stat_1 = 'weather/gsod/2008/085750-99999-2008.op'
stat_2 = 'weather/gsod/2008/279470-99999-2008.op'
#function to
tomilli = (lambda x: int(datetime.strptime(str(x),'%Y%m%d').strftime('%s'))*1000)
adapter = weather[stat_1]
date_1 = adapter[:]['YEARMODA']
date_1 = np.array([tomilli(x) for x in adapter[:]['YEARMODA']])
temp_1 = adapter[:]['TEMP']
adapter = weather[stat_2]
date_2 = adapter[:]['YEARMODA']
date_2 = np.array([tomilli(x) for x in adapter[:]['YEARMODA']])
temp_2 = adapter[:]['TEMP']
source = p.make_source(date=date_1, temp_1=temp_1, temp_2=temp_2)
p.plot_dates('date', 'temp_1', data_source=source,width=500, height=300,title='Daily Average Temperatures STN: 085750')
p.figure()
p.plot_dates('date', 'temp_2', data_source=source,width=500, height=300,title='Daily Average Temperatures STN: 279470')
p.table(source, ['date', 'temp_1', 'temp_2'])
stat_1_1981 = 'weather/gsod/1981/085750-99999-1981.op'
adapter = weather[stat_1_1981]
temp_1_1981 = adapter[:]['TEMP']
p.figure()
p.plot_dates(date_1,temp_1,width=500, height=300,title='Daily Average Temperatures for years 2008 and 1981')
p.plot_dates(date_1,temp_1_1981,width=500, height=300)
from webplot import p
p.use_doc('webplot example')
import numpy as np
import datetime
import time
x = np.arange(100) / 6.0
y = np.sin(x)
z = np.cos(x)
data_source = p.make_source(idx=range(100), x=x, y=y, z=z)
p.plot(x, y, 'orange')
p.figure()
p.plot('x', 'y', color='blue', data_source=data_source, title='sincos')
p.plot('x', 'z', color='green')
p.figure()
p.plot('x', 'y', data_source=data_source)
p.figure()
p.plot('x', 'z', data_source=data_source)
p.figure()
p.table(data_source, ['x', 'y', 'z'])
p.scatter('x', 'y', data_source=data_source)
p.figure()
p.scatter('x', 'z', data_source=data_source)
p.figure()
p.hold(False)
p.scatter('x', 'y', 'orange', data_source=data_source)
p.scatter('x', 'z', 'red', data_source=data_source)
p.plot('x', 'z', 'yellow', data_source=data_source)
p.plot('x', 'y', 'black', data_source=data_source)
print "click on the plots tab to see results"
