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.
ofrecido por
Data Processing Using Python
Universidad de Nankín
Acerca de este Curso
24,765 vistas recientes
Habilidades que obtendrás
Python ProgrammingNumpyPandasWxpython
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 27 horas para completar
Sugerido: 3-5 hours/week
Inglés (English)
Subtítulos: Inglés (English)
Programa - Qué aprenderás en este curso
24 minutos para completar
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 minutos para completar
1 video (Total 4 minutos), 2 lecturas
1 video
2 lecturas
Teaching Methods10m
FAQ10m
7 horas para completar
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 horas para completar
16 videos (Total 170 minutos), 5 lecturas, 3 cuestionarios
16 videos
2 The First Python Program16m
3 Basics of Python Syntax15m
4 Data Types of Python9m
5 Basic Operations of Python10m
6 Functions, Modules and Packages of Python8m
1.1 Extension: Build a Python Environment4m
1 Conditions12m
2 range5m
3 Loops15m
4 break, continue and else in Loops11m
5 Self-defined Functions14m
6 Recursion11m
7 Scope of Variable4m
A1: Standard Library Functions14m
A2: Exceptions10m
5 lecturas
1.1 Walk into Python slides10m
1.1 References10m
1.1 Programming exercises(Not Graded)10m
1.2 Multi-dimensional View of Python slides10m
1.2 Control structure & function exercises(9 questions)10m
2 ejercicios de práctica
Walk into Python quiz20m
More About Python quiz24m
4 horas para completar
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 horas para completar
10 videos (Total 139 minutos), 5 lecturas, 1 cuestionario
10 videos
2 Network Data Retrieval20m
2.1 Extension: RE introduction16m
2.1 Extension: Dynamic web crawling example5m
1 Sequence8m
2 String17m
3 List14m
4 Tuple7m
2.2 Extension: IO&functional programming15m
2.2 Extension: Mutable objects modify issue9m
5 lecturas
2 Data Retrieval and Represent slides10m
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(8 questions)10m
1 ejercicio de práctica
Data Acquisition and Presentation quiz30m
3 horas para completar
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 horas para completar
9 videos (Total 109 minutos), 5 lecturas, 1 cuestionario
9 videos
2 Dictionary Use15m
3 Set11m
3.1 Extension: dict and set programming examples12m
1 Extension Library SciPy6m
2 ndarray18m
3 Series7m
4 DataFrame8m
3.2 Extension: Common numpy applications16m
5 lecturas
3 Powerful Data Structure and Software Ecosystem slides10m
3.1 Programming exercise(Not Graded)10m
3.1 Classic dict programming(1 question)10m
3.2 Programming exercise for DataFrame(Not Graded)10m
3.2 Modify the DataFrames10m
1 ejercicio de práctica
Powerful Data Structures and Python Extension Libraries quiz28m
10 horas para completar
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 horas para completar
12 videos (Total 222 minutos), 13 lecturas, 3 cuestionarios
12 videos
2 Fundamentals of Python Plotting23m
3 Data Clean of Data Exploration and Preprocessing20m
4 Data Transformation of Data Precessing22m
5 Data Reduction of Data Preproccessing18m
1 Basic Data Characteristics Analysis of Data Exploration24m
2 Data Statistics and Analysis Based on pandas27m
3 Cluster Analysis14m
4 Aplications of Python into Science and Engineering Fields7m
5 Applications into Humanities and Social Sciences Fields7m
4.2 Extension: An Analysis of the Differences between Males and Females on Film Ratings17m
4.2 Extension: Classification of Red Wine Data Based on Random Forest Model21m
13 lecturas
4.1 Data retrieval and preprocessing of Python Slides10m
4.1 References10m
4.1.1 code snippets for reference only10m
4.1.3: Analyze test results using Box-plot10m
Web API - TuShare and Data Analysis ta30m
4.1 Titanic Data Set Acquisition10m
4.2 Data Statistics, Mining and Application Slides10m
4.2 code snippets for reference only10m
4.2.1 K-means algorithm an discussion on K value10m
4.2.1 Extension: Scikit-learn Machine Learning Basics10m
4.2.6 Project- —Linear Regression for Boston houses price prediction10m
4.2.6 Extension: Introduction to WAV audio processing10m
4.2.7 Learn More about NLTK10m
2 ejercicios de práctica
Data retrieval and preprocessing of Python quiz16m
Data Statistics, Mining and Application quiz20m
Principales revisiones sobre Data Processing Using Python
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.
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.
ofrecido por
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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si compro el Certificado?
Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.