Python数据分析项目

端到端数据分析，采用python语言，Python－End to end Data Analysis.zip

Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. What You Will Learn • Understand how to install and manage Anaconda • Read, sort, and map data using NumPy and pandas • Find out how to create and slice data arrays using NumPy • Discover how to subset your DataFrames using pandas • Handle missing data in a pandas DataFrame • Explore hierarchical indexing and plotting with pandas

Python for Data Analysis-带书签目录超清文字版英文版 这个是带完整目录书签的文字版本，文本内容可以复制的哦

Title: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, 2nd Edition Author: Wes McKinney Length: 550 pages Edition: 2 Language: English Publisher: O'Reilly Media Publication Date: 2017-09-25 ISBN-10: 1491957662 ISBN-13: 9781491957660 Table of Contents Chapter 1 Preliminaries Chapter 2 Python Language Basics, IPython, and Jupyter Notebooks Chapter 3 Built-in Data Structures, Functions, and Files Chapter 4 NumPy Basics: Arrays and Vectorized Computation Chapter 5 Getting Started with pandas Chapter 6 Data Loading, Storage, and File Formats Chapter 7 Data Cleaning and Preparation Chapter 8 Data Wrangling: Join, Combine, and Reshape Chapter 9 Plotting and Visualization Chapter 10 Data Aggregation and Group Operations Chapter 11 Interlude: Data Analysis Examples Chapter 12 Time Series Chapter 13 Advanced NumPy Chapter 14 Using Modeling Libraries with pandas Chapter 15 Examples Data Sets Appendix Advanced IPython and Jupyter

伊丽莎白-约瑟芬-纽马克-技术试验 从消费者的角度评估有助于肯尼亚品牌声誉的因素。 使用R语言和Rstudio进行的分析。 附加文件 Newmark Analytics正在开展一项名为“肯尼亚消费者对品牌声誉认知度的决定因素”的调查。 这项研究的目的是从客户的角度评估影响肯尼亚品牌声誉的因素。 如果html对于github而言太大，则链接到文件

股市探索数据分析笔记本 使用库Numpy，Matplotlib和Pandas进行股票市场数据集探索性数据分析的Jupyter Notebook。 数据集具有以下功能： serial_number：每个变量的唯一标识符 time_stamp：捕获数据的日期 open_value：指定日期的期初值 maximum_value：在特定日期达到的索引的最高值 minimum_value：特定日期的索引的最低值 resolve_value：结算当天的值 volume_sell：卖出指数的数量

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SARS Covid 2的全球数据分析 网络抓取工具worldosmeters_scraper.exe从worldometers.info中获取所有数据，并每天创建所有国家/地区的today_worldwide_covid19_data.csv数据库。 然后， covid19_analysis_2.2.py分析所有数据。 该脚本有两种语言，希腊语和英语。 只需输入“ GR”（希腊）或“ EN”（英语）即可。 如果您想测试脚本，只需下载covid19_analysis_2.2.exe并运行它。 today_worldwide_covid19_data.csv每天更新。 与old_version的区别在于，现在您可以从.csv文件中的224检查每个国家或地区的统计信息而且您只需下载一次.exe，而不是每天都要下载的旧版本！ 输出： 资料来源

目录 1 - 1 - Unit 1- Introduction (3-23).mp4 1 - 2 - Unit 1, Part 1- (1) Data Basics (4-52).mp4 1 - 3 - Unit 1, Part 1- (2) Observational Studies and Experiments (4-44).mp4 1 - 4 - Unit 1, Part 1- (3) Sampling and Sources of Bias (7-53).mp4 1 - 5 - Unit 1, Part 1- (4) Experimental Design (2-59).mp4 1 - 6 - Unit 1, Part 1- (Spotlight) Random Sample Assignment (3-47).mp4 1 - 7 - Unit 1, Part 2- (1) Visualizing Numerical Data (12-57).mp4 1 - 8 - Unit 1, Part 2- (2) Measures of Center (5-17).mp4 .....