I'm plotting some histograms with hist() --- well, actually with ax.hist(), where ax is an axis --- and the "normed=1" isn't working the way I would expect.

from pylab import *

data = sin(arange(0.0,100,.01))

fig = figure()

ax = fig.add_subplot(111)

ax.hist(data,bins=50,normed=1,align='center')

show()

If I do not include normed=1, then the Y scale is an actual count inside each bin. (The scale goes from 1-1000).

If I include normed=1, the Y scale goes from 1 - 7. What does that mean? normed is supposed to make the first result from ax.hist be a normalized probability distribution. But I would think that it would change the Y axis to be a probability as well, and it doesn't do that.

The docstrings do not give any insight, so I looked at the source code. It certainly *looks* like it's plotting the probability distribution. But why does the above example give a Y scale going from 1 to 7? Perhaps I'm showing my lack of statistics here, but I would think that a strict probability distribution would have the value of all of the bars adding to 1,

Sorry to send out so many messages today. I really am trying to figure this out on my own...