python - create heatmap2d from txt file

Question

I have set of 2d data (30K) as txt file.

  X       Y
2.50    135.89
2.50    135.06
2.50    110.85
2.50    140.92
2.50    157.53
2.50    114.61
2.50    119.53
2.50    154.14
2.50    136.48
2.51    176.85
2.51    147.19
2.51    115.59
2.51    144.57
2.51    148.34
2.51    136.73
2.51    118.89
2.51    145.73
2.51    131.43
2.51    118.17
2.51    149.68
2.51    132.33

I plotted as a scatter plot with gnuplot but I would like to represent as a heatmap2d or density distribution. I looked through the examples in MatPlotLib or R and they all seem to already start with random data to generate the image.

I tried those code and get error like this

hist, edges = histogramdd([x,y], bins, range, normed, weights)

AttributeError: The dimension of bins must be equal to the dimension of the sample x. Script terminated.

Is there any methods to open txt file and plot this data in gnuplot, matplotlib. my scatter plot look like this

i want to show this picture as contour map or density map with color code bar. my x-axis at range of 2.5-3.5 and y axis at range of 110-180 i have 30k data points

Answer 1

If you're willing to do everything in Python, you can compute the histogram and build a contour plot in one script :

import numpy as np
import matplotlib.pyplot as plt

# load the data
M = np.loadtxt('datafile.dat', skiprows=1)

# compute 2d histogram
bins_x = 100
bins_y = 100
H, xedges, yedges = np.histogram2d(M[:,0], M[:,1], [bins_x, bins_y])

# xedges and yedges are each length 101 -- here we average
# the left and right edges of each bin
X, Y = np.meshgrid((xedges[1:] + xedges[:-1]) / 2,
                   (yedges[1:] + yedges[:-1]) / 2)

# make the plot, using a "jet" colormap for colors
plt.contourf(X, Y, H, cmap='jet')

plt.show()  # or plt.savefig('contours.pdf')

I just made up some test data composed of 2 Gaussians and got this result :