HTML5 Chart Lib Introduction
表格抓取,存库,提取成图(从国家外汇管理局官网爬取汇率信息)
表格抓取，存库，提取成图（从国家外汇管理局官网爬取汇率信息）从国家外汇管理局官网爬取汇率信息，并使用一、分析网页爬虫1.使用post方法读取import requestspayload = {'projectBean.startDate':'2017-02-01','projectBean.endDate':'2017-05-01','queryYN':'true'}res = requests.post('/AppStructured/view/project_RMBQuery.action', data = payload)#res#res.text2.安装html5lib可以不先安装，如步骤3提示：html5lib not found, please install it，再安装也可pip install html5lib3.剖析汇率信息from bs4 import BeautifulSoupimport pandassoup = BeautifulSoup(res.text, 'html.parser')3.1查看soup.select('#InfoTable')[0]格式，因pandas读取的字节格式数据#type(soup.select('#InfoTable')[0])#type(soup.select('#InfoTable')[0].prettify('utf-8'))#soup.select('#InfoTable')[0].prettify('utf-8')#pandas.read_html(soup.select('#InfoTable')[0].prettify('utf-8'))3.2使用pandas读取表格数据dfs = pandas.read_html(soup.select('#InfoTable')[0].prettify('utf-8'), header=0)#len(dfs) #查看元素个数为1#dfs[0]3.3将数据装载df_rates = dfs[0]3.4查看数据#df_rates.head()4。
数据采集1+x中级习题(含答案)
数据采集1+x中级习题（含答案）一、单选题（共63题，每题1分，共63分）1.HBase 分布式存储和负载均衡的最小单元为( )。
A、RegionB、StoreC、HFileD、MemStore正确答案：A2.Logstash的INPUT数据输入配置中用于开发人员进行测试的方式是哪一种A、filebeatB、kafkaC、stdinD、file正确答案：C3.检索所有比“王华”年龄大的学生姓名、年龄和性别。
正确的SELECT 语句是A、SELECT SN，AGE，SEX FROM S WHERE AGE＞(SELECT AGE FROM S WHERE SN=“王华”)B、SELECT SN，AGE，SEX FROM S WHERE SN＝“王华”C、SELECT SN，AGE，SEX FROM S WHERE AGE＞(SELECT AGE WHERE SN=“王华”)D、SELECT SN，AGE，SEX FROM S WHERE AGE＞王华．AGE正确答案：A4.HBase是分布式列式存储系统，记录按什么（）集中存放。
A、列族B、列C、行D、不确定正确答案：A5.关于Python内存管理，下列说法错误的是()A、变量不必事先声明B、变量无须先创建和赋值而直接使用C、可以使用del释放资源D、变量无须指定类型正确答案：B6.数据清洗是针对不符合要求的数据进行处理，以下不属于数据清洗范围的是（）A、错误的数据B、不完整的数据C、重复的数据D、无缺失数据正确答案：D7.Apache服务器的主配置文件A、http.confB、httpd.confC、httpd.cfgD、config.cfg正确答案：B8.HBase虚拟分布式模式须要（）个节点？A、1B、2C、3D、最少3个正确答案：A9.scrapy的哪个命令可以测试爬取网页的整个过程A、scrapy fetchB、scrapy benchC、scrapy shellD、scrapy view正确答案：B10.“ab”+”c”*2 结果是：（）A、abccB、abc2C、ababccD、abcabc正确答案：A11.Tomcat容器数据采集中检查JDK的版本命令为（）A、java -versionB、javacC、java versionD、check version正确答案：A12.HBase分布式模式最好需要（）个节点？A、1B、2C、3D、最少3个正确答案：C13.<input id="jq1 type="text"/>以下哪种可以隐藏该属性（）"A、$("jq1).hide();B、$("#jq1").remove();C、$(#jq1).remove();D、$("#jq1").hide();正确答案：D14.关于python类，说法错误的是（）A、类的类方法可以用对象和类名来调用B、类的静态属性可以用类名和对象来调用C、类的实例方法必须创建对象后才可以调用D、类的实例方法必须创建对象前才可以调用正确答案：D15.（）又称全网爬虫，爬行对象由一批种子URL扩充至整个Web，主要为门户站点、搜索引擎和大型Web服务提供商采集数据。
Chart description
Office
Reception
The past tense is used throughout the extract because the time is finished and is marked by expressions like: # 10 years ago # in 1992 # by the end of 1991 # last year Regular verbs end in ’ed’: reach reached remain remained increase increased drop dropped level leveled Irregular verbs: rise rose fall fell go went be was/were
Describing graphs
Office
Reception-On Working Range, Market and Distribution System
cost
a. b. c. d. e.
a sharp fall /a steep drop a leveling-off/ a stable period a dramatic rise/ a sudden increase a sharp fall/ a steep drop a dramatic rise/ a sudden increase
Office
Office
Chart Description
histogram pie chart trend chart 柱狀圖、直方圖 圓餅圖 趨勢圖 柏拉圖、排列圖
Pareto chart
Pareto diagram
diagram of curve
chart
chartChartIntroduction:In today's data-driven world, charts have become an indispensable tool for visualizing and presenting information. From business analysts to educators and researchers, everyone relies on charts to communicate complex data in a clear and concise manner. This document aims to provide an in-depth understanding of charts, their types, and their significance in various fields.Section 1: What is a Chart?A chart is a graphical representation of data, often depicted in the form of bars, lines, or other symbols. It presents data in a visually appealing manner, making it easier for viewers to grasp trends and patterns. Charts are commonly used in presentations, reports, and dashboards to provide an overview of data or to support key points. They play a crucial role in data analysis and decision-making processes.Section 2: Types of Charts2.1 Bar Charts:Bar charts are one of the most common chart types used to compare values across different categories. They consist of horizontal or vertical bars, with the length or height representing the data values. Bar charts are effective in demonstrating data comparisons, such as sales performance by product category or population distribution by age group.2.2 Line Charts:Line charts are used to represent data changes over time. They consist of data points connected by lines, thereby illustrating trends and patterns. Line charts are widely used in financial analysis, stock market tracking, and weather forecasting. They enable analysts to identify trends, predict future outcomes, and make informed decisions.2.3 Pie Charts:Pie charts are circular charts divided into sectors, each representing a portion of the whole. They are used to showcase proportions and percentages. Pie charts work best when comparing a few categories or when the data set adds up to 100%. They are commonly used in market research, budget allocation, and demographic analysis.2.4 Scatter Plots:Scatter plots are useful for identifying relationships between two variables. They consist of dots plotted on a graph, with the x-axis representing one variable and the y-axis representing another. Scatter plots help establish correlations and identify outliers, making them valuable in scientific research, forecasting, and trend analysis.2.5 Area Charts:Area charts are similar to line charts but filled with color or shading. They are used to visualize cumulative data, often showing how categories contribute to a whole over time. Area charts are commonly used in statistics, economics, and project management. They effectively communicate cumulative data trends and patterns.Section 3: Importance of Charts3.1 Data Visualization:Charts play a vital role in data visualization by transforming complex data sets into concise and understandable visuals. They make data more approachable and enable effective decision-making.3.2 Communication and Presentation:Charts simplify data interpretation and enhance communication between stakeholders. They provide a comprehensive overview and make it easier for the audience to understand and retain information.3.3 Analytics and Insights:Charts facilitate data analysis by highlighting trends, outliers, and patterns. They allow analysts to uncover insights, discover correlations, and make data-driven decisions.3.4 Decision-making:Charts aid in decision-making processes by presenting datain a format that is easy to comprehend. They provide a visual context that supports problem-solving and strategic planning.Conclusion:Charts are an essential tool in visualizing and presenting data. They simplify complex information, facilitate data analysis, enhance communication, and aid in decision-making processes. With a wide range of chart types available, individuals and businesses can effectively present their data and convey key insights. Understanding the various chart types and their applications is crucial for professionals in diverse fields. Embracing the power of charts can significantly improve data analysis and communication, leading to informed decisions and better outcomes.。
BeautifulSoup Python库的中文名称说明书
Table of ContentsAbout1 Chapter 1: Getting started with beautifulsoup2 Remarks2 Versions3 Examples3 Installation or Setup3A BeautifulSoup "Hello World" scraping example3 Chapter 2: Locating elements5 Examples5 Locate a text after an element in BeautifulSoup5 Using CSS selectors to locate elements in BeautifulSoup5 Locating comments6 Filter functions6 Basic usage6 Providing additional arguments to filter functions7 Accessing internal tags and their attributes of initially selected tag7 Collecting optional elements and/or their attributes from series of pages7 Credits10AboutYou can share this PDF with anyone you feel could benefit from it, downloaded the latest version from: beautifulsoupIt is an unofficial and free beautifulsoup ebook created for educational purposes. All the content is extracted from Stack Overflow Documentation, which is written by many hardworking individuals at Stack Overflow. It is neither affiliated with Stack Overflow nor official beautifulsoup.The content is released under Creative Commons BY-SA, and the list of contributors to each chapter are provided in the credits section at the end of this book. Images may be copyright of their respective owners unless otherwise specified. All trademarks and registered trademarks are the property of their respective company owners.Use the content presented in this book at your own risk; it is not guaranteed to be correct nor accurate, please send your feedback and corrections to ********************Chapter 1: Getting started with beautifulsoup RemarksIn this section, we discuss what Beautiful Soup is, what it is used for and a brief outline on how to go about using it.Beautiful Soup is a Python library that uses your pre-installed html/xml parser and converts the web page/html/xml into a tree consisting of tags, elements, attributes and values. To be more exact, the tree consists of four types of objects, Tag, NavigableString, BeautifulSoup and Comment. This tree can then be "queried" using the methods/properties of the BeautifulSoup object that is created from the parser library.Your need : Often, you may have one of the following needs :1.You might want to parse a web page to determine, how many of what tags are found, how many elements of each tag are found and their values. You might want to change them.You might want to determine element names and values, so that you can use them in2.conjunction with other libraries for web page automation, such as Selenium.3.You might want to transfer/extract data shown in a web page to other formats, such as aCSV file or to a relational database such as SQLite or mysql. In this case, the library helps you with the first step, of understanding the structure of the web page, although you will be using other libraries to do the act of transfer.4.You might want to find out how many elements are styled with a certain CSS style and which ones.Sequence for typical basic use in your Python code:1.Import the Beautiful Soup libraryOpen a web page or html-text with the BeautifulSoup library, by mentioning which parser to2.be used. The result of this step is a BeautifulSoup object. (Note: This parser namementioned, must be installed already as part of your Python pacakges. For instance,html.parser, is an in-built, 'with-batteries' package shipped with Python. You could installother parsers such as lxml or html5lib. )3."Query" or search the BeautifulSoup object using the syntax 'object.method' and obtain the result into a collection, such as a Python dictionary. For some methods, the output will be a simple value.4.Use the result from the previous step to do whatever you want to do with it, in rest of your Python code. You can also modify the element values or attribute values in the tree object.Modifications don't affect the source of the html code, but you can call output formattingmethods (such as prettify) to create new output from the BeautifulSoup object.Commonly used methods: Typically, the .find and .find_all methods are used to search the tree, giving the input arguments.The input arguments are : the tag name that is being sought, attribute names and other related arguments. These arguments could be presented as : a string, a regular expression, a list or even a function.Common uses of the BeautifulSoup object include :1.Search by CSS class2.Search by Hyperlink address3.Search by Element Id, tag4.Search by Attribute name. Attribute value.If you have a need to filter the tree with a combination of the above criteria, you could also write a function that evaluates to true or false, and search by that function.VersionsExamplesInstallation or Setuppip may be used to install BeautifulSoup. To install Version 4 of BeautifulSoup, run the command: pip install beautifulsoup4Be aware that the package name is beautifulsoup4 instead of beautifulsoup, the latter name stands for old release, see old beautifulsoupA BeautifulSoup "Hello World" scraping examplefrom bs4 import BeautifulSoupimport requestsmain_url = "https:///wiki/Hello_world"req = requests.get(main_url)soup = BeautifulSoup(req.text, "html.parser")# Finding the main title tag.title = soup.find("h1", class_ = "firstHeading")print title.get_text()# Finding the mid-titles tags and storing them in a list.mid_titles = [tag.get_text() for tag in soup.find_all("span", class_ = "mw-headline")]# Now using css selectors to retrieve the article shortcut linkslinks_tags = soup.select("li.toclevel-1")for tag in links_tags:print tag.a.get("href")# Retrieving the side page links by "blocks" and storing them in a dictionaryside_page_blocks = soup.find("div",id = "mw-panel").find_all("div",class_ = "portal")blocks_links = {}for num, block in enumerate(side_page_blocks):blocks_links[num] = [link.get("href") for link in block.find_all("a", href = True)]print blocks_links[0]Output:"Hello, World!" program#Purpose#History#Variations#See_also#References#External_links[u'/wiki/Main_Page', u'/wiki/Portal:Contents', u'/wiki/Portal:Featured_content',u'/wiki/Portal:Current_events', u'/wiki/Special:Random',u'https:///wiki/Special:FundraiserRedirector?utm_source=donate&utm_medium=sidebar&u u'//']Entering your prefered parser when instanciating Beautiful Soup avoids the usual Warningdeclaring that no parser was explicitely specified.Different methods can be used to find an element within the webpage tree.Although a handful of other methods exist, CSS classes and CSS selectors are two handy ways tofind elements in the tree.It should be noted that we can look for tags by setting their attribute value to True when searching them.get_text() allows us to retrieve text contained within a tag. It returns it as a single Unicode string.tag.get("attribute") allows to get a tag's attribute value.Read Getting started with beautifulsoup online:https:///beautifulsoup/topic/1817/getting-started-with-beautifulsoupChapter 2: Locating elementsExamplesLocate a text after an element in BeautifulSoupImagine you have the following HTML:<div><label>Name:</label>John Smith</div>And you need to locate the text "John Smith" after the label element.In this case, you can locate the label element by text and then use .next_sibling property:from bs4 import BeautifulSoupdata = """<div><label>Name:</label>John Smith</div>"""soup = BeautifulSoup(data, "html.parser")label = soup.find("label", text="Name:")print(label.next_sibling.strip())Prints John Smith.Using CSS selectors to locate elements in BeautifulSoupBeautifulSoup has a limited support for CSS selectors, but covers most commonly used ones. Use select() method to find multiple elements and select_one() to find a single element.Basic example:from bs4 import BeautifulSoupdata = """<ul><li class="item">item1</li><li class="item">item2</li><li class="item">item3</li></ul>"""soup = BeautifulSoup(data, "html.parser")for item in soup.select("li.item"):print(item.get_text())Prints:item1item2item3Locating commentsTo locate comments in BeautifulSoup, use the text (or string in the recent versions) argument checking the type to be Comment:from bs4 import BeautifulSoupfrom bs4 import Commentdata = """<html><body><div><!-- desired text --></div></body></html>"""soup = BeautifulSoup(data, "html.parser")comment = soup.find(text=lambda text: isinstance(text, Comment))print(comment)Prints desired text.Filter functionsBeautifulSoup allows you to filter results by providing a function to find_all and similar functions. This can be useful for complex filters as well as a tool for code reuse.Basic usageDefine a function that takes an element as its only argument. The function should return True if the argument matches.def has_href(tag):'''Returns True for tags with a href attribute'''return bool(tag.get("href"))soup.find_all(has_href) #find all elements with a href attribute#equivilent using lambda:soup.find_all(lambda tag: bool(tag.get("href")))Another example that finds tags with a href value that do not start withProviding additional arguments to filter functionsSince the function passed to find_all can only take one argument, it's sometimes useful to make 'function factories' that produce functions fit for use in find_all. This is useful for making your tag-finding functions more flexible.def present_in_href(check_string):return lambda tag: tag.get("href") and check_string in tag.get("href")soup.find_all(present_in_href("/partial/path"))Accessing internal tags and their attributes of initially selected tagLet's assume you got an html after selecting with soup.find('div', class_='base class'):from bs4 import BeautifulSoupsoup = BeautifulSoup(SomePage, 'lxml')html = soup.find('div', class_='base class')print(html)<div class="base class"><div>Sample text 1</div><div>Sample text 2</div><div><a class="ordinary link" href="https://">URL text</a></div></div><div class="Confusing class"></div>'''And if you want to access <a> tag's href, you can do it this way:a_tag = html.alink = a_tag['href']print(link)https://This is useful when you can't directly select <a> tag because it's attrs don't give you unique identification, there are other "twin" <a> tags in parsed page. But you can uniquely select a parent tag which contains needed <a>.Collecting optional elements and/or their attributes from series of pagesLet's consider situation when you parse number of pages and you want to collect value fromelement that's optional (can be presented on one page and can be absent on another) for a paticular page.Moreover the element itself, for example, is the most ordinary element on page, in other words no specific attributes can uniquely locate it. But you see that you can properly select its parent element and you know wanted element's order number in the respective nesting level.from bs4 import BeautifulSoupsoup = BeautifulSoup(SomePage, 'lxml')html = soup.find('div', class_='base class') # Below it refers to html_1 and html_2Wanted element is optional, so there could be 2 situations for html to be:html_1 = '''<div class="base class"> # №0<div>Sample text 1</div> # №1<div>Sample text 2</div> # №2<div>!Needed text!</div> # №3</div><div>Confusing div text</div> # №4'''html_2 = '''<div class="base class"> # №0<div>Sample text 1</div> # №1<div>Sample text 2</div> # №2</div><div>Confusing div text</div> # №4'''If you got html_1 you can collect !Needed text! from tag №3 this way:wanted tag = html_1.div.find_next_sibling().find_next_sibling() # this gives you whole tag №3It initially gets №1 div, then 2 times switches to next div on same nesting level to get to №3.wanted_text = wanted_tag.text # extracting !Needed text!Usefulness of this approach comes when you get html_2 - approach won't give you error, it will give None:print(html_2.div.find_next_sibling().find_next_sibling())NoneUsing find_next_sibling() here is crucial because it limits element search by respective nesting level. If you'd use find_next() then tag №4 will be collected and you don't want it:print(html_2.div.find_next().find_next())<div>Confusing div text</div>You also can explore find_previous_sibling() and find_previous() which work straight opposite way.All described functions have their miltiple variants to catch all tags, not just the first one:find_next_siblings()find_previous_siblings()find_all_next()find_all_previous()Read Locating elements online: https:///beautifulsoup/topic/1940/locating-elementsCredits。
beautifulsoup简介
b e a u t i f u l s o u p 简介B B e e a a u u t t i i f f u u l l S S o o u u p p 是是一一个个用用于于解解析析 H H T T M M L L 和和 X X M M L L 文文档档的的 P P y y t t h h o o n n 库库。
它它提提供供了了一一种种简简单单和和灵灵活活的的方方式式来来从从网网页页中中提提取取数数据据，，例例如如抓抓取取特特定定的的标标签签、、获获取取标标签签的的属属性性、、提提取取文文本本内内容容等等。
B B e e a a u u t t i i f f u u l l S S o o u u p p 解解析析器器能能够够处处理理不不规规范范的的标标记记，，并并能能根根据据标标签签的的嵌嵌套套关关系系进进行行数数据据提提取取。
B B e e a a u u t t i i f f u u l l S S o o u u p p 的的主主要要功功能能包包括括：：11.. 解解析析文文档档：：B B e e a a u u t t i i f f u u l l S S o o u u p p 提提供供了了各各种种解解析析器器（（如如 l l x x m m l l 、、h h t t m m l l ..p p a a r r s s e e r r 、、h h t t m m l l 55l l i i b b ）），，可可以以将将 H H T T M M L L 或或 X X M M L L 文文档档加加载载到到内内存存中中，，并并生生成成一一个个可可以以遍遍历历的的树树形形结结构构。
22.. 遍遍历历文文档档树树：：可可以以使使用用 B B e e a a u u t t i i f f u u l l S S o o u u p p 的的方方法法和和属属性性来来遍遍历历文文档档树树，，如如查查找找特特定定的的标标签签、、获获取取标标签签的的属属性性、、获获取取标标签签的的文文本本内内容容等等。
python单机版自动化测试框架源代码（selenium+Appium+requests+。。。
python单机版⾃动化测试框架源代码（selenium+Appium+requests+。
⼀、⾃动化测试框架：1、框架和项⽬源代码下载说明：框架可以⽀持web界⾯UI、安卓Android，ios苹果、接⼝API等⾃动化测试。
⽂档和代码持续维护更新，有问题可以交流。
2、依赖包安装2.1、jdk2.2、python安装下载地址：或2.3、python依赖包pip install seleniumpip install xlrdpip install pymysqlpip install lxmlpip install Pillowpip install win32guipip install win32conpip install requestspip install qrcodepip install pexpectpip install chinesecalendarpip install automagicapip install tusharepip install imapclientpip install pymysqlpip install schedulepip install paramikopip install pypiwin32pip install pdfminer3Kpip install browsermob-proxypip install pywin32pip install python-dateutilpip install bs4pip install configparserpip install beautifulsoup4pip install html5libpip install matplotlibpython -m pip install cx_Oracle --upgradepip install sqlparsepip install DBUtilspip install keyboard2.3、chrome driver2.3.1、chrome driver的下载地址:2.3.2、安装下载解压放到chrome的安装⽬录下...\Google\Chrome\Application\设置path环境变量，把chrome的安装⽬录（我的：C:\ProgramFiles\Google\Chrome\Application）1、因信息安全原因，删除了真实项⽬配置⽂件中密码和http⽹页真实地址2、以业务物流追踪（ipadWuLiuZhuiZong.py）中国港⼝功能为样例，做了界⾯检查、数据库与界⾯数据对⽐、字体颜⾊（红绿）检查等功能，仅供参考⼆、简介：1. 外部⼯具：上⾯⾃动化包⽬录“autoTest\basic\browsermob-proxy”中已经包含2. autoTest\conf\config.ini可以配置⽇志级别3. autoTest\caseexcel\ipadWebCase.xls是ipad⽹页项⽬Excel⽤例，“ipadApiCase.xls"是API接⼝⽤例，"⼤屏WebCase.xls"是⼤屏项⽬⽤例，"#url.xls"是⽣产和测试等⽹页地址配置⽂件4. autoTest\basic是基础脚本，基本所有项⽬通⽤，mySysCommon.py为系统常⽤函数功能class，webTestCase.py为UI⾃动化测试常⽤函数功能class5. autoTest\report是⽤于存放测试报告和过程图⽚6. autoTest\log是⽤于存放过程⽇志7. autoTest\cases\Zd为某项⽬⾃动化脚本，allData.json为公共数据变量⽂件，publicOperation.py为当前项⽬共⽤函数，comm.py中编写unittest的test开头⽤例，ipadDanJi.py和ipadWuLiuZhuiZong.py是各测试模块。
数据采集1+x初级模考试题(含答案)
数据采集1+x初级模考试题（含答案）一、单选题（共40题，每题1分，共40分）1、re模块的常用方法中用于将输入的字符串整个扫描并返回第一个成功的匹配的是( )。
A、searchB、subC、compileD、split正确答案：A2、以下对 Python 程序缩进格式描述错误的选项是：A、不需要缩进的代码顶行写，前面不能留空白B、缩进可以用 tab 键实现，也可以用多个空格实现C、缩进是用来格式美化 Python 程序的D、严格的缩进可以约束程序结构，可以多层缩进正确答案：C3、以下CSS中，不属于font属性的是（）A、font-sizeB、font-weightC、sizeD、font-style正确答案：C4、哪个表达式用来选取当前节点？A、@B、.C、..D、/正确答案：B5、关于 Python 语言的注释，以下选项中描述错误的是A、Python 语言的单行注释以单引号’ 开头B、Python 语言的单行注释以#开头C、Python 语言的多行注释以’ ’ '（三个单引号）开头和结尾D、Python 语言有两种注释方式：单行注释和多行注释正确答案：A6、jQuery中操作DOM时，以下哪个方法可以删除所有匹配的元素（）A、removeAll()B、remove()C、empty()D、delete()正确答案：B7、ELK在安装过程中，彼此之间存在一定的依赖关系，正确的安装顺序是( )。
A、Logstash-ElasticSearch-KibanaB、ElasticSearch-Kibana-LogstashC、ElasticSearch-Logstash-KibanaD、Kibana-ElasticSearch-Logstash正确答案：C8、Python不支持的数据类型有()A、floatB、intC、charD、list正确答案：C9、httpd采用( )模块化设计方法A、core +moduleB、core + modulesC、modulesD、core正确答案：B10、Tomcat默认发布项目的位置为（）A、appsB、webappsC、WEB-INFD、classes正确答案：B11、获取页面中title标签的内容，xpath代码为（）A、//title/@text()B、//title/text()C、//title/@textD、//title/text正确答案：B12、FTP 的主要特点不包括（）。
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Flotr2 - /flotr2/index
简介
− 基于HTML5 − 提供多种图样：Bar, pie , line, candle, bubble − 灵活性高
− 图样可自定义 − 插件可自定义
− 开源
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Jscharts
特性
− 使用简单，只需客户端编码
− − − − 引入jscharts.js setDataArray设置数据，XML/JSON/Array setXXX方法设置属性 draw()方法绘制
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ZingChart
Demo
/learn/docs.php
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canvasXpress
Overview
CanvasXpress is a javascript library based on the <canvas> tag implemented in HTML5. It’s the core visualization component of BMS systems biology platform. It works in all major browsers: Chrome, Firefox, Safari, Opera, Webkit and IE; and in all operating systems: Windows, Mac, Linux, Android, iOS, etc. Website:
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ZingChart
Supported Chart Types (1)
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ZingChart
− 兼容性强 − 样式美观
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Jscharts
样例
− /examples
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Flotr2
特性1
− 使用较简单
− 引入flotr2.min.js − 以Array保存数据 − Flotr.draw(container, data, options) − Container：DOM element；options：configuration object
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canvasXpress
Supported Graphs
bar graphs, line graphs, bar-line combination graphs,boxplots, dotplots, area graphs, arealine combination graphs, stacked graphs, stacked-line combination graphs, percentage-stacked graphs, percentage-stacked-line combination graphs,heatmaps, heatmaps, 2D-scatter plots, 2D-scatter bubble plots, 3D-scatter plots, pie charts,correlation plots, Venn diagrams, networks (or pathways), candlesticks plots and genome browser
Canvas
Canvas/SVG Canvas Canvas Canvas Canvas Canvas
MooTools
JavaScript Yahoo UI Prototype DoJo ExtJS jQuery
Flotr2
Rickshaw Awesome Chart JS canvasXpress Humble Finance RGraph HighChart gRaphael jqPlot Sparklines FusionChart
主要Charts Library介绍
Charts库 Flot JS Chart 绘图引擎 Canvas Canvas 基于框架 jQuery JavaScript
TableToChart
PlotKit Yahoo UI Charts Control ProtoChart Dojo Charting EJSChart fgCharting
Supported Chart Types (2)
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ZingChart
Advantage & Disadvantage
Advantage 支持图表类型丰富 进行大数据量渲染是性能好 支持交互及数据钻取 提供在线可视化开发工具及统一 的JavaScript API 有Support Team Disadvantage 需付费（Single site/MultiDomain/Enterprise/SaaS/OEM）
− 仅IE支持 (5.0以上)
Canvas
− HTML5的一部分， 提供了通过 JavaScript 绘制图形的方法； − Firefox, Safari, Opera, Chrome支持，IE9之前的版本不支持
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ZingChart
Features
1. More than a Dozen Chart Types 支持大量图表 类型 2. Handles Massive Data Sets (10000 points and more) 支持大数据量的显示 3. Fly thru Chart Data with Zooming, Scrolling and Filtering 支持缩放，滚动及过滤 4. Build Interactive and Drillable Graphs 支持交 互及数据钻取 5. Live Data Feed Support to Update Charts in Realtime 实时动态的更新图表
Jscharts
缺点
− 仅能提供 Pie, bar & line，不支持其他图类 − 无交互性
− 生成图表为PNG图片
− 无中文支持
− 数字、英文、常规字符 − 有非官方解决方案。
− 免费非开源，商用须付费
− 39$-169$ − 免费版有水印
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8 • © 2011 Lenovo Confidential. All rights reserved.
ZingChart
Features
6. HTML5 Canvas Charts 支持HTML5 Canvas渲 染方式 7. JSON 基于JSON格式的数据创建图表 8. Update Graphs with Ajax 支持AJAX的方式更 新图表 9. Control Charts with Full JavaScript API
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Canvas
Canvas Canvas Canvas Canvas Canvas Canvas Canvas Canvas Canvas Canvas
Prototype
D3 JavaScript JavaScript Prototype jQuery jQuery Raphaël jQuery jQuery jQuery
ZingChart
Overview
ZingChart is a charting library that renders a wide array of charts and graphs in both Flash and HTML5 Canvas. Website:
− − /home
常用的一些JavaScript框架
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常用的一些JavaScript框架
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主要Charts Library介绍
/forum.php?mod=viewthre ad&tid=3167&extra= /thread-1036-1-1.html
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canvasXpress