coursera data visualization

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Visualization of image data under Python folder

Python folders like data visualization Import Matplotlib.pyplot as Plt Import Matplotlib.image as Mpimg Import NumPy as NP Import Urllib2 Import Urllib Import OS Import Shutil Subdir= "/7" Homedir = OS.GETCWD () + subdir # "/home/haoyou/dev/last_caffe_with_stn/myprojects/spn-mnistcluttered/mnist-cluttered/" +subdir Import OS def walk_dir (dir,fileinfo,topdown=true): For

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

Echarts, PHP, MySQL, Ajax, JQuery enable front-end data visualization

varMyChart = Echarts.init (document.getElementById ("Container"));//To set up related items, that is, the so-called lap skeleton, easy to wait Ajax asynchronous data filling varoption = {title: {text:' name Age Distribution chart '}, tooltip: {show:true}, Legend: {data: [' age ']}, Xaxis: [{data:names}], YAxis: [{ Type:' value '}], series: [{"Name":"Age","Type":"Bar","

"Data analysis using Python" reading notes--eighth chapter drawing and visualization

the internal relationship of data. The interactive GUI is a good choice for interactive support.MayaviThis is a 3D graphics toolkit based on the open source C + + graphics library VTK. can be integrated into Ipython for interactive use.Other librariesOther libraries or applications include: PYQWT, Veusz, Gnuplotpy, Biggles, and so on, and large libraries are developing to web-based technologies and moving away from desktop graphics technology.The fut

R Basics-Fast discovery Data (R visualization)

addition:warning message:' Stat ' is deprecated> Qplot (mtcars$cyl)> Qplot (Factor (mtcars$cyl))> Ggplot (Bod,aes (Time,demand)) +geom_bar (stat = ' identity ')> Ggplot (Bod,aes (X=factor (time), Y=demand) +geom_bar (stat= "Identity")>Https://www.cnblogs.com/lizhilei-123/p/6722116.htmlGgplot2 's fast-drawing qplot ()----color. Transparency, shapeFrequency Number Bar chart:> Library (GGPLOT2)> Ggplot (Mtcars,aes (X=factor (cyl)) +geom_bar ()Equivalent:> Qplot (Factor (cyl),

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

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

Three-dimensional visualization of noun interpretation-volume rendering, voxel, body data, volume rendering algorithm

an unknown chemical composition of the gel, you use this concrete to build a block brick, if there is a three-dimensional array , will brick X, Y, The distribution of the material in the c12>z direction is expressed, then the array can be called the body data. The so-called polygon data , not the two-dimensional plane data, but that the

Python Project---data visualization (02)

actually executes the imported module once, as follows:First look at the module being called test.py :def haha(): print("哈哈")haha()Look at the main program again main.py :import testprint("一条鱼")The execution results are:哈哈一条鱼How can you simply invoke the code without executing the called module? To be called module code is not executed, the premise is to know __name__ what the variable means, in short, if not involved in the module import, __name__ The value is " __main__ ", if the module is

Interactive data visualization with R language

, and many other functions in an HTML page. Installed via Install.packages ("DT").In Iris Data set iris, for example, execute the following code:Library (DT) DataTable (Iris)The NetworkD3 package implements the D3 JavaScript Network Diagram, which is installed through Install.packages ("networkD3").Here is an example of drawing a force-directed network diagram.# Mislinks data (misnodes) # draw forcenetwork

"D3.js Data Visualization Combat"--(3) Drawing of Sankitu (Sankey)

the drag event listener.//Draw Rectangle nodeNodes.append ("Rect"). attr ({x: function (d) { returnd.x; }, Y: function (d) { returnD.y; }, Height: function (d) { returnD.dy; }, Width:sankey.nodeWidth (), fill:"Tomato"}). Call (D3.behavior.drag (). Origin ( function(d) { returnD }). On ("Drag", DragMove));This .origin(function(d) { return d; }) is to prevent jumps when dragging, the corresponding drag event listener is:// 拖动事件响应函数function dragmove(d) { d3.select(this).attr({ "x"Math.m

CSDN open-source summer camp Baidu data visualization practices ECharts (4), csdnecharts

CSDN open-source summer camp Baidu data visualization practices ECharts (4), csdnechartsECharts knowledge point summary: During the application process, you will always encounter some difficult concepts and attributes. Here we will summarize some difficult knowledge points to facilitate understanding of the concept and better grasp ECharts. (1) 1. What does a complete option contain? What types can be summa

The use of Python data visualization matplotlib

(true, Which= ' Major ') #x坐标轴的网格使用主刻度ax. Yaxis.grid (true,which= ' major ') #x坐标轴的网格使用主刻度plt. Xlabel (' time/t ', Fontsize= ' Xx-large ') #Valid fontsizearelarge,none,medium,smaller, small,x-large,xx-small,larger,x-small,xx-largeplt.ylabel (' Y-label ', Fontsize= ' Xx-large ') plt.title (' title ', fontsize= ' Xx-large ') Plt.xlim (0,110) Plt.ylim (0,1) line1, =ax.plot (x,y, ' g.-', label= "category One",) Line2,=ax.plot (x,y2, ' b*-', label= "category II",) Line3, =ax.plot (x,y3, ' rd-', la

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

CSDN open-source summer camp Baidu data visualization practices ECharts (8), csdnecharts(1) Preface First of all, I would like to thank Mr. Lin Feng for continuing with the content mentioned in Article 7. The CSS layout is indeed very tired and I feel like I am not able to adjust it. I will not talk much about it. Today, I will explain the content of a page. I will introduce the CSS layout in detail later.I

AngularJS for data visualization

AngularJS for data visualization Preview We will study how to use AngularJS to visualize data such as bar charts and line charts. Shows the effect.You can go to codepen-Online Preview-download favorites-Effect VcD4KPGgyIGlkPQ = "analysis"> Analysis To implement this case, you must have the following elements:AngularJS basics ng-repeat svg draw line passion

plotly (online visualization data production)

Plugin Introduction:Compared with traditional text charts, visual data can help users to analyze data more conveniently, and can be viewed, processed, developed and applied more intuitively. Plotly is a tool for making visual data online, providing you with services such as charting and analysis, supporting any format, such as Excle spreadsheets, TSV, Matlab, CSV

Visualization 2: STL data display

, normal + 1, normal + 2 ); Glnormal3fv (normal ); } If (strhead = "outer ") { Fscanf (FP, "% s \ n", strline. getbuffer (20 )); Glbegin (gl_polygon ); For (INT I = 0; I { Fscanf (FP, "% s \ n", strline. getbuffer (20 )); Strline. trimleft (); If (strline = "vertex ") { Fscanf (FP, "% F \ n", vertex, vertex + 1, vertex + 2 ); Glvertex3d (vertex [0], vertex [1], vertex [2]); } } Glend (); Continue; } Else if (strhead = "endloop" | strhead = "endfacet ") { Continue; } Else if (strhead = "endso

Python Advanced Data Visualization Dash2

': ' Spring air ', ' value ': ' 601021 '},], value= ' 600933 '), DCC. Graph (id= ' my-graph ')]) @app. Callback (Output (' my-graph ', ' figure '), [Input (' My-dropdown ', ' value ')] def update_graph (selected_dropdown_value): # df = web. DataReader (# selected_dropdown_value, data_source= ' Yahoo ', # START=DT (2018, 1, 1), End=dt.now () #) d f = Ts.get_k_data (Selected_dropdown_value, ktype= ' 30') return {' data ': [{' X ': Df.index, ' y ':d f.c

[D3.js data visualization practices] -- (1) Draw gridlines and d3.js Grids

[D3.js data visualization practices] -- (1) Draw gridlines and d3.js Grids We often use regular charts (histograms, line charts, and so on) to present data. To clearly indicate which value range of the data on the number axis, the value is directly indicated in the rectangle and point. In addition to this method, you c

Visualization of metricgraphics.js– time series data

Metricsgraphics.js is based on D3 and is optimized for visualization and layout of time series data. It provides a simple way to produce common types of graphs in a principled, consistent and responsive manner. The library currently supports line charts, scatter plots and histograms, as well as carpet plots and basic linear regression functions.Online Demo Source Download Related articles that may be of int

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