Glue is a Python library to explore relationships within and among related datasets. Its main features include:手机在线看片欧美亚洲,午夜宫,赠我予白
Linked Statistical Graphics. With Glue, users can create scatter plots, histograms and images (2D and 3D) of their data. Glue is focused on the brushing and linking paradigm, where selections in any graph propagate to all others.
Flexible linking across data. Glue uses the logical links that exist between different data sets to overlay visualizations of different data, and to propagate selections across data sets. These links are specified by the user, and are arbitrarily flexible.
Full scripting capability. Glue is written in Python, and built on top of its standard scientific libraries (i.e., Numpy, Matplotlib, Scipy). Users can easily integrate their own python code for data input, cleaning, and analysis.鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧
The latest version of glue is v0.15 - find out what’s new in glue!鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧
Glue is designed with “data-hacking” workflows in mind, and can be used in different ways. For instance, you can simply make use of the graphical Glue application as is, and never type a line of code. However, you can also interact with Glue via Python in different ways:
Using the IPython terminal built-in to the Glue application鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧
Sending data in the form of NumPy arrays or Pandas DataFrames to Glue for exploration from a Python or IPython session.
Customizing/hacking your Glue setup using
config.pyfiles, including automatically loading and clean data before starting Glue, writing custom functions to parse files in your favorite file format, writing custom functions to link datasets, or creating your own data viewers. 鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧
Glue thus blurs the boundary between GUI-centric and code-centric data exploration. In addition, it is also possible to develop your own plugin packages for Glue that you can distribute to users separately, and you can also make use of the Glue framework in your own application to provide data linking capabilities.
To see how glue compares with other open-source and commercial data visualization solutions, you can view this comparison table.鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧
In the following sections, we cover the different ways of using Glue from the Glue application to the more advanced ways of interacting with Glue from Python.
Using the Glue application¶
- 手机在线看片欧美亚洲,午夜宫,赠我予白Installing and running glue
- Getting started
- 我诚实地说 谁是你的室友？你喜欢她？ 好吧 告诉我 mae把我带到了她的身旁Advanced User Interface Guide
Interacting with data from Python¶
- 手机在线看片欧美亚洲,午夜宫,赠我予白Introduction to customizing/extending glue
- List of available plugins
- Configuring Glue via a startup file
- 手机在线看片欧美亚洲,午夜宫,赠我予白Customizing your Glue environment
- Distributing your own plugin package
- Customizing the coordinate system of a data object
even though he was the reason i was leaving no - wait was in character and even though i knew i had nothing to fear from wolfe wolfe leaned forward and shook a finger at meProgrammatically configuring viewers
- Writing a simple custom data viewer
- Watching data for changes手机在线看片欧美亚洲,午夜宫,赠我予白
- Custom fitting plugins
The Glue architecture¶近距离爱上你小说.杨思敏1一5集国语版在线看1996.长春市天气预报鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧
The pages below take you through the main infrastructure in Glue, and in particular how selections, linking, and communications are handled internally. You don’t need to understand all of this in order to get started with contributing, but in order to tackle some of the more in-depth issues, this will become important. This is not meant to be a completely exhaustive guide, but if there are areas that you feel could be explained better, or are missing and would be useful, please let us know!
Information on the Data framework is available in Working with Data objects and is not repeated here.
If you use glue for research presented in a publication, please consider citing the following two references:
The first is a conference proceedings describing glue, while the second is the software itself.手机在线看片欧美亚洲,午夜宫,赠我予白
鎵嬫満鍦ㄧ嚎鐪嬬墖娆х編浜氭床,鍗堝瀹?璧犳垜浜堢櫧Robitaille et al (2017) glueviz v0.10: multidimensional data exploration