本文作者星河里的章鱼喵，文章通过介绍Visualization即可视化，罗列了数据的展现方式。
对于数据分析最困难的一部分就是数据的展示，解读数据之间的关系，清晰有效的传达并且沟通数据信息。
对于数据挖掘，我们可以通过文中对数据可视化的案例找到分析数据、展现数据的方法和思路。
Datavisualization是一件很有趣的事情。
最近在尝试处理数据，便顺手翻了翻visualization的进展，然后除了IBM大名鼎鼎的的many-eyes。
还有一个比较好有意思的网站是visualizing。
Visualizing跟many-eyes很像，都是社区形式的网站，用户可以注册然后上传，而且网站还有积累下来

System.Windows.Forms.DataVisualization.dll3.5版本

实现一个界面。
界面上具有两个两个按钮，一个“导入”，一个“导出”，界面上还有一个类似dataview的数据显示控件

本资源为ScottMurray的InteractiveDataVisualizationfortheWeb一书中的源代码示例，包含大量D3.js的代码，适合D3的学习者。

TheJupyterNotebookallowsyoutocreateandsharedocumentsthatcontainlivecode,equations,visualizations,andexplanatorytext.TheJupyterNotebooksystemisextensivelyusedindomainssuchasdatacleaningandtransformation,numericalsimulation,statisticalmodeling,andmachinelearning.LearningJupyter5willhelpyougettogripswithinteractivecomputingusingreal-worldexamples.ThebookstartswithadetailedoverviewoftheJupyterNotebooksystemanditsinstallationindifferentenvironments.Next,youwilllearntointegratetheJupytersystemwithdifferentprogramminglanguagessuchasR,Python,Java,JavaScript,andJulia,andexplorevariousversionsandpackagesthatarecompatiblewiththeNotebooksystem.Movingahead,youwillmasterinteractivewidgetsandnamespacesandworkwithJupyterinamulti-usermode.Bytheendofthisbook,youwillhaveusedJupyterwithabigdatasetandbeabletoapplyallthefunctionalitiesyou’veexploredthroughoutthebook.YouwillalsohavelearnedallabouttheJupyterNotebookandbeabletostartperformingdatatransformation,numericalsimulation,anddatavisualization.

Thisneweditiontotheclassicbookbyggplot2creatorHadleyWickhamhighlightscompatibilitywithknitrandRStudio.ggplot2isadatavisualizationpackageforRthathelpsuserscreatedatagraphics,includingthosethataremulti-layered,withease.Withggplot2,it'seasyto:producehandsome,publication-qualityplotswithautomaticlegendscreatedfromtheplotspecificationsuperimposemultiplelayers(points,lines,maps,tiles,boxplots)fromdifferentdatasourceswithautomaticallyadjustedcommonscalesaddcustomizablesmoothersthatusepowerfulmodelingcapabilitiesofR,suchasloess,linearmodels,generalizedadditivemodels,androbustregressionsaveanyggplot2plot(orpartthereof)forlatermodificationorreusecreatecustomthemesthatcapturein-houseorjournalstylerequirementsandthatcaneasilybeappliedtomultipleplotsapproachagraphfromavisualperspective,thinkingabouthoweachcomponentofthedataisrepresentedonthefinalplotThisbookwillbeusefultoeveryonewhohasstruggledwithdisplayingdatainaninformativeandattractiveway.SomebasicknowledgeofRisnecessary(e.g.,importingdataintoR).ggplot2isamini-languagespecificallytailoredforproducinggraphics,andyou'lllearneverythingyouneedinthebook.Afterreadingthisbookyou'llbeabletoproducegraphicscustomizedpreciselyforyourproblems,andyou'llfinditeasytogetgraphicsoutofyourheadandontothescreenorpage.TableofContentsPartIGettingStartedChapter1IntroductionChapter2GettingStartedwithggplot2Chapter3ToolboxPartIITheGrammarChapter4MasteringtheGrammarChapter5BuildaPlotLayerbyLayerChapter6Scales,AxesandLegendsChapter7PositioningChapter8ThemesPartIIIDataAnalysisChapter9DataAnalysisChapter10DataTransformationChapter11ModellingforVisualisationChapter12Programmingwithggplot2

2017年的新书呀，D34.x以及ES2017!!2017年的新书呀，D34.x以及ES2017!!

Datavisualizationisoneofthemostimportantpartofdatascience.Manybooksandcoursespresentacatalogueofgraphicsbuttheydon'tteachyouwhichchartstouseaccordingtothetypeofthedata.Inthisbook,westartbypresentingthekeygraphicsystemsandpackagesavailableinR,includingRbasegraphs,latticeandggplot2plottingsystems.Next,weprovidemorethan200practicalexamplestocreategreatgraphicsfortherightdatausingeithertheggplot2packageandextensionsorthetraditionalRgraphics.Withthisbook,you'lllearn:-Howtoquicklycreatebeautifulgraphicsusingggplot2packages-Howtoproperlycustomizeandannotatetheplots-Typeofgraphicsforvisualizingcategoricalandcontinuousvariables-Howtoaddautomaticallyp-valuestoboxplots,barplotsandalternatives-Howtoaddmarginaldensityplotsandcorrelationcoefficientstoscatterplots-Keymethodsforanalyzingandvisualizingmultivariatedata-Rfunctionsandpackagesforplottingtimeseriesdata-Howtocombinemultipleplotsononepagetocreateproduction-qualityfigures.

Chapter1providesin-depthinformationabouthowneuralnetworksfunction,wheretogetdatafrom,andhowtopreprocessthatdatatomakeiteasiertoconsume.Chapter2isaboutgettingstuckandwhattodoaboutit.Neuralnetsarenotoriouslyhardtodebugandthetipsandtricksinthischapteronhowtomakethembehavewillcomeinhandywhengoingthroughthemoreproject-orientedrecipesintherestofthebook.Ifyouareimpatient,youcanskipthischapterandgobacktoitlaterwhenyoudogetstuck.Chapters3through15aregroupedaroundmedia,startingwithtextrocessing,followedbyimageprocessing,andfinallymusicprocessinginChapter15.Eachchapterdescribesoneprojectsplitintovariousrecipes.Typicallyachapterwillstartwithadataacquisitionrecipe,followedbyafewrecipesthatbuildtowardthegoalofthechapterandarecipeondatavisualization.Chapter16isaboutusingmodelsinproduction.Runningexperimentsinnotebooksisgreat,butultimatelywewanttoshareourresultswithactualusersandgetourmodelsrunonrealserversormobiledevices.Thischaptergoesthroughtheoptions.

世界国家geojson大全各国地图json数据[带例子].zip另附上在线生成地图json数据链接：http://datav.aliyun.com/tools/atlas/#&lat=30.35828173619863&lng=106.7222742206687&zoom=3.5

在日常工作中，钉钉打卡成了我生活中不可或缺的一部分。然而，有时候这个看似简单的任务却给我带来了不少烦恼。 每天早晚，我总是得牢记打开钉钉应用，点击"工作台"，再找到"考勤打卡"进行签到。有时候因为工作忙碌，会忘记打卡，导致考勤异常，影响当月的工作评价。而且，由于我使用的是苹果手机，有时候系统更新后，钉钉的某些功能会出现异常，使得打卡变得更加麻烦。 另外，我的家人使用的是安卓手机，他们也经常抱怨钉钉打卡的繁琐。尤其是对于那些不太熟悉手机操作的长辈来说，每次打卡都是一次挑战。他们总是担心自己会操作失误，导致打卡失败。 为了解决这些烦恼，我开始思考是否可以通过编写一个全自动化脚本来实现钉钉打卡。经过一段时间的摸索和学习，我终于成功编写出了一个适用于苹果和安卓系统的钉钉打卡脚本。