I am looking to draw a two dimensional normal distribution using numpy given the mean and the standard deviation of 30. I am relatively new to numpy. I have read the numpy.random.multivariate_normal function but dont have a clarity on what the covariance matrix represents and how to represent the standard deviation.
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Possible duplicate of [python pylab plot normal distribution](http://stackoverflow.com/questions/10138085/python-pylab-plot-normal-distribution) – Aug 18 '16 at 20:35
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By 2d do you mean you want to plot two normal distributions on the same plot? Or a multivariable Guassian dist? A covariance matrix simply represents the covariance between each element in the row vs the column. Here are some good docs on `multivariable_normal` http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.multivariate_normal.html – Adam Aug 18 '16 at 20:51
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I am given a two dimensional array (340, 340). The mean of the distribution is (170, 170) and the standard deviation is 30. I have no clue as to how to create the covariance matrix and the visualize the curve. – user3473213 Aug 18 '16 at 20:59