課程信息

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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 the 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.

Note: videos are in Chinese (Simplified) with English subtitles. All other materials are in English.

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初級

完成時間大約為29 小時

英語（English）

字幕：英語（English）

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Python ProgrammingNumpyPandasWxpython

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

初級

完成時間大約為29 小時

英語（English）

字幕：英語（English）

教學大綱 - 您將從這門課程中學到什麼

內容評分93%（1,382 個評分）

週

1

週 1

完成時間為 24 分鐘

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.

完成時間為 24 分鐘

1 個視頻（總計 4 分鐘）, 2 個閱讀材料

1 個視頻

Promotion Video3分鐘

2 個閱讀材料

Teaching Methods10分鐘

FAQ10分鐘

完成時間為 7 小時

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!

完成時間為 7 小時

16 個視頻（總計 170 分鐘）, 5 個閱讀材料, 3 個測驗

16 個視頻

1 Introduction to Python5分鐘

2 The First Python Program16分鐘

3 Basics of Python Syntax15分鐘

4 Data Types of Python9分鐘

5 Basic Operations of Python10分鐘

6 Functions, Modules and Packages of Python8分鐘

1.1 Extension: Build a Python Environment4分鐘

1 Conditions12分鐘

2 range5分鐘

3 Loops15分鐘

4 break, continue and else in Loops11分鐘

5 Self-defined Functions14分鐘

6 Recursion11分鐘

7 Scope of Variable4分鐘

A1: Standard Library Functions14分鐘

A2: Exceptions10分鐘

5 個閱讀材料

1.1 Walk into Python slides10分鐘

1.1 References10分鐘

1.1 Programming exercises(Not Graded)10分鐘

1.2 Multi-dimensional View of Python slides10分鐘

1.2 Control structure & function exercises(9 questions)10分鐘

2 個練習

Walk into Python quiz20分鐘

More About Python quiz24分鐘

週

2

週 2

完成時間為 4 小時

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.

完成時間為 4 小時

10 個視頻（總計 139 分鐘）, 5 個閱讀材料, 1 個測驗

10 個視頻

1 Local Data Acquisition22分鐘

2 Network Data Retrieval20分鐘

2.1 Extension: RE introduction16分鐘

2.1 Extension: Dynamic web crawling example5分鐘

1 Sequence8分鐘

2 String17分鐘

3 List14分鐘

4 Tuple7分鐘

2.2 Extension: IO&functional programming15分鐘

2.2 Extension: Mutable objects modify issue9分鐘

5 個閱讀材料

2 Data Retrieval and Represent slides10分鐘

2.1 Internet Data Retrival Programming exercise(Not Graded)10分鐘

2.1 code snippets for reference only10分鐘

Sequence fuctions practice10分鐘

Sequences and Files Programming Exercise(8 questions)10分鐘

1 個練習

Data Acquisition and Presentation quiz30分鐘

週

3

週 3

完成時間為 3 小時

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.

完成時間為 3 小時

9 個視頻（總計 109 分鐘）, 6 個閱讀材料, 1 個測驗

9 個視頻

1 Why Are Dictionaries Needed13分鐘

2 Dictionary Use15分鐘

3 Set11分鐘

3.1 Extension: dict and set programming examples12分鐘

1 Extension Library SciPy6分鐘

2 ndarray18分鐘

3 Series7分鐘

4 DataFrame8分鐘

3.2 Extension: Common numpy applications16分鐘

6 個閱讀材料

Data Structure Selection10分鐘

3 Powerful Data Structure and Software Ecosystem slides10分鐘

3.1 Programming exercise(Not Graded)10分鐘

3.1 Classic dict programming(1 question)10分鐘

3.2 Programming exercise for DataFrame(Not Graded)10分鐘

3.2 Modify the DataFrames10分鐘

1 個練習

Powerful Data Structures and Python Extension Libraries quiz28分鐘

週

4

週 4

完成時間為 10 小時

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.

完成時間為 10 小時

13 個視頻（總計 240 分鐘）, 13 個閱讀材料, 3 個測驗

13 個視頻

1 Convenient and Fast Data Acquisition18分鐘

2 Fundamentals of Python Plotting23分鐘

3 Data Clean of Data Exploration and Preprocessing20分鐘

4 Data Transformation of Data Precessing22分鐘

5 Data Reduction of Data Preproccessing18分鐘

Copy of 1 Convenient and Fast Data Acquisition18分鐘

1 Basic Data Characteristics Analysis of Data Exploration24分鐘

2 Data Statistics and Analysis Based on pandas27分鐘

3 Cluster Analysis14分鐘

4 Aplications of Python into Science and Engineering Fields7分鐘

5 Applications into Humanities and Social Sciences Fields7分鐘

4.2 Extension: An Analysis of the Differences between Males and Females on Film Ratings17分鐘

4.2 Extension: Classification of Red Wine Data Based on Random Forest Model21分鐘

13 個閱讀材料

4.1 Data retrieval and preprocessing of Python Slides10分鐘

4.1 References10分鐘

4.1.1 code snippets for reference only10分鐘

4.1.3: Analyze test results using Box-plot10分鐘

Web API - TuShare and Data Analysis task30分鐘

4.1 Titanic Data Set Acquisition10分鐘

4.2 Data Statistics, Mining and Application Slides10分鐘

4.2 code snippets for reference only10分鐘

4.2.1 K-means algorithm an discussion on K value10分鐘

4.2.1 Extension: Scikit-learn Machine Learning Basics10分鐘

4.2.6 Project- —Linear Regression for Boston houses price prediction10分鐘

4.2.6 Extension: Introduction to WAV audio processing10分鐘

4.2.7 Learn More about NLTK10分鐘

2 個練習

Data retrieval and preprocessing of Python quiz16分鐘

Data Statistics, Mining and Application quiz20分鐘

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Data Processing Using Python