scatter-plot

I am trying to create a scatterplot matrix with interactive selection between geom items in individual matrix plots. This works when I am dealing with geom_points (inside ggpairs()). When a user selects points in any of the 3 bottom-left individual matrix plots, then they can see the points highlighted in the other matrix plots. Below is a simple example: library(GGally) library(ggplot2) library(plotly) dat = mtcars[,1:3] p <- ggpairs(dat) ggplotly(p) However, in my case, I am aiming to use geom_hex instead of geom_points. I am hoping to develop a way that a user can highlight a hexagon(s) in

I want to create a scatter plot matrix which will be composed by some subplots. I have extracted from a .txt file my data and created an array of shape (x,y,z,p1,p2,p3). The first three columns of the array represent the x,y,z coordinates from the original image that these data come from and the last three columns(p1, p2, p3) some other parameters. Consequently, in each row of the array the parameters p1, p2, p3 have the same coordinates(x,y,z).In the scatter plot, I want to visualize the p1 parameter against the p2, p3 parameters in a first stage. For every point I pick, I would like its (x,y

I want to have a scatter plot with colormap for edgecolors but no facecolors. When I use facecolor='None' , it does not work. import numpy as np import matplotlib.pyplot as plt N = 50 x = np.random.rand(N) y = np.random.rand(N) colors = np.random.rand(N) area = np.pi * (15 * np.random.rand(N))**2 # 0 to 15 point radii plt.scatter(x, y, s=area,c=colors,facecolors='None',cmap="gist_rainbow", alpha=0.5) plt.show() Any solution? The c argument will affect facecolor and edgecolor simultaneouly, the arguments facecolor and edgecolor are hence ignored. A solution would be not to use the c argument

I have a bunch of cross plots with two sets of data and have been looking for a matploltib way of highlighting their plotted regions with smoothed polygon outlines. At the moment i just use Adobe Illustrator and amend saved plot, but this is not ideal. Example: I'd be grateful for any pointers/links to examples. Cheers Pablo Here, you have an example. I was written the main ideas, but obviously, you could do it better. A short explanations: 1) You need to compute the convex-hull ( http://en.wikipedia.org/wiki/Convex_hull ) 2) With the hull, you could scale it to keep all your data inside. 3)