## matplotlib-users

 [Matplotlib-users] Computing Simple Statistics from a Histogram From: Wayne Watson - 2009-12-01 12:33:47 ```Is there some statistics function that computes the mean, std. dev., min/max, etc. from a frequency distribution? -- Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedifiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,00, or 115 per year. -- The Science of Fear by D. Gardner Web Page: ```
 Re: [Matplotlib-users] Computing Simple Statistics from a Histogram From: John Hunter - 2009-12-01 12:48:42 ```On Tue, Dec 1, 2009 at 6:32 AM, Wayne Watson wrote: > Is there some statistics function that computes the mean, std. dev., min/max, etc. from a frequency distribution? numpy has many functions for basic descriptive statistics. If "data" is an array of your data, you can do (import numpy as np) mean: np.mean(data) median: np.median(data) standard deviation: np.std(data) min: np.min(data) max: np.max(data) In scipy.stats, there are many more (skew, kurtosis, etc...) See also, this example: http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/py4science/examples/stats_descriptives.py?view=markup&pathrev=4027 JDH ```
 Re: [Matplotlib-users] Computing Simple Statistics from a Histogram From: Wayne Watson - 2009-12-01 16:51:38 ```I do not believe that any of those calculations are based on the pdf, frequency of occurrence-histogram. This, (1, 2,2, 4, 2,5,4) and not this (1,3, 0,2,1). The latter are the frequencies of occurrence for 1,2,3,4,5. John Hunter wrote: > On Tue, Dec 1, 2009 at 6:32 AM, Wayne Watson > wrote: > >> Is there some statistics function that computes the mean, std. dev., min/max, etc. from a frequency distribution? >> > > numpy has many functions for basic descriptive statistics. If "data" > is an array of your data, you can do (import numpy as np) > > mean: np.mean(data) > median: np.median(data) > standard deviation: np.std(data) > min: np.min(data) > max: np.max(data) > > In scipy.stats, there are many more (skew, kurtosis, etc...) See > also, this example: > > > http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/py4science/examples/stats_descriptives.py?view=markup&pathrev=4027 > > JDH > > -- Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet The popular press and many authorities believe the number of pedofiles that prowl the web is 50,00. There are no figures that support this. The number of children below 18 years of age kidnapped by strangers is 1 in 600,000, or 115 per year. -- The Science of Fear by D. Gardner Web Page: ```