Plotting boxplot in matplotlib with without data array?
Question: Is there a way to create plots in **matplotlib** without having raw data?

I have a tool which reports `Mean`, `Max`, `Min`, `standard_daviation`,
`P_50`, `P_90`, and `P_99`, but does not give all the data-points. I am trying
to create a plot boxplot like plot which will convey most of above properties.
But I haven't found any way to generate such a plot in matplotlib without
having all the data points. Is there any way that I can generate such a plot
in matplotlib.

I have preference for matplotlib as most of the infrastructure is in Python
and I am already using matplotlib for some other parts.


Answer: It depends on what
[distribution](http://docs.scipy.org/doc/numpy/reference/routines.random.html#distributions)
you want - you can plot some of these like so:

    
    
    import numpy as np
    loc, scale = 0., 1 # like mean and s.d.
    x=np.arange(-8., 8., .01)
    laplace = np.exp(-abs(x-loc/scale))/(2.*scale)
    gumbel = (1/scale)*np.exp(-(x - scale)/scale)* np.exp( -np.exp( -(x - scale) /scale) )
    logistic = np.exp((loc-x)/scale)/(scale*(1+np.exp((loc-x)/scale))**2)
    normal = 1/(scale * np.sqrt(2 * np.pi))*np.exp( - (x - loc)**2 / (2 * scale**2) )
    lognormal = (np.exp(-(np.log(x) - loc)**2 / (2 * scale**2))/ (x * scale * np.sqrt(2 * np.pi)))
    rayleigh = (x/(scale*scale))*(np.exp((-x*x)/(2*scale*scale)))
    standard_cauchy = 1/(np.pi*(1+(x*x)))
    
    
    plt.plot(x,gumbel,label='gumbel scale=1')
    plt.plot(x,laplace,label='laplace scale=1, loc = 0')
    plt.plot(x,normal,label='normal scale=1, loc = 0')
    plt.plot(x,logistic,label='logistic scale=1, loc = 0')
    plt.plot(x,lognormal,label='lognormal scale=1, loc = 0')
    plt.plot(x,rayleigh,label='rayleigh scale=1')
    plt.plot(x,standard_cauchy,label='standard_cauchy')
    

![enter image description here](http://i.stack.imgur.com/LJBj0.png)

