numpy官方用户手册150页，适合做numpy快速入门，numpyapi手册可以作为参考工具书

由官网没有64位工具包，楼主耗时两天配置python64位下numpy、matplotlib、scipy、dateutil、pyparsing的安装，附带安装包和操作指南。实现傻瓜式安装

NumPy是使用Python进行科学计算的基础软件包。除了明显的科学用途外，NumPy还可以用作通用数据的高效多维容器。可以定义任意数据类型。这使NumPy能够无缝快速地与各种数据库集成。

绘制散点图 假设通过爬虫你获取到了北京2016年3,10月份每天白天的最高气温(分别位于列表a,b),那么此时如何寻找出气温和随时间(天)变化的某种规律? a = [11,17,16,11,12,11,12,6,6,7,8,9,12,15,14,17,18,21,16,17,20,14,15,15,15,19,21,22,22,22,23] b = [26,26,28,19,21,17,16,19,18,20,20,19,22,23,17,20,21,20,22,15,11,15,5,13,17,10,11,13,12,13,6] 数据来源: http://lishi.tianqi.com/beijing/index.html

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

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

吴恩达网易云公开课《深度学习》week4--deep_nn_model二分类

纯手写卷积神经网络，未使用任何神经网络框架，使用numpy纯手写卷积神经网络，研究此代码可充分搞懂卷积神经网络原理，本人也是通过此代码亲自走过来的。代码简单。 适用人群：适用于有意愿彻底搞懂卷积神经网络底层原理的同学，适合做该领域研究的学者，较易上手。 阅读建议：对于想学习python的同学，可通过此小项目一边研习python代码语法，一边学习卷积神经网络算法，可以很快入门python,并掌握基础的卷积神经网络算法。

numpy-1.13.3+mkl-cp27-cp27m-win_amd64.whl，安装包，可以便捷地在python里配置numpy工具，已经实际操作测试过，可顺利运行！

numpy-1.14.5+mkl-cp36-cp36m-win_amd64.zip科学计算包库，.whl格式，pip安装毫无压力