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, where you can design the main body of the new analysis.650) this.width=650; "src=" http://pic.pc6.com/up/2015-1/14224140158935530.jpg "style=" border:0px; "alt=" 14224140158935530.jpg "/>Here, the data source and the new data analysis are done, and the next step is to do a detailed analysis of the data, such as documentation examples.Gender dimension analysis b
= Rev (levels (Uspopage$agegroup)))Operation Result:If you need to draw a percentage stacked chart, simply modify the underlying data based on the work above.The R language implementation code is as follows:# Convert data to percent format Uspopage_prop = ddply (Uspopage, "year", transform, Percent = Thousands/sum (Thousands) * 100) # base function Ggplot (USP Opage_prop, AES (x = year, y = Percent, fill =
method is simple to add the marginal carpet function on the basis of the original scatter plot function. The R language implementation code is as follows:# base function Ggplot (Faithful, AES (x = eruptions, y = waiting)) + # Scatter graph function geom_point () + # Marginal carpet function Geom_rug () Operation Result:add a label to a scatter plotThis example uses the following test data set:The method of adding labels to scatter plots is als
! Hoststate::up hoststatetype::hard Servicestate::ok servicestatetype::hard graphiteprefix::jenkins GRAPHITEPO Stfix::swap metrictype::$_servicemetrictype$When you see the above configuration file, there is a question: Why do you want to change the file to this format? The reason is that Nagios's data wants to be transferred to INFLUXDB and needs graphios to act as a porter, Graphios's code is written in Python, where a piece of code is designed to t
= Axes.scatter (type2_x, type2_y, s=40, c= ' green ') Type3 = Axes.scatter (type3_x, type3_y, s=50, c= ' Blue ') Plt.xlabel (the number of miles you earn per year ', Fontproperties=zhfont) Plt.ylabel (percentage of events consumed by you ' playing video games ', Fontproperties=zhfont) Axes.legend ((Type1, type2, Type3), (U ' dislike ', U ' charm General ', U ' very attractive '), loc=2, Prop=zhfont) plt.show ()The resulting scatter plot is as follows: Summary: This paper briefly introduces Matp
location information of node. This completes the same circular pop-up effect as the rubber band.In addition, the navigation bar out is also more abrupt, here also use animation, let it from left to right slowly stretched out:New Animate ({from: {x:x1, y:y1},to: {x:x2, Y:y2},delay:"point '" Bounceout ') function (value) {node.setcenterlocation (value.x, value.y);},}). Play ();The difference from the previous animation is that the point structure of {x, y} is used here, and each frame updates t
be sortable (nationality is not sorted). However, he has a limitation, that is, the data points of up to 6, otherwise cannot be identified. Therefore, the application of the occasion is limited. For example, if you have three machines with five identical parts, you can plot the amount of wear on each machine on a radar chart.7. Funnel ChartScenario: Funnel chart is suitable for process analysis of many business processes.Advantage: In site analysis,
Python development [module]: CSV file data visualization,CSV Module
1. CSV file format
To store data in a text file, the simplest way is to write data into a file as a series of comma-separated values (CSV). Such a file becomes a CSV file, as shown below:
AKDT,Max TemperatureF,Mean TemperatureF,Min TemperatureF,Max Dew
CSDN open source summer camp Baidu data visualization practices ECharts (8) problem analysis, csdnechartsECharts Problem description:
The problem is that the points on the line chart are displayed. Someone asked if they can not be displayed at the beginning. When you click or move the mouse over it, the points on the line chart are displayed?As shown in:
Analysis: if the point on the line is not displayed,
Angularjs for data visualizationPreviewWe use ANGULARJS to realize the data visualization of bar chart, line chart and so on. The effect is as shown.Everyone can go to codepen-online preview-Download Collection-effectAnalysisThe following elements are required to implement this case:
Basic knowledge of Angularjs
Ng-repeat
SVG Draw Line
Passio
the volumeImport NumPy as NPX=np.random.randint (1,100,100) (generates 100 random integers from 1 to 100)BINS=[0,10,20,30,40,50,60,70,80,90,100] (Specify the range of divisions)Plt.hist (X,bins) (the number of conforming data in this range according to the specified range)Plt.hist (x,bins,rwidth=0.7) (Make bar chart spacing)Plt.show ()To plot a scatter plot:X=np.random.randint (1,10,50) (generates random numbers)Y=np.random.randint (1,10,50)Plt.scatt
Objective
In the 3D computer room data Center visualization application, with the continuous popularization and development of video surveillance networking system, network cameras are more used in monitoring system, especially the advent of high-definition era, more speed up the development and application of network cameras.
While the number of surveillance cameras is constantly huge, in the monitoring s
"Today" data, to facilitate timely attention to the latest data, while grasping the trend of data changes.
Data visualization: Complex data, clear and present
Data
Support Chart linkageMulti-dimensional and effective analysis of data linkage of multiple graphsPrivatization deploymentLocal deployment rocket to create a dedicated data visualization platformRocket can be quickly integrated with other systemsCreate a direct link to a dashboard or panel through the rocket Publishing feature, or you can copy the generated code i
In the process of Finereport this report software, it is often necessary to use the function is data analysis. And how the complex data, collation analysis, so as to draw clear findings, it is our learning Finereport the key to this software. The following small series for everyone to share the Finereport report how to data v
Echarts, a pure JavaScript chart library, based on canvas, relies on zrender at the underlying layer. Common chart libraries for commercial products provide intuitive, vivid, interactive, And customizable data visualization charts. The innovative drag-and-drop re-computing, data view, value-range roaming and other features greatly enhance the user experience and
First set up the basic environment, assuming there is already a Python operating environment. Then need to install some common basic library, such as NumPy, scipy for numerical calculation, pandas for data analysis, Matplotlib/bokeh/seaborn for data visualization. And then on demand to load the library of data acquisit
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