Introspection, 内省 ?,在标识符前或后加上,显示出对象状况和docstring ??,显示出source code ?,在命名空间中search 比如用tab completion,对于numpy太多属性和函数,想用通配符*去search和过滤,但tab completion是不支持的,这时候用? The %run Command 可以直接执行一个python脚本, In [550]: %run ipython_script...
This pragmatic guide will help train you in one of the most important tools in the field - Python. Filled with practical case studies, ... (展开全部) Python for Data Analysis的创作者 ··· Wes McKinney 作者 作者简介 ··· Wes McKinney 资深数据分析专家,对各种Python库(包括NumPy、panda...
some of which (like Bokeh and Altair) take advantage of modern web technology to create interactive visualizations that integrate well with the Jupyter notebook. Rather than use multiple visualization tools in this book, I decided to stick with matplotlib for teaching the fundamentals, ...
Data analysts in modern data-driven Enterpriseswant to be empowered with powerful new-age tools and strategies to extract a wealth of actionable insights at the speed of business in near real-time. Python, with its diverse libraries, packages, and frameworks, can democratize data ana...
Wes McKinney is a Nashville-based software developer and entrepreneur. After finishing his undergraduate degree in mathematics at MIT in 2007, he went on to do quantitative finance work at AQR Capital Management in Greenwich, CT. Frustrated by cumbersome data analysis tools, he learned Python and ...
利用Python进行数据分析 2017 第二版 (Python for Data Analysis, 2nd Edition)中文翻译笔记 这本书的英文版github仓库:pydata-book 作者Wes McKinney是pandas的创作者,所以书中关于pandas的讲解也是最实用的部分。我也直接联系过了Wes本人,这个笔记不会有任何版权问题,当然,也不会用于任何商业用途。
For the most part, data analytics libraries in Python are at least somewhat derived from the NumPy library, which includes hundreds of mathematical calculations, operations, and functions. Python analytics tools have become popular due to the computer language’s widespread adoption and its versatility...
The library contains convenience functions for data cleaning, feature selection & extraction, visualization, partitioning data for model validation, and versioning transformations of data. The library uses and is intended to be a helpful addition to common Python data analysis tools such as pandas, sci...
tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to ...
This chapter will introduce Ethics in algorithm development and common tools that are used for data analysis. Ethics is an important consideration in developing Artificial Intelligence algorithms. The outputs of computers are derived from the data that are provided as input and the algorithms developed...