scatter-plot

问题 In using the function scatterplot3d() from the scatterplot3d package, grid=TRUE only plots the grid for XY-plane. A look at the function source code has only X and Y components. I want to draw the grid for YZ- and XZ- planes as well, as below in the picture: I have searched the images for examples of R scatterplot3d images with these grids to no avail. I thought about s3d$plane3d but the planes that were generated look very messy. I have not have experience editing codes or writing function

问题 we are building our reports on matplotlib. Each page has multiple charts and some text. In the report data there is over 100 locations, each location has a density. The idea is to plot the points on a map where the color (shade of red) represents the density of the location. However, I do not understand the connection between the kwargs : c and cmap in the ax.scatter call, nor do I understand the role of color.Normalize in this application. import pandas as pd import matplotlib import numpy

问题 I am looking for a Scatter Plot 3D component for a Web application. Right now I am using JMathPlot (inside a Java Applet) to produce something like this: alt text http://jmathtools.berlios.de/lib/exe/fetch.php?media=scatterplot3d.png JMathPlot is fine, but is missing some required functionality (I am especially interested in having tooltips for the plot points). Are there any alternatives? Any interactive web technology (javascript, java applet, flash, silverlight) is fine. The user should be

问题 I have a data set with 9 columns. 7 features are used for feature selection and one of them for the classification. I used tsne library for feature selection in order to see how much my data could be classified.The result from tsne is shown in picture. However, I want to visualize my data in another way. I would like to set a color for each observation based on the column f1 (id). for example : f1(id) f2 f3 ... f9(class label) 1 66 77 ... A 1 44 88 ... A 2 33 55 ... B 2 77 88 .. B colors come

问题 How can I position the value points directly above the ticks (or the ticks directly under the points), using DC.js. I could not manage that, DC.js (or D3.js) positions the value points shifted to the left of the ticks, although the X-value is exactly the tick value. Important: I need this feature for ordinal X axis (it works fine for linear X axis)! var data = [ {"x":"a","y":1}, {"x":"b","y":2}, {"x":"c","y":3} ]; ... dc.scatterPlot("#mychart") .dimension(dimension) .group(group) .x(d3.scale

问题 I am using plotly 4.5.2 in R. I have created a scatterplot which is sized on a variable, the issue is these sizes are also reflected in the legend which makes them hard to read. I want my graph to remain the same, with the only exception being the size of the bubbles in the legend. These bubbles can either be set to all be the same size or scaled to a smaller size. Importantly, the sizes in the graph must remain the same. Please find reproducible code here: library(plotly) data <- data.frame

问题 I would like to make my scatterplot circles shaded according to the value in one column. "value"; "avg.sal"; "avg.temp" 2,5698; 34,27254; 4,44 5,4361; 34,30686; 4,64 2,27; 34,3538; 8,05 5,6015; 34,50136; 5,01 2,27; 34,37596; 7,4 I have my plot ready with salinity on the y-axis and temperature on the x-axis. plot(df$avg.sal, df$avg.temp) How do I shade the circles (e.g. from light blue to dark blue) according to the column "value"? The values have a big range but smaller values (e.g. 2) should

问题 I have XY data (a 2D tSNE embedding of high dimensional data) which I'd like to scatter plot . The data are assigned to several cluster s, so I'd like to color code the points by cluster and then add a single label for each cluster , that has the same color coding as the cluster s, and is located outside (as much as possible) from the cluster 's points. Any idea how to do this using R in either ggplot2 and ggrepel or plotly ? Here's the example data (the XY coordinates and cluster assignments

问题 I'm writing a program in C++ that acquires 4 dimensional points data over a UDP socket and then plots the data in 6 separate 2D scatter plots. For example if we name the dimensions: A,B,C,D the six 2d plots would be AxB, AxC, AxD, BxC, BxD, and CxD. Over the course of a few hours the program accrues ~50K points. Currently I plot each point once, using immediate mode. I don't clear the buffer between draw calls so previously plotted points persist until the buffer is cleared. I'm not happy

问题 I am plotting timeseries data using Matplotlib and some of the data is missing in the sequence. Matplotlib implicitly joins the last contiguous data point to the next one. But in case data is missing, the plot looks ugly. The following is the plot obtained. It can be seen that near the April 30th marker, data is missing and Matplotlib joins the points. Also the following image is the scatter plot of the data. Scatter plot covers up this fault, but then contiguous data points won't be joint in