It’s not clear if you want discrete colors or if the colors you list are just markers along the range of Y. I’ll show both. For discrete colors, use Y1 as joran defines it dat$Y1 <- cut(dat$Y,breaks = c(-Inf,-3:3,Inf),right = FALSE) Then you can get a plot with the specific colors you list using a … Read more
For people looking at this today, I would recommend the Seaborn heatmap() as documented here. The example above would be done as follows: import numpy as np from pandas import DataFrame import seaborn as sns %matplotlib inline Index= [‘aaa’, ‘bbb’, ‘ccc’, ‘ddd’, ‘eee’] Cols = [‘A’, ‘B’, ‘C’, ‘D’] df = DataFrame(abs(np.random.randn(5, 4)), index=Index, columns=Cols) … Read more
This is late, but here is my python implementation of the flowingdata NBA heatmap. updated:1/4/2014: thanks everyone # -*- coding: utf-8 -*- # <nbformat>3.0</nbformat> # ———————————————————————— # Filename : heatmap.py # Date : 2013-04-19 # Updated : 2014-01-04 # Author : @LotzJoe >> Joe Lotz # Description: My attempt at reproducing the FlowingData graphic in … Read more
If you don’t want hexagons, you can use numpy’s histogram2d function: import numpy as np import numpy.random import matplotlib.pyplot as plt # Generate some test data x = np.random.randn(8873) y = np.random.randn(8873) heatmap, xedges, yedges = np.histogram2d(x, y, bins=50) extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]] plt.clf() plt.imshow(heatmap.T, extent=extent, origin=’lower’) plt.show() This makes a 50×50 heatmap. … Read more