In [4]:

    

from pandas import DataFrame
import itertools
import numpy as np
from pymatgen.util.plotting_utils import get_publication_quality_plot
%matplotlib inline


    

In [5]:

    

d = np.array(list(itertools.product(range(1, 5), range(1, 5))))


    

In [6]:

    

data = DataFrame({"X": d[:, 0], "Y": d[:, 1]})
data["Average"] = data.mean(axis=1)


    

In [7]:

    

plt = get_publication_quality_plot(12, 8)
print plt.hist(data["Average"], color='k', bins=np.arange(0.75, 4.5, 0.5), width=0.05, normed=True)
plt.xticks(np.arange(0.75, 4.5, 0.5), np.arange(0.75, 4.5, 0.5)  + 0.25)
plt.xlabel("Sample Mean")
plt.ylabel("Probability")


    

    




(array([ 0.125,  0.25 ,  0.375,  0.5  ,  0.375,  0.25 ,  0.125]), array([ 0.75,  1.25,  1.75,  2.25,  2.75,  3.25,  3.75,  4.25]), <a list of 7 Patch objects>)






    
Out[7]:





<matplotlib.text.Text at 0x10c636790>






    

In [8]:

    

data = [105, 97, 245, 163, 207, 134, 218, 199, 160, 196]


    

In [15]:

    

avg = np.average(data)
stddev = 34 / np.sqrt(10)
a = 2.58
interval = (avg - stddev * a, avg + stddev * a)
print interval


    

    




(144.66050036500297, 200.13949963499704)

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