datavisual-tools

从今天开始我准备写一个系列的博客，题目取为《最流行的14款数据可视化库/工具》。下面的可视化库主要是用来作图展示。一图胜千言，让我们用图说话?

计划

总共是14个库，我的计划是花费半年写完，也就是6个月的时间。因为工作的关系，时间上不能充分地保证，但是基本上每半个月一定会写完一个库?

坚持就是胜利✌️见证半年后丰收的日子

内容

针对于每个库，将来会从它的安装、特点、使用细节、案例等方面来展开?，希望在提升自己技能的同时，也希望能够对数据、可视化方向感兴趣的小伙伴有所帮助?

完成之后，所有的资源都会开源出来，敬请期待come on！

环境、工具

环境

• Python3.7.5
• Anaconda
• Jupyter notebook
• MacOS系统

工具

• Typora（写博客）
• Markdown （博客格式.md文档）
• iPic（上传图片）

14个库

Matplotlib

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

Matplotlib makes easy things easy and hard things possible.

Seaborn

Seaborn is a Python data visualization library based on matplotlib.

It provides a high-level interface for drawing attractive and informative statistical graphics.

Plotly_express

Plotly Express is a terse, consistent, high-level API for rapid data exploration and figure generation.

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on “tidy” data and produces easy-to-style figures. Every Plotly Express function returns a graph_objects.

Figure object whose data and layout has been pre-populated according to the provided arguments.

Bokeh

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.

Pyecharts

Echarts 是一个由百度开源的数据可视化，凭借着良好的交互性，精巧的图表设计，得到了众多开发者的认可。而 Python 是一门富有表达力的语言，很适合用于数据处理。当数据分析遇上数据可视化时，pyecharts 诞生了。

image-20200427235601525

D3.js

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

Google Chart

Google Charts provides a perfect way to visualize data on your website. From simple line charts to complex hierarchical tree maps, the chart gallery provides a large number of ready-to-use chart types.

The most common way to use Google Charts is with simple JavaScript that you embed in your web page. You load some Google Chart libraries, list the data to be charted, select options to customize your chart, and finally create a chart object with an id that you choose. Then, later in the web page, you create a `` with that id to display the Google Chart.

HighCharts

Make your data come alive

product illustration

Highcharts is a modern SVG-based, multi-platform charting library. It makes it easy to add interactive charts to web and mobile projects.

It has been in active development since 2009, and remains a developer favorite due to its robust feature set, ease of use and thorough documentation.

Gephi

Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free

Tableau

Tableau 是极强大、安全且灵活的端到端数据分析平台，提供从连接到协作的一整套功能。借助数据的力量提高人员素质。Tableau 是一个独一无二的商业智能平台，可以将数据转化为指导行动的见解。它既提供了适合个人用户的功能，又能够扩展到企业规模。

Tableau Prep

Tableau Prep 可帮助您准备用于分析的数据 。让更多人员能够快速、自信地合并、组织和清理自己的数据。

Tableau Desktop

Tableau Desktop 被誉为可视化分析的“黄金标准”，是为分析而生的完美工具。凭借易于使用的界面，Tableau Desktop 在商业智能产业引发了颠覆性变革。

Tableau Online

Tableau Online 帮助您实现云端自助式分析。无需管理任何服务器，安全，可扩展。

Tableau Server

Tableau Server 可以实现您的企业需要的真正企业级分析，让人们可以轻松地共享和管理本地或公有云端的数据与见解。

image-20200428004703126

DataV

DataV数据可视化是使用可视化应用的方式来分析并展示庞杂数据的产品

DataV旨让更多的人看到数据可视化的魅力，帮助非专业的工程师通过图形化的界面轻松搭建专业水准的可视化应用，满足您会议展览、业务监控、风险预警、地理信息分析等多种业务的展示需求。

Datawrapper

Enrich your stories with charts, maps and tables

RawGraphs

RAW Graphs is an open source data visualization framework built with the goal of making the visual representation of complex data easy for everyone.

Primarily conceived as a tool for designers and vis geeks, RAW Graphs aims at providing a missing link between spreadsheet applications (e.g. Microsoft Excel, Apple Numbers, OpenRefine) and vector graphics editors (e.g. Adobe Illustrator, Inkscape, Sketch).

The project, led and maintained by the DensityDesign Research Lab (Politecnico di Milano) was released publicly in 2013 and is regarded by many as one of the most important tools in the field of data visualization.

image-20200428001705562

Chartblocks

The online chart building tool

The world’s easiest chart builder app. Design and share a chart in minutes.

加油呀⛽️