datacamp data visualization

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Finereport data visualization analysis of graphic and graphical steps

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

Application of data visualization design in PPT

The display of chart data is the most commonly used function in PPT design. For the audience to quickly understand the content of the PPT data, we need to the PPT chart data for visual design processing. Today brings you to the Visage data Visualization Design Guide, we can

Finereport report How to perform data visualization analysis

, 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

The use of "Python data visualization" Pyecharts __python

Echarts Baidu is very famous also very diao.Echarts is Baidu Open source of a data visualization JS library. Mainly used for data visualization.Pyecharts is a class library that is used to generate echarts charts. is actually the butt of echarts and Python. Url:Https://github.com/chenjiandongx/pyecharts/blob/master/docs/zh-cn/documentation.md#%E5%BC%80%E5%A7%8B%E

Fourth: R language Data visualization line chart, stacked map, stacked area chart

= 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 =

Fifth: Scatter plot of the R language data visualization

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

Nagios+influxdb+grafana Monitoring Data visualization process

! 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

Python Data visualization-Create a scatter plot using matplotlib

= 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

Tensorboard Visualization in Ubuntu environment does not show data problems no scalar data was found ... (the author's pro-Test is effective) (turn)

Tensorboard:tensorflow comes with a visual tool. The chart visualization with Tensorboard encountered a problem that the chart does not display.Environment: Ubuntu systemRun the code to get the TensorFlow event file logs, for example the path is:/home/wang/tensorflow/logs, logs also contains train and test. At this point, Tensorboard runs by reading the event file by typing the command in cmd: tensorboard--logdir=log file path. According to our curren

Python Data visualization--matplotlib user manual Getting Started: Pyplot drawing

[0, 1].plot (data[0], data[1]) OneAxs[1, 1].HIST2D (data[0], data[1]) A -Plt.show ()5. Add Text: Axis label, property label1 ImportMatplotlib.pyplot as Plt2 ImportNumPy as NP3Mu, sigma = 100, 154x = mu + sigma * NP.RANDOM.RANDN (10000)5 6 #The histogram of the data7N, bins, patches = plt.hist (x, Normed=true, facecolo

HTML5 Big Data Visualization (i) Rainbow explosion map

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

Data visualization Diagram (ii)

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,

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

A discussion on the Pygal module of Python real-data visualization (Basic article)

die import Dieimport pygal# 实例化两个Die类对象die_1 = Die()die_2 = Die(10) # 注意这里传入10results = []for roll_num in range(50000): result = die_1.roll() + die_2.roll() results.append(result) # 将结果放入results列表frequencies = []max_result = die_1.num_sides + die_2.num_sides# 将实验的结果数据统计出每个数字出现的次数for value in range(2, max_result + 1): frequency = results.count(value) frequencies.append(frequency)# 绘制直方图# 实例化一个bar对象,对该对象的title、x_labels、x_title、y_title属性设置相当于在直方图设置。hist = pygal.Bar()hist.title = "Res

Csdn open-source summer camp Baidu data visualization practices echarts (8) Problem Analysis

),Magic_type_changed (dynamic type switching), timeline_changed (timeline change ),Data_zoom (data area scaling), data_range (value range roaming), map_roam (MAP roaming ),Legend_selected (legend selection), map_selected (MAP selection), and pie_selected (pie chart selection) The Code is as follows: Option = {tooltip: {trigger: 'item'}, Legend: {data: ['highest ', 'lowest']}, toolbox: {Show: True, f

CSDN open source summer camp Baidu data visualization practices ECharts (8) problem analysis, csdnecharts

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,

Time resampling of Pandas data Visualization (iii)

Time resampling of Pandas data Visualization (iii) Python+pandas generate the specified date and resampling-CSDN blog https://blog.csdn.net/LY_ysys629/article/details/73823803 Pandas Resample Method-Csdn Blog https://blog.csdn.net/wangshuang1631/article/details/52314944 —————————————————————————————————————————————————— Time Series Conversions: C=PD. Series (Np.random.rand (5), index= (Pd.date_range

Python advanced data processing and visualization (i)

])cluster analysis based on results  numpy.vstack: https://docs.scipy.org/doc/numpy/reference/generated/numpy.vstack.html  Scipy.cluster.vq.kmeans: https://docs.scipy.org/doc/scipy/reference/generated/ Scipy.cluster.vq.kmeans.html#scipy.cluster.vq.kmeans  scipy.cluster.vq.vq: https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.vq.vq.html2. Matplotlib Drawing Basics3. Matplotlib Image Attribute Control4. Pandas drawing5. Data access6. Py

Python feature notes-data visualization

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

3D Room Data Center visualization based on HTML5 's WebGL and VR technology

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

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