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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-analysis-python
课程评论：没有评论
课程名称：使用Python进行数据分析 概述：本课程为学生提供了使用Python进行基本数据科学技术的介绍。学生将了解核心概念，如数据框（Data Frame）和数据连接，并学习如何使用数据分析库，如pandas、numpy和matplotlib。课程涵盖了如何加载、检查和查询现实世界数据，并回答有关这些数据的基本问题。学生将掌握数据聚合、总结以及基本数据可视化的技能。 课程大纲： 模块1：使用csv模块加载、查询和筛选数据 描述：本模块为学生提供了使用Python简单csv库加载、检查和探索数据的概述。首先，模块包括Jupyter Notebook的简要介绍和基础Python的回顾，涵盖数据结构、循环和函数。随后，模块深入分析存储在.csv文件中的数据，包括基本查询、处理数据错误的方法，以及如何根据各种标准筛选和排序数据。 模块2：使用pandas加载、查询、连接和筛选数据 描述：在本模块中，学生将被介绍到核心概念，如数据框和数据连接。学生将获得使用行业标准数据分析库pandas加载和查询现实世界数据的实践经验，并回答有关该数据的问题。模块展示了如何进行高级筛选和索引、获取数据的子集、限制查询结果中的数据属性以及进行基本计算。内容包括构建简单推荐系统的方法、清理数据的策略、处理缺失值和创建新数据。 模块3：数据汇总和可视化 描述：本模块进一步推进数据分析的过程，概述了数据聚合、汇总和可视化。学生将接触到分组和索引数据的概念，以及如何使用pandas在数据透视表中显示结果。本模块还演示了如何使用Jupyter Notebook准备和可视化数据，包括直方图和散点图。学生将掌握数据聚合、汇总和基本数据可视化的技能，并获得使用数据分析库numpy和matplotlib的经验。
Name:Module 1 : Loading, Querying, & Filtering Data Using the csv Module
Description:This first module provides students with an overview of loading, inspecting, and exploring data using Python's simple csv library. To get started, this module includes a brief overview of Jupyter Notebook and a concise review of basic Python, including data structures, loops, and functions. This module showcases to the students an in-depth analysis of data stored in a .csv file, including basic querying, approaches for dealing with data errors, and how to filter and sort data based on a variety of criteria.
Name:Module 2 : Loading, Querying, Joining & Filtering Data Using pandas
Description:In this module, students are introduced to core concepts like the Data Frame and joining data. Students will get experience using pandas, an industry-standard data analysis library, to load and query real-world data and to answer questions about that data. This module demonstrates how to do advanced filtering and indexing, slice subsets of data, restrict data attributes in query results, and do basic computations over the data. Includes how to build a simple recommendation system, and approaches for cleaning data, dealing with missing values, and creating new data.
Name:Module 3 : Summarizing & Visualizing Data
Description:This module takes data analysis a step further by providing an overview of the process of aggregating, summarizing, and visualizing data. Students are introduced to the concept of grouping and indexing data, and how to display results in a pivot table using pandas. This module also demonstrates how to prepare and visualize data using a histogram and scatterplot in Jupyter Notebook. Students will gain skills in data aggregation and summarization, as well as basic data visualization. In addition, students will get experience using data analysis libraries like numpy and matplotlib.
This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.
