social Sciences Fields7 min
4.2 Extension: An Analysis of the Differences between Males and Females on Film Ratings17 min
4.2 Extension: Classification of Red Wine Data Based on Random Forest Model21 min
13 lectures
4.1 Data retrieval and preprocessing of Python Slides10 min
4.1 References10 min
4.1.1 code snippets for reference only10 min
4.1.3: Analyze test results using Box-plot10 min
Web API - TuShare and Data Analysis ta30 min
4.1 Titanic Data Set Acquisition10 min
4.2 Data Statistics, Mining and Application Slides10 min
4.2 code snippets for reference only10 min
4.2.1 K-means algorithm an discussion on K value10 min
4.2.1 Extension: Scikit-learn Machine Learning Basics10 min
4.2.6 Project- —Linear Regression for Boston houses price prediction10 min
4.2.6 Extension: Introduction to WAV audio processing10 min
4.2.7 Learn More about NLTK10 min
2 exercices pour s'entraîner
Data retrieval and preprocessing of Python quiz16 min
Data Statistics, Mining and Application quiz20 min
Avis
4.4
Meilleurs avis pour DATA PROCESSING USING PYTHON
par SROct 21, 2018
The course provides an insight into the basic structure of Python. It will help you in navigating the areas where Python is robust and effective.
par JLSep 11, 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.
par SMJun 5, 2018
Very nice course. Could be extended to 12 weeks with more detailed coverage of packages. Please upload English audio tracks.
par SWMay 3, 2017
Professor talks too fast. Maybe since it is not in English, I feel like that.
par GKAug 4, 2017
Very concise, yet interesting and effective course.
par YQNov 26, 2017
课程深入浅出，学到了很多东西！非常值得！然后由于做了笔记，也一边操作，所以以后会经常翻过来查看笔记。
Foire Aux Questions
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