In [279]:
import numpy as np
import matplotlib.pyplot as plt
import datetime
import pandas as pd
from bs4 import BeautifulSoup
from urllib2 import urlopen
import sqlite3
from functools import partial
from collections import defaultdict
import re
%matplotlib inline
In [406]:
data = pd.read_table('MGE_multifam_vacancy.txt', delimiter=' ', )
fig, axes = plt.subplots(1, 2, figsize=(7, 3.5))
ax = axes[0]
data_iter = data.iteritems()
data_iter.next()
for year, rates in data_iter:
ax.plot(range(4, 0, -1), rates, '.-', label=year)
ax.set_xlabel('Quarter')
ax.set_ylabel('Vacancy Rate [%]')
ax.get_xaxis().set_ticks(range(1, 5))
ax.legend(loc='best', ncol=2)
ax.set_ylim(0)
ax = axes[1]
years = [datetime.datetime(int(yr), 1, 1) for yr in data.columns[1:].values]
for row, row_data in data.iterrows():
ax.plot(years, row_data.values[1:], label="Q%1.0f"%row_data.values[0])
ax.set_xlabel("Year")
ax.legend(loc='best')
ax.set_ylim(0)
/usr/local/lib/python2.7/site-packages/ipykernel/__main__.py:1: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators; you can avoid this warning by specifying engine='python'.
if __name__ == '__main__':
Out[406]:
(0, 5.0)
In [176]:
date = [datetime.datetime(int(yr), int(month*3), 1) for yr in data.columns[1:].values for month in data['Quarter']]
vac_rate = data.values[:, 1:].ravel(order='F')
fig, axis = plt.subplots(1, figsize=(5, 3.5))
axis.plot(date, vac_rate, '.-')
axis.set_xlabel('Year')
axis.set_ylabel('Vacancy Rate')
axis.set_ylim(0)
Out[176]:
(0, 5.0)
In [368]:
conn = sqlite3.connect('/Users/spardy/MGE_Vacancy.db')
c = conn.cursor()
for year in xrange(2003, 2016, 1):
for quarter in xrange(1, 5):
table_name = "rv_{:d}Qtr{:d}".format(year, quarter)
c.execute("DROP TABLE if exists %s" % table_name)
c.execute("CREATE TABLE %s (Town, ZIP, Units, Vacant, Percent)" % table_name)
if year == 2015 and quarter == 4:
url = 'https://www.mge.com/customer-service/multifamily/vacancy-rates/'
else:
url = 'https://www.mge.com/customer-service/multifamily/vacancy-rates/rv_{:d}Qtr{:d}.htm'.format(year,
quarter)
page = urlopen(url)
soup = BeautifulSoup(page.read(), 'html.parser')
for row in soup.find_all("td", attrs={'class': re.compile(r".*\bhighlight\b.*")}):
column_data = ['']*5
for i, column in enumerate(row.parent.find_all("td")):
if i > 4:
break
column_data[i] = column.text
else: # no break
c.execute("INSERT INTO %s VALUES (?, ?, ?, ?, ?)" % table_name, (column_data))
conn.commit()
conn.close()
In [369]:
conn = sqlite3.connect('/Users/spardy/MGE_Vacancy.db')
c = conn.cursor()
vacancy_data = {}
for year in xrange(2003, 2016, 1):
vacancy_data[year] = {}
for quarter in xrange(1, 5):
table_name = "rv_{:d}Qtr{:d}".format(year, quarter)
data = c.execute("SELECT count(*) FROM sqlite_master WHERE name ='%s' and type='table';" % table_name).fetchall()
if data[0][0] > 0:
data = c.execute("SELECT * FROM %s" % table_name).fetchall()
else:
continue
#Trim data
data[:] = [x for x in data[:] if x[1].isdigit()]
vacancy_data[year][quarter] = data
conn.close()
In [371]:
for year, yearly_data in vacancy_data.iteritems():
for quarter, quarterly_data in yearly_data.iteritems():
date = datetime.datetime(int(year), int(quarter*3), 1)
for zip_data in quarterly_data:
if zip_data[0] == 'Madison':
plt.plot(date, zip_data[4], 'k.')
In [372]:
zip_dict = defaultdict(list)
for year, yearly_data in vacancy_data.iteritems():
for quarter, quarterly_data in yearly_data.iteritems():
date = datetime.datetime(int(year), int(quarter*3), 1)
for zip_data in quarterly_data:
#if float(zip_data[2].replace(",", "")) > 100: # eleminate small towns
zip_dict[zip_data[1]].append({date: zip_data[4]})
In [397]:
zip_dict['54645']
Out[397]:
[{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}]
In [373]:
nzips = len(zip_dict.keys())
nyears = len(vacancy_data.keys())
nquarters = 4
ndims = 3
dataset_full = np.zeros((nyears, nquarters, nzips, ndims))*np.nan
zip_axis = [k for k in zip_dict.keys()]
zip_order = {k: i for i, k in enumerate(zip_dict.keys())}
year_axis = [k for k in vacancy_data.keys()]
quarter_axis = range(1, 5)
for i, (year, yearly_data) in enumerate(vacancy_data.iteritems()):
for j, (quarter, quarterly_data) in enumerate(yearly_data.iteritems()):
for zip_data in quarterly_data:
try:
k = zip_order[zip_data[1]]
except KeyError:
continue
dataset_full[i, j, k, 0] = float(zip_data[2].replace(",", ""))
dataset_full[i, j, k, 1] = float(zip_data[2].replace(",", ""))
try:
dataset_full[i, j, k, 2] = float(zip_data[4])
except ValueError:
dataset_full[i, j, k, 2] = float(zip_data[-2])/float(zip_data[-3])
In [403]:
dataset_full[:, :, :, 0] > 10
Out[403]:
array([[[False, True, False, ..., False, True, True],
[False, True, False, ..., False, True, True],
[False, True, False, ..., False, True, True],
[False, True, False, ..., False, False, False]],
[[False, True, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],
[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],
...,
[[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False],
[False, False, False, ..., False, False, False]],
[[False, True, False, ..., False, False, False],
[False, True, False, ..., False, False, False],
[False, True, False, ..., False, False, False],
[False, True, False, ..., False, False, False]],
[[False, True, False, ..., False, False, False],
[False, True, False, ..., False, False, False],
[False, True, False, ..., False, False, False],
[False, True, False, ..., False, False, False]]], dtype=bool)
In [413]:
fig, axis = plt.subplots(1, figsize=(5, 3.5))
mask = np.ones_like(dataset_full[:, :, :, 0])*np.nan
mask[np.where(dataset_full[:, :, :, 0] > 10)] = 1
axis.plot(map(partial(datetime.datetime, month=1, day=1), year_axis),
np.nanmean(dataset_full[:, :, :, 2]*mask, axis=1), color='gray', alpha=0.75)
axis.plot(map(partial(datetime.datetime, month=1, day=1), year_axis),
np.nanmean(np.nanmean(dataset_full[:, :, :, 2]*mask, axis=1), axis=1),
color='black', linewidth=4)
print np.nanmean(dataset_full[:, :, :, 2]*mask, axis=2).ravel()
axis.set_xlabel('Year')
axis.set_ylabel('Vacancy Rate')
[ 2.9875 4.1375 4.07 4.27166667 4.3314021 5.76
5.75857143 5.88714286 5.7 6.84142857 6.38785714 5.72928571
5.19214286 6.04428571 5.65785714 5.11785714 4.76785714 5.39285714
4.70428571 4.29 4.15142857 4.035 3.20071429 3.03571429
3.12928571 4.25857143 4.73285714 3.93214286 3.955 4.90428571
3.69928571 2.77428571 2.81857143 3.37428571 2.46571429 2.07071429
1.885 3.07571429 2.60857143 2.40571429 1.75071429 2.73571429
2.88571429 2.08142857 1.95647059 3.06375 2.46125 2.090625
1.93375 2.869375 2.756875 2.08625 ]
Out[413]:
<matplotlib.text.Text at 0x111698210>
In [444]:
mask = np.ones_like(dataset_full[:, :, :, 0])*np.nan
mask[np.where(dataset_full[:, :, :, 0] > 10)] = 1
vacs = np.nanmean(dataset_full[:, :, :, 2]*mask, axis=2).ravel()
year = 2002
with file('Vacancy_Rates_avg.csv', 'w') as f:
f.write('Date,Quarter,Rate\n')
for i, vac in enumerate(vacs):
if not i%4:
year += 1
f.write("%d/%02d,%d,%3.4f\n" % (year, (i%4)*3+1, (i%4)+1, vac))
In [442]:
nzips = len(zip_dict.keys())
nyears = len(vacancy_data.keys())
nquarters = 4
ndims = 3
zip_axis = [k for k in zip_dict.keys()]
zip_order = {k: i for i, k in enumerate(zip_dict.keys())}
year_axis = [k for k in vacancy_data.keys()]
quarter_axis = range(1, 5)
with file('Vacancy_Rates.csv', 'w') as f:
f.write('Date,%s\n' % ",".join(zip_dict.keys()))
for i, (year, yearly_data) in enumerate(vacancy_data.iteritems()):
for j, (quarter, quarterly_data) in enumerate(yearly_data.iteritems()):
line = ["-1"]*(1+nzips)
line[0] = "{:d}/{:02d}".format(year, quarter*4)
for zip_data in quarterly_data:
k = zip_order[zip_data[1]]+1
if float(zip_data[2].replace(",", "")) > 20:
try:
line[k] = zip_data[4].replace("\n", "")
except ValueError:
line[k] = str(float(zip_data[-2])/float(zip_data[-3]))
f.write("%s\n" % ",".join(line))
In [401]:
query_string = """
ogr2ogr -f GeoJSON -where "NAME = '%s'" zipcode.json WI_zipcode_regions.geojson
"""
query_string = query_string % "' OR NAME = '".join(zip_dict.keys())
print query_string
ogr2ogr -f GeoJSON -where "NAME = '54645' OR NAME = '53597' OR NAME = '53582' OR NAME = '53704' OR NAME = '53705' OR NAME = '53703' OR NAME = '54648' OR NAME = '53527' OR NAME = '54670' OR NAME = '53508' OR NAME = '53562' OR NAME = '53560' OR NAME = '53507' OR NAME = '53528' OR NAME = '53529' OR NAME = '53911' OR NAME = '53955' OR NAME = '53593' OR NAME = '54631' OR NAME = '54665' OR NAME = '53503' OR NAME = '54638' OR NAME = '54655' OR NAME = '53555' OR NAME = '53590' OR NAME = '53719' OR NAME = '53718' OR NAME = '54652' OR NAME = '53715' OR NAME = '53714' OR NAME = '53717' OR NAME = '53716' OR NAME = '53711' OR NAME = '53713' OR NAME = '53558' OR NAME = '53578' OR NAME = '53517' OR NAME = '53515' OR NAME = '53532' OR NAME = '53571' OR NAME = '53572' OR NAME = '53575' OR NAME = '53826' OR NAME = '53821' OR NAME = '53726' OR NAME = '53929' OR NAME = '54626' OR NAME = '53583' OR NAME = '53598'" zipcode.json WI_zipcode_regions.geojson
In [404]:
zip_dict
Out[404]:
defaultdict(list,
{u'53503': [{datetime.datetime(2003, 3, 1, 0, 0): u' 2.08'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n6.25'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.04'}],
u'53507': [{datetime.datetime(2003, 3, 1, 0, 0): u' 25.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'53508': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'53515': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.03'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n3.03'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.85'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53517': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'53527': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53528': [{datetime.datetime(2003, 3, 1, 0, 0): u' 1.19'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n5.04'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.36'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n1.76'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n1.75'},
{datetime.datetime(2004, 6, 1, 0, 0): u'2.62'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n3.15'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n3.22'},
{datetime.datetime(2005, 3, 1, 0, 0): u'2.64'},
{datetime.datetime(2005, 6, 1, 0, 0): u'3.77'},
{datetime.datetime(2005, 9, 1, 0, 0): u'3.50'},
{datetime.datetime(2005, 12, 1, 0, 0): u'3.30'},
{datetime.datetime(2006, 3, 1, 0, 0): u'1.80'},
{datetime.datetime(2006, 6, 1, 0, 0): u'2.67'},
{datetime.datetime(2006, 9, 1, 0, 0): u'2.11'},
{datetime.datetime(2006, 12, 1, 0, 0): u'3.61'},
{datetime.datetime(2007, 3, 1, 0, 0): u'3.32'},
{datetime.datetime(2007, 6, 1, 0, 0): u'5.07'},
{datetime.datetime(2007, 9, 1, 0, 0): u'7.18'},
{datetime.datetime(2007, 12, 1, 0, 0): u'6.25'},
{datetime.datetime(2008, 3, 1, 0, 0): u'4.80'},
{datetime.datetime(2008, 6, 1, 0, 0): u'3.02'},
{datetime.datetime(2008, 9, 1, 0, 0): u'3.59'},
{datetime.datetime(2008, 12, 1, 0, 0): u'3.26'},
{datetime.datetime(2009, 3, 1, 0, 0): u'3.88'},
{datetime.datetime(2009, 6, 1, 0, 0): u'6.92'},
{datetime.datetime(2009, 9, 1, 0, 0): u'7.48'},
{datetime.datetime(2009, 12, 1, 0, 0): u'5.72'},
{datetime.datetime(2010, 3, 1, 0, 0): u'5.42'},
{datetime.datetime(2010, 6, 1, 0, 0): u'6.62'},
{datetime.datetime(2010, 9, 1, 0, 0): u'1.80'},
{datetime.datetime(2010, 12, 1, 0, 0): u'0.90'},
{datetime.datetime(2011, 3, 1, 0, 0): u'0.89'},
{datetime.datetime(2011, 6, 1, 0, 0): u'2.10'},
{datetime.datetime(2011, 9, 1, 0, 0): u'2.71'},
{datetime.datetime(2011, 12, 1, 0, 0): u'0.90'},
{datetime.datetime(2012, 3, 1, 0, 0): u'0.89'},
{datetime.datetime(2012, 6, 1, 0, 0): u'3.30'},
{datetime.datetime(2012, 9, 1, 0, 0): u'5.42'},
{datetime.datetime(2012, 12, 1, 0, 0): u'7.76'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.52'},
{datetime.datetime(2013, 6, 1, 0, 0): u'3.64'},
{datetime.datetime(2013, 9, 1, 0, 0): u'4.55'},
{datetime.datetime(2013, 12, 1, 0, 0): u'1.26'},
{datetime.datetime(2014, 3, 1, 0, 0): u'0.31'},
{datetime.datetime(2014, 6, 1, 0, 0): u'1.59'},
{datetime.datetime(2014, 9, 1, 0, 0): u'0.94'},
{datetime.datetime(2014, 12, 1, 0, 0): u'1.27'},
{datetime.datetime(2015, 3, 1, 0, 0): u'0.64'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.29'},
{datetime.datetime(2015, 9, 1, 0, 0): u'1.41'},
{datetime.datetime(2015, 12, 1, 0, 0): u'1.12'}],
u'53529': [{datetime.datetime(2003, 3, 1, 0, 0): u' 2.63'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.56'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n5.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53532': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.22'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n5.64'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n5.64'}],
u'53555': [{datetime.datetime(2003, 3, 1, 0, 0): u' 1.68'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.95'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.96'}],
u'53558': [{datetime.datetime(2003, 3, 1, 0, 0): u' 8.33'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n4.08'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n4.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n2.08'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n4.16'},
{datetime.datetime(2014, 3, 1, 0, 0): u'0.00'}],
u'53560': [{datetime.datetime(2003, 3, 1, 0, 0): u' 1.42'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.77'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53562': [{datetime.datetime(2003, 3, 1, 0, 0): u' 5.15'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n5.60'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n6.17'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n6.35'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n7.08'},
{datetime.datetime(2004, 6, 1, 0, 0): u'6.87'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n8.21'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n8.38'},
{datetime.datetime(2005, 3, 1, 0, 0): u'7.94'},
{datetime.datetime(2005, 6, 1, 0, 0): u'8.68'},
{datetime.datetime(2005, 9, 1, 0, 0): u'9.96'},
{datetime.datetime(2005, 12, 1, 0, 0): u'9.59'},
{datetime.datetime(2006, 3, 1, 0, 0): u'8.95'},
{datetime.datetime(2006, 6, 1, 0, 0): u'9.51'},
{datetime.datetime(2006, 9, 1, 0, 0): u'9.37'},
{datetime.datetime(2006, 12, 1, 0, 0): u'8.17'},
{datetime.datetime(2007, 3, 1, 0, 0): u'7.70'},
{datetime.datetime(2007, 6, 1, 0, 0): u'7.64'},
{datetime.datetime(2007, 9, 1, 0, 0): u'6.93'},
{datetime.datetime(2007, 12, 1, 0, 0): u'6.32'},
{datetime.datetime(2008, 3, 1, 0, 0): u'6.24'},
{datetime.datetime(2008, 6, 1, 0, 0): u'6.90'},
{datetime.datetime(2008, 9, 1, 0, 0): u'4.04'},
{datetime.datetime(2008, 12, 1, 0, 0): u'3.24'},
{datetime.datetime(2009, 3, 1, 0, 0): u'3.41'},
{datetime.datetime(2009, 6, 1, 0, 0): u'3.77'},
{datetime.datetime(2009, 9, 1, 0, 0): u'4.00'},
{datetime.datetime(2009, 12, 1, 0, 0): u'3.29'},
{datetime.datetime(2010, 3, 1, 0, 0): u'3.00'},
{datetime.datetime(2010, 6, 1, 0, 0): u'3.41'},
{datetime.datetime(2010, 9, 1, 0, 0): u'3.38'},
{datetime.datetime(2010, 12, 1, 0, 0): u'2.77'},
{datetime.datetime(2011, 3, 1, 0, 0): u'2.51'},
{datetime.datetime(2011, 6, 1, 0, 0): u'2.61'},
{datetime.datetime(2011, 9, 1, 0, 0): u'1.77'},
{datetime.datetime(2011, 12, 1, 0, 0): u'1.57'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.29'},
{datetime.datetime(2012, 6, 1, 0, 0): u'2.05'},
{datetime.datetime(2012, 9, 1, 0, 0): u'1.85'},
{datetime.datetime(2012, 12, 1, 0, 0): u'1.63'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.19'},
{datetime.datetime(2013, 6, 1, 0, 0): u'2.02'},
{datetime.datetime(2013, 9, 1, 0, 0): u'2.05'},
{datetime.datetime(2013, 12, 1, 0, 0): u'1.11'},
{datetime.datetime(2014, 3, 1, 0, 0): u'1.23'},
{datetime.datetime(2014, 6, 1, 0, 0): u'1.05'},
{datetime.datetime(2014, 9, 1, 0, 0): u'1.21'},
{datetime.datetime(2014, 12, 1, 0, 0): u'0.98'},
{datetime.datetime(2015, 3, 1, 0, 0): u'1.08'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.55'},
{datetime.datetime(2015, 9, 1, 0, 0): u'1.56'},
{datetime.datetime(2015, 12, 1, 0, 0): u'1.35'}],
u'53571': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'53572': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.97'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.96'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n1.98'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53575': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n3.89'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n3.94'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n2.85'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n1.38'},
{datetime.datetime(2014, 3, 1, 0, 0): u'0.00'},
{datetime.datetime(2014, 6, 1, 0, 0): u'0.00'},
{datetime.datetime(2014, 9, 1, 0, 0): u'1.40'},
{datetime.datetime(2014, 12, 1, 0, 0): u'0.00'},
{datetime.datetime(2015, 3, 1, 0, 0): u'0.00'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.40'},
{datetime.datetime(2015, 9, 1, 0, 0): u'1.38'},
{datetime.datetime(2015, 12, 1, 0, 0): u'1.36'}],
u'53578': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n1.58'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n1.58'}],
u'53582': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'53583': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53590': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n10.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n0.00'}],
u'53593': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.29'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n3.70'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n4.09'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n50.00'}],
u'53597': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.15'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.30'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n3.63'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n4.94'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n'},
{datetime.datetime(2014, 3, 1, 0, 0): u'2.87'},
{datetime.datetime(2014, 6, 1, 0, 0): u'2.88'},
{datetime.datetime(2014, 9, 1, 0, 0): u'2.09'},
{datetime.datetime(2014, 12, 1, 0, 0): u'1.69'},
{datetime.datetime(2015, 3, 1, 0, 0): u'1.68'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.74'},
{datetime.datetime(2015, 9, 1, 0, 0): u'0.66'},
{datetime.datetime(2015, 12, 1, 0, 0): u'0.44'}],
u'53598': [{datetime.datetime(2003, 3, 1, 0, 0): u' 1.44'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n1.44'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n1.44'}],
u'53703': [{datetime.datetime(2003, 3, 1, 0, 0): u' 2.76'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n4.26'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n4.06'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n3.46'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n3.39'},
{datetime.datetime(2004, 6, 1, 0, 0): u'4.68'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n5.19'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n5.03'},
{datetime.datetime(2005, 3, 1, 0, 0): u'4.32'},
{datetime.datetime(2005, 6, 1, 0, 0): u'4.98'},
{datetime.datetime(2005, 9, 1, 0, 0): u'3.88'},
{datetime.datetime(2005, 12, 1, 0, 0): u'3.03'},
{datetime.datetime(2006, 3, 1, 0, 0): u'3.13'},
{datetime.datetime(2006, 6, 1, 0, 0): u'4.64'},
{datetime.datetime(2006, 9, 1, 0, 0): u'3.49'},
{datetime.datetime(2006, 12, 1, 0, 0): u'2.98'},
{datetime.datetime(2007, 3, 1, 0, 0): u'2.73'},
{datetime.datetime(2007, 6, 1, 0, 0): u'3.70'},
{datetime.datetime(2007, 9, 1, 0, 0): u'2.41'},
{datetime.datetime(2007, 12, 1, 0, 0): u'2.32'},
{datetime.datetime(2008, 3, 1, 0, 0): u'2.20'},
{datetime.datetime(2008, 6, 1, 0, 0): u'3.37'},
{datetime.datetime(2008, 9, 1, 0, 0): u'2.18'},
{datetime.datetime(2008, 12, 1, 0, 0): u'2.00'},
{datetime.datetime(2009, 3, 1, 0, 0): u'1.95'},
{datetime.datetime(2009, 6, 1, 0, 0): u'3.36'},
{datetime.datetime(2009, 9, 1, 0, 0): u'3.27'},
{datetime.datetime(2009, 12, 1, 0, 0): u'2.18'},
{datetime.datetime(2010, 3, 1, 0, 0): u'2.19'},
{datetime.datetime(2010, 6, 1, 0, 0): u'3.63'},
{datetime.datetime(2010, 9, 1, 0, 0): u'2.12'},
{datetime.datetime(2010, 12, 1, 0, 0): u'1.82'},
{datetime.datetime(2011, 3, 1, 0, 0): u'1.80'},
{datetime.datetime(2011, 6, 1, 0, 0): u'3.25'},
{datetime.datetime(2011, 9, 1, 0, 0): u'1.75'},
{datetime.datetime(2011, 12, 1, 0, 0): u'1.52'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.43'},
{datetime.datetime(2012, 6, 1, 0, 0): u'2.87'},
{datetime.datetime(2012, 9, 1, 0, 0): u'1.50'},
{datetime.datetime(2012, 12, 1, 0, 0): u'1.52'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.49'},
{datetime.datetime(2013, 6, 1, 0, 0): u'2.56'},
{datetime.datetime(2013, 9, 1, 0, 0): u'1.63'},
{datetime.datetime(2013, 12, 1, 0, 0): u'1.34'},
{datetime.datetime(2014, 3, 1, 0, 0): u'1.53'},
{datetime.datetime(2014, 6, 1, 0, 0): u'3.02'},
{datetime.datetime(2014, 9, 1, 0, 0): u'2.45'},
{datetime.datetime(2014, 12, 1, 0, 0): u'2.04'},
{datetime.datetime(2015, 3, 1, 0, 0): u'2.07'},
{datetime.datetime(2015, 6, 1, 0, 0): u'3.56'},
{datetime.datetime(2015, 9, 1, 0, 0): u'3.18'},
{datetime.datetime(2015, 12, 1, 0, 0): u'2.36'}],
u'53704': [{datetime.datetime(2003, 3, 1, 0, 0): u' 2.91'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n4.27'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n3.87'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n2.99'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n3.05'},
{datetime.datetime(2004, 6, 1, 0, 0): u'4.07'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n4.24'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n3.74'},
{datetime.datetime(2005, 3, 1, 0, 0): u'3.60'},
{datetime.datetime(2005, 6, 1, 0, 0): u'4.35'},
{datetime.datetime(2005, 9, 1, 0, 0): u'4.29'},
{datetime.datetime(2005, 12, 1, 0, 0): u'3.84'},
{datetime.datetime(2006, 3, 1, 0, 0): u'3.37'},
{datetime.datetime(2006, 6, 1, 0, 0): u'4.53'},
{datetime.datetime(2006, 9, 1, 0, 0): u'4.27'},
{datetime.datetime(2006, 12, 1, 0, 0): u'3.52'},
{datetime.datetime(2007, 3, 1, 0, 0): u'3.50'},
{datetime.datetime(2007, 6, 1, 0, 0): u'3.97'},
{datetime.datetime(2007, 9, 1, 0, 0): u'3.25'},
{datetime.datetime(2007, 12, 1, 0, 0): u'3.10'},
{datetime.datetime(2008, 3, 1, 0, 0): u'3.35'},
{datetime.datetime(2008, 6, 1, 0, 0): u'3.49'},
{datetime.datetime(2008, 9, 1, 0, 0): u'3.18'},
{datetime.datetime(2008, 12, 1, 0, 0): u'2.73'},
{datetime.datetime(2009, 3, 1, 0, 0): u'2.46'},
{datetime.datetime(2009, 6, 1, 0, 0): u'3.86'},
{datetime.datetime(2009, 9, 1, 0, 0): u'3.95'},
{datetime.datetime(2009, 12, 1, 0, 0): u'2.77'},
{datetime.datetime(2010, 3, 1, 0, 0): u'2.70'},
{datetime.datetime(2010, 6, 1, 0, 0): u'3.74'},
{datetime.datetime(2010, 9, 1, 0, 0): u'3.12'},
{datetime.datetime(2010, 12, 1, 0, 0): u'1.99'},
{datetime.datetime(2011, 3, 1, 0, 0): u'1.86'},
{datetime.datetime(2011, 6, 1, 0, 0): u'2.89'},
{datetime.datetime(2011, 9, 1, 0, 0): u'2.20'},
{datetime.datetime(2011, 12, 1, 0, 0): u'1.22'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.40'},
{datetime.datetime(2012, 6, 1, 0, 0): u'2.75'},
{datetime.datetime(2012, 9, 1, 0, 0): u'2.04'},
{datetime.datetime(2012, 12, 1, 0, 0): u'1.62'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.55'},
{datetime.datetime(2013, 6, 1, 0, 0): u'1.99'},
{datetime.datetime(2013, 9, 1, 0, 0): u'2.05'},
{datetime.datetime(2013, 12, 1, 0, 0): u'1.58'},
{datetime.datetime(2014, 3, 1, 0, 0): u'1.80'},
{datetime.datetime(2014, 6, 1, 0, 0): u'2.64'},
{datetime.datetime(2014, 9, 1, 0, 0): u'2.42'},
{datetime.datetime(2014, 12, 1, 0, 0): u'1.91'},
{datetime.datetime(2015, 3, 1, 0, 0): u'1.78'},
{datetime.datetime(2015, 6, 1, 0, 0): u'2.63'},
{datetime.datetime(2015, 9, 1, 0, 0): u'2.34'},
{datetime.datetime(2015, 12, 1, 0, 0): u'1.70'}],
u'53705': [{datetime.datetime(2003, 3, 1, 0, 0): u' 7.43'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n10.34'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n9.36'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n8.79'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n9.27'},
{datetime.datetime(2004, 6, 1, 0, 0): u'10.64'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n7.64'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n8.59'},
{datetime.datetime(2005, 3, 1, 0, 0): u'8.57'},
{datetime.datetime(2005, 6, 1, 0, 0): u'10.31'},
{datetime.datetime(2005, 9, 1, 0, 0): u'8.41'},
{datetime.datetime(2005, 12, 1, 0, 0): u'7.72'},
{datetime.datetime(2006, 3, 1, 0, 0): u'7.53'},
{datetime.datetime(2006, 6, 1, 0, 0): u'9.26'},
{datetime.datetime(2006, 9, 1, 0, 0): u'6.44'},
{datetime.datetime(2006, 12, 1, 0, 0): u'5.94'},
{datetime.datetime(2007, 3, 1, 0, 0): u'6.19'},
{datetime.datetime(2007, 6, 1, 0, 0): u'8.36'},
{datetime.datetime(2007, 9, 1, 0, 0): u'4.41'},
{datetime.datetime(2007, 12, 1, 0, 0): u'3.79'},
{datetime.datetime(2008, 3, 1, 0, 0): u'3.56'},
{datetime.datetime(2008, 6, 1, 0, 0): u'4.23'},
{datetime.datetime(2008, 9, 1, 0, 0): u'2.95'},
{datetime.datetime(2008, 12, 1, 0, 0): u'3.31'},
{datetime.datetime(2009, 3, 1, 0, 0): u'3.39'},
{datetime.datetime(2009, 6, 1, 0, 0): u'4.87'},
{datetime.datetime(2009, 9, 1, 0, 0): u'3.96'},
{datetime.datetime(2009, 12, 1, 0, 0): u'3.60'},
{datetime.datetime(2010, 3, 1, 0, 0): u'3.68'},
{datetime.datetime(2010, 6, 1, 0, 0): u'5.41'},
{datetime.datetime(2010, 9, 1, 0, 0): u'3.91'},
{datetime.datetime(2010, 12, 1, 0, 0): u'3.43'},
{datetime.datetime(2011, 3, 1, 0, 0): u'3.57'},
{datetime.datetime(2011, 6, 1, 0, 0): u'4.42'},
{datetime.datetime(2011, 9, 1, 0, 0): u'2.39'},
{datetime.datetime(2011, 12, 1, 0, 0): u'2.37'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.90'},
{datetime.datetime(2012, 6, 1, 0, 0): u'3.39'},
{datetime.datetime(2012, 9, 1, 0, 0): u'2.17'},
{datetime.datetime(2012, 12, 1, 0, 0): u'1.71'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.81'},
{datetime.datetime(2013, 6, 1, 0, 0): u'3.05'},
{datetime.datetime(2013, 9, 1, 0, 0): u'2.41'},
{datetime.datetime(2013, 12, 1, 0, 0): u'1.65'},
{datetime.datetime(2014, 3, 1, 0, 0): u'2.11'},
{datetime.datetime(2014, 6, 1, 0, 0): u'6.12'},
{datetime.datetime(2014, 9, 1, 0, 0): u'4.27'},
{datetime.datetime(2014, 12, 1, 0, 0): u'3.86'},
{datetime.datetime(2015, 3, 1, 0, 0): u'3.87'},
{datetime.datetime(2015, 6, 1, 0, 0): u'5.60'},
{datetime.datetime(2015, 9, 1, 0, 0): u'3.57'},
{datetime.datetime(2015, 12, 1, 0, 0): u'3.66'}],
u'53711': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.03'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n5.37'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n5.71'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n4.67'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n5.23'},
{datetime.datetime(2004, 6, 1, 0, 0): u'6.89'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n5.69'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n5.14'},
{datetime.datetime(2005, 3, 1, 0, 0): u'5.16'},
{datetime.datetime(2005, 6, 1, 0, 0): u'7.01'},
{datetime.datetime(2005, 9, 1, 0, 0): u'6.37'},
{datetime.datetime(2005, 12, 1, 0, 0): u'5.28'},
{datetime.datetime(2006, 3, 1, 0, 0): u'4.80'},
{datetime.datetime(2006, 6, 1, 0, 0): u'5.44'},
{datetime.datetime(2006, 9, 1, 0, 0): u'5.87'},
{datetime.datetime(2006, 12, 1, 0, 0): u'4.76'},
{datetime.datetime(2007, 3, 1, 0, 0): u'4.66'},
{datetime.datetime(2007, 6, 1, 0, 0): u'5.15'},
{datetime.datetime(2007, 9, 1, 0, 0): u'5.21'},
{datetime.datetime(2007, 12, 1, 0, 0): u'4.34'},
{datetime.datetime(2008, 3, 1, 0, 0): u'3.90'},
{datetime.datetime(2008, 6, 1, 0, 0): u'3.92'},
{datetime.datetime(2008, 9, 1, 0, 0): u'4.53'},
{datetime.datetime(2008, 12, 1, 0, 0): u'3.85'},
{datetime.datetime(2009, 3, 1, 0, 0): u'3.83'},
{datetime.datetime(2009, 6, 1, 0, 0): u'4.90'},
{datetime.datetime(2009, 9, 1, 0, 0): u'5.25'},
{datetime.datetime(2009, 12, 1, 0, 0): u'5.06'},
{datetime.datetime(2010, 3, 1, 0, 0): u'5.37'},
{datetime.datetime(2010, 6, 1, 0, 0): u'5.88'},
{datetime.datetime(2010, 9, 1, 0, 0): u'4.95'},
{datetime.datetime(2010, 12, 1, 0, 0): u'3.72'},
{datetime.datetime(2011, 3, 1, 0, 0): u'2.86'},
{datetime.datetime(2011, 6, 1, 0, 0): u'3.00'},
{datetime.datetime(2011, 9, 1, 0, 0): u'3.17'},
{datetime.datetime(2011, 12, 1, 0, 0): u'2.71'},
{datetime.datetime(2012, 3, 1, 0, 0): u'2.31'},
{datetime.datetime(2012, 6, 1, 0, 0): u'3.82'},
{datetime.datetime(2012, 9, 1, 0, 0): u'3.44'},
{datetime.datetime(2012, 12, 1, 0, 0): u'3.04'},
{datetime.datetime(2013, 3, 1, 0, 0): u'2.60'},
{datetime.datetime(2013, 6, 1, 0, 0): u'2.65'},
{datetime.datetime(2013, 9, 1, 0, 0): u'3.53'},
{datetime.datetime(2013, 12, 1, 0, 0): u'2.15'},
{datetime.datetime(2014, 3, 1, 0, 0): u'2.19'},
{datetime.datetime(2014, 6, 1, 0, 0): u'2.99'},
{datetime.datetime(2014, 9, 1, 0, 0): u'2.81'},
{datetime.datetime(2014, 12, 1, 0, 0): u'1.92'},
{datetime.datetime(2015, 3, 1, 0, 0): u'2.14'},
{datetime.datetime(2015, 6, 1, 0, 0): u'3.00'},
{datetime.datetime(2015, 9, 1, 0, 0): u'2.66'},
{datetime.datetime(2015, 12, 1, 0, 0): u'2.28'}],
u'53713': [{datetime.datetime(2003, 3, 1, 0, 0): u' 6.48'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n8.42'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n9.45'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n8.96'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n8.74'},
{datetime.datetime(2004, 6, 1, 0, 0): u'10.43'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n10.53'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n10.30'},
{datetime.datetime(2005, 3, 1, 0, 0): u'10.48'},
{datetime.datetime(2005, 6, 1, 0, 0): u'10.59'},
{datetime.datetime(2005, 9, 1, 0, 0): u'9.90'},
{datetime.datetime(2005, 12, 1, 0, 0): u'9.37'},
{datetime.datetime(2006, 3, 1, 0, 0): u'9.01'},
{datetime.datetime(2006, 6, 1, 0, 0): u'8.21'},
{datetime.datetime(2006, 9, 1, 0, 0): u'8.17'},
{datetime.datetime(2006, 12, 1, 0, 0): u'8.39'},
{datetime.datetime(2007, 3, 1, 0, 0): u'8.54'},
{datetime.datetime(2007, 6, 1, 0, 0): u'9.06'},
{datetime.datetime(2007, 9, 1, 0, 0): u'8.69'},
{datetime.datetime(2007, 12, 1, 0, 0): u'8.33'},
{datetime.datetime(2008, 3, 1, 0, 0): u'8.61'},
{datetime.datetime(2008, 6, 1, 0, 0): u'7.49'},
{datetime.datetime(2008, 9, 1, 0, 0): u'6.41'},
{datetime.datetime(2008, 12, 1, 0, 0): u'6.53'},
{datetime.datetime(2009, 3, 1, 0, 0): u'6.47'},
{datetime.datetime(2009, 6, 1, 0, 0): u'7.64'},
{datetime.datetime(2009, 9, 1, 0, 0): u'7.76'},
{datetime.datetime(2009, 12, 1, 0, 0): u'6.68'},
{datetime.datetime(2010, 3, 1, 0, 0): u'6.32'},
{datetime.datetime(2010, 6, 1, 0, 0): u'6.79'},
{datetime.datetime(2010, 9, 1, 0, 0): u'5.90'},
{datetime.datetime(2010, 12, 1, 0, 0): u'5.37'},
{datetime.datetime(2011, 3, 1, 0, 0): u'5.14'},
{datetime.datetime(2011, 6, 1, 0, 0): u'5.18'},
{datetime.datetime(2011, 9, 1, 0, 0): u'5.07'},
{datetime.datetime(2011, 12, 1, 0, 0): u'4.36'},
{datetime.datetime(2012, 3, 1, 0, 0): u'4.25'},
{datetime.datetime(2012, 6, 1, 0, 0): u'4.72'},
{datetime.datetime(2012, 9, 1, 0, 0): u'3.94'},
{datetime.datetime(2012, 12, 1, 0, 0): u'3.03'},
{datetime.datetime(2013, 3, 1, 0, 0): u'3.06'},
{datetime.datetime(2013, 6, 1, 0, 0): u'4.17'},
{datetime.datetime(2013, 9, 1, 0, 0): u'4.23'},
{datetime.datetime(2013, 12, 1, 0, 0): u'3.80'},
{datetime.datetime(2014, 3, 1, 0, 0): u'4.25'},
{datetime.datetime(2014, 6, 1, 0, 0): u'4.75'},
{datetime.datetime(2014, 9, 1, 0, 0): u'3.71'},
{datetime.datetime(2014, 12, 1, 0, 0): u'3.24'},
{datetime.datetime(2015, 3, 1, 0, 0): u'3.27'},
{datetime.datetime(2015, 6, 1, 0, 0): u'4.32'},
{datetime.datetime(2015, 9, 1, 0, 0): u'3.46'},
{datetime.datetime(2015, 12, 1, 0, 0): u'2.56'}],
u'53714': [{datetime.datetime(2003, 3, 1, 0, 0): u' 4.51'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n5.88'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n7.32'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n7.77'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n7.50'},
{datetime.datetime(2004, 6, 1, 0, 0): u'7.66'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n6.62'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n7.95'},
{datetime.datetime(2005, 3, 1, 0, 0): u'7.52'},
{datetime.datetime(2005, 6, 1, 0, 0): u'9.01'},
{datetime.datetime(2005, 9, 1, 0, 0): u'8.74'},
{datetime.datetime(2005, 12, 1, 0, 0): u'7.82'},
{datetime.datetime(2006, 3, 1, 0, 0): u'7.92'},
{datetime.datetime(2006, 6, 1, 0, 0): u'10.20'},
{datetime.datetime(2006, 9, 1, 0, 0): u'9.42'},
{datetime.datetime(2006, 12, 1, 0, 0): u'7.90'},
{datetime.datetime(2007, 3, 1, 0, 0): u'7.46'},
{datetime.datetime(2007, 6, 1, 0, 0): u'5.99'},
{datetime.datetime(2007, 9, 1, 0, 0): u'6.44'},
{datetime.datetime(2007, 12, 1, 0, 0): u'6.39'},
{datetime.datetime(2008, 3, 1, 0, 0): u'7.25'},
{datetime.datetime(2008, 6, 1, 0, 0): u'6.38'},
{datetime.datetime(2008, 9, 1, 0, 0): u'4.48'},
{datetime.datetime(2008, 12, 1, 0, 0): u'4.18'},
{datetime.datetime(2009, 3, 1, 0, 0): u'3.94'},
{datetime.datetime(2009, 6, 1, 0, 0): u'5.32'},
{datetime.datetime(2009, 9, 1, 0, 0): u'5.85'},
{datetime.datetime(2009, 12, 1, 0, 0): u'5.36'},
{datetime.datetime(2010, 3, 1, 0, 0): u'5.66'},
{datetime.datetime(2010, 6, 1, 0, 0): u'5.71'},
{datetime.datetime(2010, 9, 1, 0, 0): u'6.06'},
{datetime.datetime(2010, 12, 1, 0, 0): u'3.84'},
{datetime.datetime(2011, 3, 1, 0, 0): u'4.48'},
{datetime.datetime(2011, 6, 1, 0, 0): u'4.76'},
{datetime.datetime(2011, 9, 1, 0, 0): u'2.89'},
{datetime.datetime(2011, 12, 1, 0, 0): u'3.28'},
{datetime.datetime(2012, 3, 1, 0, 0): u'2.45'},
{datetime.datetime(2012, 6, 1, 0, 0): u'3.73'},
{datetime.datetime(2012, 9, 1, 0, 0): u'2.53'},
{datetime.datetime(2012, 12, 1, 0, 0): u'3.03'},
{datetime.datetime(2013, 3, 1, 0, 0): u'2.78'},
{datetime.datetime(2013, 6, 1, 0, 0): u'3.37'},
{datetime.datetime(2013, 9, 1, 0, 0): u'3.77'},
{datetime.datetime(2013, 12, 1, 0, 0): u'3.03'},
{datetime.datetime(2014, 3, 1, 0, 0): u'3.32'},
{datetime.datetime(2014, 6, 1, 0, 0): u'4.51'},
{datetime.datetime(2014, 9, 1, 0, 0): u'4.32'},
{datetime.datetime(2014, 12, 1, 0, 0): u'4.05'},
{datetime.datetime(2015, 3, 1, 0, 0): u'3.31'},
{datetime.datetime(2015, 6, 1, 0, 0): u'4.83'},
{datetime.datetime(2015, 9, 1, 0, 0): u'3.63'},
{datetime.datetime(2015, 12, 1, 0, 0): u'3.07'}],
u'53715': [{datetime.datetime(2003, 3, 1, 0, 0): u' 1.02'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n1.35'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.51'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n1.67'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n1.43'},
{datetime.datetime(2004, 6, 1, 0, 0): u'2.34'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n3.62'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n3.38'},
{datetime.datetime(2005, 3, 1, 0, 0): u'2.79'},
{datetime.datetime(2005, 6, 1, 0, 0): u'3.28'},
{datetime.datetime(2005, 9, 1, 0, 0): u'3.48'},
{datetime.datetime(2005, 12, 1, 0, 0): u'2.37'},
{datetime.datetime(2006, 3, 1, 0, 0): u'2.32'},
{datetime.datetime(2006, 6, 1, 0, 0): u'2.56'},
{datetime.datetime(2006, 9, 1, 0, 0): u'2.39'},
{datetime.datetime(2006, 12, 1, 0, 0): u'1.48'},
{datetime.datetime(2007, 3, 1, 0, 0): u'1.48'},
{datetime.datetime(2007, 6, 1, 0, 0): u'2.20'},
{datetime.datetime(2007, 9, 1, 0, 0): u'1.15'},
{datetime.datetime(2007, 12, 1, 0, 0): u'1.10'},
{datetime.datetime(2008, 3, 1, 0, 0): u'0.72'},
{datetime.datetime(2008, 6, 1, 0, 0): u'1.18'},
{datetime.datetime(2008, 9, 1, 0, 0): u'1.33'},
{datetime.datetime(2008, 12, 1, 0, 0): u'0.96'},
{datetime.datetime(2009, 3, 1, 0, 0): u'1.15'},
{datetime.datetime(2009, 6, 1, 0, 0): u'2.51'},
{datetime.datetime(2009, 9, 1, 0, 0): u'2.51'},
{datetime.datetime(2009, 12, 1, 0, 0): u'2.09'},
{datetime.datetime(2010, 3, 1, 0, 0): u'2.07'},
{datetime.datetime(2010, 6, 1, 0, 0): u'3.32'},
{datetime.datetime(2010, 9, 1, 0, 0): u'2.36'},
{datetime.datetime(2010, 12, 1, 0, 0): u'2.44'},
{datetime.datetime(2011, 3, 1, 0, 0): u'2.35'},
{datetime.datetime(2011, 6, 1, 0, 0): u'2.92'},
{datetime.datetime(2011, 9, 1, 0, 0): u'0.92'},
{datetime.datetime(2011, 12, 1, 0, 0): u'0.96'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.07'},
{datetime.datetime(2012, 6, 1, 0, 0): u'2.56'},
{datetime.datetime(2012, 9, 1, 0, 0): u'3.28'},
{datetime.datetime(2012, 12, 1, 0, 0): u'2.05'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.53'},
{datetime.datetime(2013, 6, 1, 0, 0): u'2.24'},
{datetime.datetime(2013, 9, 1, 0, 0): u'5.28'},
{datetime.datetime(2013, 12, 1, 0, 0): u'3.73'},
{datetime.datetime(2014, 3, 1, 0, 0): u'3.42'},
{datetime.datetime(2014, 6, 1, 0, 0): u'3.71'},
{datetime.datetime(2014, 9, 1, 0, 0): u'4.68'},
{datetime.datetime(2014, 12, 1, 0, 0): u'3.97'},
{datetime.datetime(2015, 3, 1, 0, 0): u'3.55'},
{datetime.datetime(2015, 6, 1, 0, 0): u'4.02'},
{datetime.datetime(2015, 9, 1, 0, 0): u'5.39'},
{datetime.datetime(2015, 12, 1, 0, 0): u'4.39'}],
u'53716': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.83'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n6.52'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n4.89'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n2.29'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n3.24'},
{datetime.datetime(2004, 6, 1, 0, 0): u'5.73'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n4.49'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n3.90'},
{datetime.datetime(2005, 3, 1, 0, 0): u'4.67'},
{datetime.datetime(2005, 6, 1, 0, 0): u'6.86'},
{datetime.datetime(2005, 9, 1, 0, 0): u'6.55'},
{datetime.datetime(2005, 12, 1, 0, 0): u'4.36'},
{datetime.datetime(2006, 3, 1, 0, 0): u'5.49'},
{datetime.datetime(2006, 6, 1, 0, 0): u'7.25'},
{datetime.datetime(2006, 9, 1, 0, 0): u'5.88'},
{datetime.datetime(2006, 12, 1, 0, 0): u'4.92'},
{datetime.datetime(2007, 3, 1, 0, 0): u'2.85'},
{datetime.datetime(2007, 6, 1, 0, 0): u'4.92'},
{datetime.datetime(2007, 9, 1, 0, 0): u'4.81'},
{datetime.datetime(2007, 12, 1, 0, 0): u'3.78'},
{datetime.datetime(2008, 3, 1, 0, 0): u'3.75'},
{datetime.datetime(2008, 6, 1, 0, 0): u'5.07'},
{datetime.datetime(2008, 9, 1, 0, 0): u'4.65'},
{datetime.datetime(2008, 12, 1, 0, 0): u'4.09'},
{datetime.datetime(2009, 3, 1, 0, 0): u'4.21'},
{datetime.datetime(2009, 6, 1, 0, 0): u'5.57'},
{datetime.datetime(2009, 9, 1, 0, 0): u'6.34'},
{datetime.datetime(2009, 12, 1, 0, 0): u'6.17'},
{datetime.datetime(2010, 3, 1, 0, 0): u'6.16'},
{datetime.datetime(2010, 6, 1, 0, 0): u'7.62'},
{datetime.datetime(2010, 9, 1, 0, 0): u'6.57'},
{datetime.datetime(2010, 12, 1, 0, 0): u'5.58'},
{datetime.datetime(2011, 3, 1, 0, 0): u'5.94'},
{datetime.datetime(2011, 6, 1, 0, 0): u'6.12'},
{datetime.datetime(2011, 9, 1, 0, 0): u'5.01'},
{datetime.datetime(2011, 12, 1, 0, 0): u'4.02'},
{datetime.datetime(2012, 3, 1, 0, 0): u'3.55'},
{datetime.datetime(2012, 6, 1, 0, 0): u'4.65'},
{datetime.datetime(2012, 9, 1, 0, 0): u'3.55'},
{datetime.datetime(2012, 12, 1, 0, 0): u'3.33'},
{datetime.datetime(2013, 3, 1, 0, 0): u'3.17'},
{datetime.datetime(2013, 6, 1, 0, 0): u'4.44'},
{datetime.datetime(2013, 9, 1, 0, 0): u'3.86'},
{datetime.datetime(2013, 12, 1, 0, 0): u'3.13'},
{datetime.datetime(2014, 3, 1, 0, 0): u'3.70'},
{datetime.datetime(2014, 6, 1, 0, 0): u'4.92'},
{datetime.datetime(2014, 9, 1, 0, 0): u'2.50'},
{datetime.datetime(2014, 12, 1, 0, 0): u'3.36'},
{datetime.datetime(2015, 3, 1, 0, 0): u'2.53'},
{datetime.datetime(2015, 6, 1, 0, 0): u'3.99'},
{datetime.datetime(2015, 9, 1, 0, 0): u'2.83'},
{datetime.datetime(2015, 12, 1, 0, 0): u'2.78'}],
u'53717': [{datetime.datetime(2003, 3, 1, 0, 0): u' 4.20'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n4.89'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n6.06'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n5.95'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n4.94'},
{datetime.datetime(2004, 6, 1, 0, 0): u'4.94'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n5.02'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n4.76'},
{datetime.datetime(2005, 3, 1, 0, 0): u'3.11'},
{datetime.datetime(2005, 6, 1, 0, 0): u'4.12'},
{datetime.datetime(2005, 9, 1, 0, 0): u'4.76'},
{datetime.datetime(2005, 12, 1, 0, 0): u'4.21'},
{datetime.datetime(2006, 3, 1, 0, 0): u'2.93'},
{datetime.datetime(2006, 6, 1, 0, 0): u'3.11'},
{datetime.datetime(2006, 9, 1, 0, 0): u'3.02'},
{datetime.datetime(2006, 12, 1, 0, 0): u'1.64'},
{datetime.datetime(2007, 3, 1, 0, 0): u'2.83'},
{datetime.datetime(2007, 6, 1, 0, 0): u'3.11'},
{datetime.datetime(2007, 9, 1, 0, 0): u'2.38'},
{datetime.datetime(2007, 12, 1, 0, 0): u'2.38'},
{datetime.datetime(2008, 3, 1, 0, 0): u'2.19'},
{datetime.datetime(2008, 6, 1, 0, 0): u'1.64'},
{datetime.datetime(2008, 9, 1, 0, 0): u'1.37'},
{datetime.datetime(2008, 12, 1, 0, 0): u'2.10'},
{datetime.datetime(2009, 3, 1, 0, 0): u'1.09'},
{datetime.datetime(2009, 6, 1, 0, 0): u'1.83'},
{datetime.datetime(2009, 9, 1, 0, 0): u'3.20'},
{datetime.datetime(2009, 12, 1, 0, 0): u'3.02'},
{datetime.datetime(2010, 3, 1, 0, 0): u'3.66'},
{datetime.datetime(2010, 6, 1, 0, 0): u'4.39'},
{datetime.datetime(2010, 9, 1, 0, 0): u'5.40'},
{datetime.datetime(2010, 12, 1, 0, 0): u'2.38'},
{datetime.datetime(2011, 3, 1, 0, 0): u'2.74'},
{datetime.datetime(2011, 6, 1, 0, 0): u'1.09'},
{datetime.datetime(2011, 9, 1, 0, 0): u'1.00'},
{datetime.datetime(2011, 12, 1, 0, 0): u'1.64'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.55'},
{datetime.datetime(2012, 6, 1, 0, 0): u'1.64'},
{datetime.datetime(2012, 9, 1, 0, 0): u'1.19'},
{datetime.datetime(2012, 12, 1, 0, 0): u'1.28'},
{datetime.datetime(2013, 3, 1, 0, 0): u'0.73'},
{datetime.datetime(2013, 6, 1, 0, 0): u'1.09'},
{datetime.datetime(2013, 9, 1, 0, 0): u'1.19'},
{datetime.datetime(2013, 12, 1, 0, 0): u'1.28'},
{datetime.datetime(2014, 3, 1, 0, 0): u'1.10'},
{datetime.datetime(2014, 6, 1, 0, 0): u'3.38'},
{datetime.datetime(2014, 9, 1, 0, 0): u'1.92'},
{datetime.datetime(2014, 12, 1, 0, 0): u'1.55'},
{datetime.datetime(2015, 3, 1, 0, 0): u'1.00'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.28'},
{datetime.datetime(2015, 9, 1, 0, 0): u'1.64'},
{datetime.datetime(2015, 12, 1, 0, 0): u'1.00'}],
u'53718': [{datetime.datetime(2003, 3, 1, 0, 0): u' 5.27'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n7.80'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n6.42'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n4.51'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n4.56'},
{datetime.datetime(2004, 6, 1, 0, 0): u'3.21'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n2.19'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n2.55'},
{datetime.datetime(2005, 3, 1, 0, 0): u'2.81'},
{datetime.datetime(2005, 6, 1, 0, 0): u'5.59'},
{datetime.datetime(2005, 9, 1, 0, 0): u'5.30'},
{datetime.datetime(2005, 12, 1, 0, 0): u'6.81'},
{datetime.datetime(2006, 3, 1, 0, 0): u'4.70'},
{datetime.datetime(2006, 6, 1, 0, 0): u'3.48'},
{datetime.datetime(2006, 9, 1, 0, 0): u'2.06'},
{datetime.datetime(2006, 12, 1, 0, 0): u'2.14'},
{datetime.datetime(2007, 3, 1, 0, 0): u'2.29'},
{datetime.datetime(2007, 6, 1, 0, 0): u'2.09'},
{datetime.datetime(2007, 9, 1, 0, 0): u'1.35'},
{datetime.datetime(2007, 12, 1, 0, 0): u'1.10'},
{datetime.datetime(2008, 3, 1, 0, 0): u'1.70'},
{datetime.datetime(2008, 6, 1, 0, 0): u'1.17'},
{datetime.datetime(2008, 9, 1, 0, 0): u'1.07'},
{datetime.datetime(2008, 12, 1, 0, 0): u'0.66'},
{datetime.datetime(2009, 3, 1, 0, 0): u'1.14'},
{datetime.datetime(2009, 6, 1, 0, 0): u'2.38'},
{datetime.datetime(2009, 9, 1, 0, 0): u'2.09'},
{datetime.datetime(2009, 12, 1, 0, 0): u'1.62'},
{datetime.datetime(2010, 3, 1, 0, 0): u'1.82'},
{datetime.datetime(2010, 6, 1, 0, 0): u'3.07'},
{datetime.datetime(2010, 9, 1, 0, 0): u'1.50'},
{datetime.datetime(2010, 12, 1, 0, 0): u'0.50'},
{datetime.datetime(2011, 3, 1, 0, 0): u'1.52'},
{datetime.datetime(2011, 6, 1, 0, 0): u'3.00'},
{datetime.datetime(2011, 9, 1, 0, 0): u'1.21'},
{datetime.datetime(2011, 12, 1, 0, 0): u'0.85'},
{datetime.datetime(2012, 3, 1, 0, 0): u'0.92'},
{datetime.datetime(2012, 6, 1, 0, 0): u'2.10'},
{datetime.datetime(2012, 9, 1, 0, 0): u'0.80'},
{datetime.datetime(2012, 12, 1, 0, 0): u'0.26'},
{datetime.datetime(2013, 3, 1, 0, 0): u'0.74'},
{datetime.datetime(2013, 6, 1, 0, 0): u'1.55'},
{datetime.datetime(2013, 9, 1, 0, 0): u'1.16'},
{datetime.datetime(2013, 12, 1, 0, 0): u'0.69'},
{datetime.datetime(2014, 3, 1, 0, 0): u'1.17'},
{datetime.datetime(2014, 6, 1, 0, 0): u'2.12'},
{datetime.datetime(2014, 9, 1, 0, 0): u'0.84'},
{datetime.datetime(2014, 12, 1, 0, 0): u'0.22'},
{datetime.datetime(2015, 3, 1, 0, 0): u'0.56'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.86'},
{datetime.datetime(2015, 9, 1, 0, 0): u'2.94'},
{datetime.datetime(2015, 12, 1, 0, 0): u'0.54'}],
u'53719': [{datetime.datetime(2003, 3, 1, 0, 0): u' 5.95'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n6.76'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n7.30'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n6.43'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n6.36'},
{datetime.datetime(2004, 6, 1, 0, 0): u'7.96'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n9.94'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n12.10'},
{datetime.datetime(2005, 3, 1, 0, 0): u'12.96'},
{datetime.datetime(2005, 6, 1, 0, 0): u'12.23'},
{datetime.datetime(2005, 9, 1, 0, 0): u'11.44'},
{datetime.datetime(2005, 12, 1, 0, 0): u'10.51'},
{datetime.datetime(2006, 3, 1, 0, 0): u'9.28'},
{datetime.datetime(2006, 6, 1, 0, 0): u'11.30'},
{datetime.datetime(2006, 9, 1, 0, 0): u'14.96'},
{datetime.datetime(2006, 12, 1, 0, 0): u'14.90'},
{datetime.datetime(2007, 3, 1, 0, 0): u'12.44'},
{datetime.datetime(2007, 6, 1, 0, 0): u'11.94'},
{datetime.datetime(2007, 9, 1, 0, 0): u'10.65'},
{datetime.datetime(2007, 12, 1, 0, 0): u'9.71'},
{datetime.datetime(2008, 3, 1, 0, 0): u'8.78'},
{datetime.datetime(2008, 6, 1, 0, 0): u'6.25'},
{datetime.datetime(2008, 9, 1, 0, 0): u'3.88'},
{datetime.datetime(2008, 12, 1, 0, 0): u'4.60'},
{datetime.datetime(2009, 3, 1, 0, 0): u'5.97'},
{datetime.datetime(2009, 6, 1, 0, 0): u'4.31'},
{datetime.datetime(2009, 9, 1, 0, 0): u'8.91'},
{datetime.datetime(2009, 12, 1, 0, 0): u'6.26'},
{datetime.datetime(2010, 3, 1, 0, 0): u'6.55'},
{datetime.datetime(2010, 6, 1, 0, 0): u'6.61'},
{datetime.datetime(2010, 9, 1, 0, 0): u'2.80'},
{datetime.datetime(2010, 12, 1, 0, 0): u'2.95'},
{datetime.datetime(2011, 3, 1, 0, 0): u'2.73'},
{datetime.datetime(2011, 6, 1, 0, 0): u'4.67'},
{datetime.datetime(2011, 9, 1, 0, 0): u'3.59'},
{datetime.datetime(2011, 12, 1, 0, 0): u'2.59'},
{datetime.datetime(2012, 3, 1, 0, 0): u'2.30'},
{datetime.datetime(2012, 6, 1, 0, 0): u'4.02'},
{datetime.datetime(2012, 9, 1, 0, 0): u'3.74'},
{datetime.datetime(2012, 12, 1, 0, 0): u'2.73'},
{datetime.datetime(2013, 3, 1, 0, 0): u'1.65'},
{datetime.datetime(2013, 6, 1, 0, 0): u'4.02'},
{datetime.datetime(2013, 9, 1, 0, 0): u'3.52'},
{datetime.datetime(2013, 12, 1, 0, 0): u'3.59'},
{datetime.datetime(2014, 3, 1, 0, 0): u'3.23'},
{datetime.datetime(2014, 6, 1, 0, 0): u'3.88'},
{datetime.datetime(2014, 9, 1, 0, 0): u'2.80'},
{datetime.datetime(2014, 12, 1, 0, 0): u'2.44'},
{datetime.datetime(2015, 3, 1, 0, 0): u'2.15'},
{datetime.datetime(2015, 6, 1, 0, 0): u'3.23'},
{datetime.datetime(2015, 9, 1, 0, 0): u'4.46'},
{datetime.datetime(2015, 12, 1, 0, 0): u'2.87'}],
u'53726': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.74'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.32'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.73'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n1.42'},
{datetime.datetime(2004, 3, 1, 0, 0): u'\n1.51'},
{datetime.datetime(2004, 6, 1, 0, 0): u'2.60'},
{datetime.datetime(2004, 9, 1, 0, 0): u'\n4.09'},
{datetime.datetime(2004, 12, 1, 0, 0): u'\n3.38'},
{datetime.datetime(2005, 3, 1, 0, 0): u'3.23'},
{datetime.datetime(2005, 6, 1, 0, 0): u'5.00'},
{datetime.datetime(2005, 9, 1, 0, 0): u'2.85'},
{datetime.datetime(2005, 12, 1, 0, 0): u'2.00'},
{datetime.datetime(2006, 3, 1, 0, 0): u'1.46'},
{datetime.datetime(2006, 6, 1, 0, 0): u'2.46'},
{datetime.datetime(2006, 9, 1, 0, 0): u'1.76'},
{datetime.datetime(2006, 12, 1, 0, 0): u'1.30'},
{datetime.datetime(2007, 3, 1, 0, 0): u'0.76'},
{datetime.datetime(2007, 6, 1, 0, 0): u'2.30'},
{datetime.datetime(2007, 9, 1, 0, 0): u'1.00'},
{datetime.datetime(2007, 12, 1, 0, 0): u'1.15'},
{datetime.datetime(2008, 3, 1, 0, 0): u'1.07'},
{datetime.datetime(2008, 6, 1, 0, 0): u'2.38'},
{datetime.datetime(2008, 9, 1, 0, 0): u'1.15'},
{datetime.datetime(2008, 12, 1, 0, 0): u'0.99'},
{datetime.datetime(2009, 3, 1, 0, 0): u'0.92'},
{datetime.datetime(2009, 6, 1, 0, 0): u'2.38'},
{datetime.datetime(2009, 9, 1, 0, 0): u'1.69'},
{datetime.datetime(2009, 12, 1, 0, 0): u'1.23'},
{datetime.datetime(2010, 3, 1, 0, 0): u'0.77'},
{datetime.datetime(2010, 6, 1, 0, 0): u'2.46'},
{datetime.datetime(2010, 9, 1, 0, 0): u'1.92'},
{datetime.datetime(2010, 12, 1, 0, 0): u'1.15'},
{datetime.datetime(2011, 3, 1, 0, 0): u'1.07'},
{datetime.datetime(2011, 6, 1, 0, 0): u'1.23'},
{datetime.datetime(2011, 9, 1, 0, 0): u'0.84'},
{datetime.datetime(2011, 12, 1, 0, 0): u'1.00'},
{datetime.datetime(2012, 3, 1, 0, 0): u'1.08'},
{datetime.datetime(2012, 6, 1, 0, 0): u'1.46'},
{datetime.datetime(2012, 9, 1, 0, 0): u'1.07'},
{datetime.datetime(2012, 12, 1, 0, 0): u'0.69'},
{datetime.datetime(2013, 3, 1, 0, 0): u'0.69'},
{datetime.datetime(2013, 6, 1, 0, 0): u'1.51'},
{datetime.datetime(2013, 9, 1, 0, 0): u'1.17'},
{datetime.datetime(2013, 12, 1, 0, 0): u'0.80'},
{datetime.datetime(2014, 3, 1, 0, 0): u'1.03'},
{datetime.datetime(2014, 6, 1, 0, 0): u'1.46'},
{datetime.datetime(2014, 9, 1, 0, 0): u'1.02'},
{datetime.datetime(2014, 12, 1, 0, 0): u'0.95'},
{datetime.datetime(2015, 3, 1, 0, 0): u'1.31'},
{datetime.datetime(2015, 6, 1, 0, 0): u'1.61'},
{datetime.datetime(2015, 9, 1, 0, 0): u'3.00'},
{datetime.datetime(2015, 12, 1, 0, 0): u'1.90'}],
u'53821': [{datetime.datetime(2003, 3, 1, 0, 0): u' 2.23'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.23'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.23'}],
u'53826': [{datetime.datetime(2003, 3, 1, 0, 0): u' 8.82'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n12.12'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n15.38'}],
u'53911': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'53929': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n2.85'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n2.94'}],
u'53955': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'54626': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'54631': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 12, 1, 0, 0): u'\n0.00'}],
u'54638': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'54645': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'54648': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}],
u'54652': [{datetime.datetime(2003, 3, 1, 0, 0): u' 25.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n25.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n100.00'}],
u'54655': [{datetime.datetime(2003, 3, 1, 0, 0): u' 3.44'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n10.34'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n6.89'}],
u'54665': [{datetime.datetime(2003, 3, 1, 0, 0): u' 7.35'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n1.44'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n1.72'}],
u'54670': [{datetime.datetime(2003, 3, 1, 0, 0): u' 0.00'},
{datetime.datetime(2003, 6, 1, 0, 0): u'\n0.00'},
{datetime.datetime(2003, 9, 1, 0, 0): u'\n0.00'}]})
In [ ]:
Content source: stephenpardy/PythonNotebooks
Similar notebooks: