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I am trying to understand what are the values of a 2D histogram.

I have 2 numpy arrays of the same length X and Y (float numbers in each one).

For example the first 10 values of X: [ 88, 193, 60, 98, 78, 100, 75, 76, 130]

and Y: [ 18. , 9. , 36.1, 18.5, 34.3, 32.9, 32.2, 22. , 15. ]

When I use:

import matplotlib.pyplot as plt

plt.hist2d(X,Y, bins=(10,20))

I get a 2D histogram.

But what does it mean?

1D histogram simply shows me how much of each item I have.

Please explain me what does it mean in 2D.

Thanks in advance!

Steve
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1 Answers1

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Suppose you have a 1D array, you plot the position of its values on the x axis, they are so dense that you can't tell the spatial distribution, you use a 1D histogram to show the distribution by count of boxes along the x axis. Problem solved.

Then you have two 1D arrays, a list of 2D dots in (x, y) axes. You plot their positions on the x-y plane, again they are so dense and overlap with each other. You want to view the distribution better by count of boxes in the plane, so you try a 2D diagram. Problem solved.

Here is an example

import numpy as np
import matplotlib.pyplot as plt

%matplotlib inline

# prepare 2D random dots centered at (0, 0)
n = 100000
x = np.random.randn(n)
y = x + np.random.randn(n)

# plot data
fig1 = plt.figure()
plt.plot(x,y,'.r')
plt.xlabel('x')
plt.ylabel('y')

gives

enter image description here

# plot 2D histogram using pcolor
fig2 = plt.figure()
plt.hist2d(x, y, bins=100)
plt.xlabel('x')
plt.ylabel('y')
cbar = plt.colorbar()
cbar.ax.set_ylabel('Counts')

gives

enter image description here

notArefill
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Neo X
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  • Hi Neo, thanks for the answer - so you mean that 2D histogram with the bins map just tell me how much points are in each 2D bin? For example if I see a bin in the middle of the 2D histogram it's value is the count of points that are in this bin range? – Steve Feb 16 '17 at 00:47
  • Exactly, as in my updated answer, the counts of the little boxes in second figure are colored in a heatmap style. Hope it helps. – Neo X Feb 16 '17 at 00:49
  • My pleasure too : ) – Neo X Feb 16 '17 at 00:58