def plotLattice():
p.figure()
p.hold('on')
sd = np.where(I==-1) #spin down
su = np.where(I==1) #spin up
l = str(L)
p.scatter(sd[0],sd[1],color='black',title='2D Ising Model Size: '+l+'x'+l)
p.scatter(su[0],su[1],color='blue')
def pairs_plot(st1,st2,length):
adapter1 = stocks[st1][:length]
adapter2 = stocks[st2][:length]
dates =[tomilli(x) for x in adapter1['Date'][:]]
#plot the opening price of two stocks
p.figure()
p.plot(dates,adapter1['Open'][:],width=500, height=300,title=st1+' vs. '+ st2)
p.plot(dates,adapter2['Open'][:],width=500, height=300)
def plot(self,key,column=None,title=None):
'''Convenience plotting with Wakari'''
from webplot import p
p.use_doc('TR Plots')
p.figure()
data = self.data[key]
if isinstance(data,pd.core.series.TimeSeries):
dates = data.index.values.astype('datetime64[ms]').astype('int64')
fig = p.plot_dates(dates,data.values,title=title,width=500,height=300)
else:
dates = data.index.values.astype('datetime64[ms]').astype('int64')
fig = p.plot_dates(dates,data[column].values,title=title,width=500,height=300)
return fig
def plot(self, key, column=None, title=None):
'''Convenience plotting with Wakari'''
from webplot import p
p.use_doc('TR Plots')
p.figure()
data = self.data[key]
if isinstance(data, pd.core.series.TimeSeries):
dates = data.index.values.astype('datetime64[ms]').astype('int64')
fig = p.plot_dates(dates,
data.values,
title=title,
width=500,
height=300)
else:
dates = data.index.values.astype('datetime64[ms]').astype('int64')
fig = p.plot_dates(dates,
data[column].values,
title=title,
width=500,
height=300)
return fig
uefa_data = sports[sports.keys()[4]][:]
dob_months = [int(dob.split('-')[1]) for dob in uefa_data['DOB']]
mCount = Counter(dob_months)
for c in mCount:
print c, mCount[c]
months = mCount.keys()
soccer = np.array(mCount.values())
p.plot(months,soccer,width=500, height=300,title='Number of Births per Month for UEFA 2012')
#http://www.cdc.gov/nchs/data/nvsr/nvsr60/nvsr60_01_tables.pdf#I02
#birth rates per month across USA 2009
US_Total_2009 = np.array([337980,316641,347803,337272,345257,346971,368450,359554\
,361922,347625,320195,340995],dtype='float64')
p.figure()
p.plot(months,US_Total_2009,width=500, height=300,title='Totals Births per Month 2009 (USA)')
p.figure()
soccer_normed = soccer/float(soccer.max())
US_normed = US_Total_2009/float(US_Total_2009.max())+.2
p.hold('on')
p.plot(months,US_normed,width=500, height=300,color='red',title='Normalized Birthrates per Month<br/>Red: USA (2009 shifted .2), Blue: NBA')
p.plot(months,soccer_normed,color='blue')
