def __init__(self):
self.logger = LoggerManager().getLogger(__name__)
self.hist_econ_data_factory = HistEconDataFactory()
"""
import datetime
from pythalesians.economics.events.histecondatafactory import HistEconDataFactory
from pythalesians.economics.events.popular.commonecondatafactory import CommonEconDataFactory
from pythalesians.util.loggermanager import LoggerManager
# just change "False" to "True" to run any of the below examples
#### Plot US economic data by state using a choropleth Plotly plot
####
if False:
logger = LoggerManager.getLogger(__name__)
hist = HistEconDataFactory()
start_date = '01 Jan 1990'
finish_date = datetime.datetime.utcnow()
country_group = 'usa-states'
yoy_ret = False
# select as appropriate
# data_type = 'Total Nonfarm'; title = 'Change in non-farm payrolls (YoY)'; freq = 12
# data_type = 'Real GDP'; title = 'Real GDP'; freq = 1
# data_type = 'Economic Activity Index'; title = 'Economic Activity Index (YoY change %)'; yoy_ret = True; freq = 12
# data_type = 'Total Construction Employees'; title = Total Construction Employees'; freq = 12
data_type = 'Unemployment Rate'; title = 'Unemployment Rate'; freq = 12
# data_type = 'Total Personal Income'; title = 'Total Personal Income'; freq = 12
# data_type = 'House Price Index'; title = 'House Price Index (YoY change %)'; yoy_ret = True; freq = 12;
source = 'fred'
class CommonEconDataFactory:
def __init__(self):
self.logger = LoggerManager().getLogger(__name__)
self.hist_econ_data_factory = HistEconDataFactory()
def get_econ_data_group(self, start_date, finish_date, country_group,
data_type, source):
df = self.hist_econ_data_factory.get_economic_data_history(
start_date, finish_date, country_group, data_type, source=source)
df = df.fillna(method='pad')
return df
def get_GDP_QoQ(self,
start_date,
finish_date,
country_group,
source='bloomberg'):
return self.get_econ_data_group(start_date,
finish_date,
country_group,
'GDP QoQ (SAAR)',
source=source)
def get_GDP_QoQ(self,
start_date,
finish_date,
country_group,
source='bloomberg'):
return self.get_econ_data_group(start_date,
finish_date,
country_group,
'GDP QoQ (SAAR)',
source=source)
def get_UNE(self,
start_date,
finish_date,
country_group,
source='bloomberg'):
return self.get_econ_data_group(start_date,
finish_date,
country_group,
'Unemployment Rate',
source=source)
def get_CPI_YoY(self,
start_date,
finish_date,
country_group,
source='bloomberg'):
return self.get_econ_data_group(start_date,
finish_date,
country_group,
'CPI YoY',
source=source)
def usa_plot_une(self, start_date, finish_date):
country_group = 'usa-states'
source = 'bloomberg'
une = self.get_UNE(start_date,
finish_date,
country_group,
source='bloomberg')
une = self.hist_econ_data_factory.grasp_coded_entry(une, -1)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'USA-states'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'usa'
gp.plotly_projection = 'albers usa'
gp.plotly_world_readable = False
gp.plotly_url = country_group + "-unemployment"
gp.title = "USA Unemployment"
gp.units = 'pc'
pf.plot_generic_graph(une, type='choropleth', adapter='plotly', gp=gp)
def g10_plot_gdp_cpi_une(self, start_date, finish_date, data_type='cpi'):
country_group = 'g10'
if data_type == 'cpi':
df = self.get_CPI_YoY(start_date, finish_date, country_group)
elif data_type == 'gdp':
df = self.get_GDP_QoQ(start_date, finish_date, country_group)
elif data_type == 'une':
df = self.get_UNE(start_date, finish_date, country_group)
df = self.hist_econ_data_factory.grasp_coded_entry(df, -1)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'world'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'world'
gp.plotly_projection = 'Mercator'
gp.plotly_world_readable = False
gp.plotly_url = country_group + "-" + data_type
gp.title = "G10 " + data_type
gp.units = '%'
pf.plot_generic_graph(df, type='choropleth', adapter='plotly', gp=gp)
def europe_plot_une(self, start_date, finish_date):
country_group = 'all-europe'
une = self.get_UNE(start_date, finish_date, country_group)
une = self.hist_econ_data_factory.grasp_coded_entry(une, -1)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'europe'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'europe'
gp.plotly_projection = 'Mercator'
gp.plotly_world_readable = False
gp.plotly_url = country_group + "-unemployment"
gp.title = "Europe Unemployment"
gp.units = '%'
pf.plot_generic_graph(une, type='choropleth', adapter='plotly', gp=gp)
def world_plot_cpi(self, start_date, finish_date):
country_group = 'world-liquid'
cpi = self.get_CPI_YoY(start_date, finish_date, country_group)
cpi = self.hist_econ_data_factory.grasp_coded_entry(cpi, -1)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'world'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'world'
gp.plotly_projection = 'Mercator'
gp.plotly_world_readable = False
gp.plotly_url = str(country_group) + "-cpi"
gp.title = "World Liquid CPI YoY"
gp.units = '%'
pf.plot_generic_graph(cpi, type='choropleth', adapter='plotly', gp=gp)
def g10_line_plot_cpi(self, start_date, finish_date):
today_root = datetime.date.today().strftime("%Y%m%d") + " "
country_group = 'g10-ez'
cpi = self.get_CPI_YoY(start_date, finish_date, country_group)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.title = "G10 CPI YoY"
gp.units = '%'
gp.scale_factor = Constants.plotfactory_scale_factor
gp.file_output = today_root + 'G10 CPI YoY ' + str(
gp.scale_factor) + '.png'
cpi.columns = [x.split('-')[0] for x in cpi.columns]
gp.linewidth_2 = 3
gp.linewidth_2_series = ['United States']
pf.plot_generic_graph(cpi, type='line', adapter='pythalesians', gp=gp)
def g10_line_plot_une(self, start_date, finish_date):
today_root = datetime.date.today().strftime("%Y%m%d") + " "
country_group = 'g10-ez'
une = self.get_UNE(start_date, finish_date, country_group)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.title = "G10 Unemployment Rate (%)"
gp.units = '%'
gp.scale_factor = Constants.plotfactory_scale_factor
gp.file_output = today_root + 'G10 UNE ' + str(
gp.scale_factor) + '.png'
une.columns = [x.split('-')[0] for x in une.columns]
gp.linewidth_2 = 3
gp.linewidth_2_series = ['United States']
pf.plot_generic_graph(une, type='line', adapter='pythalesians', gp=gp)
def g10_line_plot_gdp(self, start_date, finish_date):
today_root = datetime.date.today().strftime("%Y%m%d") + " "
country_group = 'g10-ez'
gdp = self.get_GDP_QoQ(start_date, finish_date, country_group)
from chartesians.graphs import PlotFactory
from chartesians.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.title = "G10 GDP"
gp.units = 'Rebased'
gp.scale_factor = Constants.plotfactory_scale_factor
gp.file_output = today_root + 'G10 UNE ' + str(
gp.scale_factor) + '.png'
gdp.columns = [x.split('-')[0] for x in gdp.columns]
gp.linewidth_2 = 3
gp.linewidth_2_series = ['United Kingdom']
from pythalesians.timeseries.calcs.timeseriescalcs import TimeSeriesCalcs
tsc = TimeSeriesCalcs()
gdp = gdp / 100
gdp = tsc.create_mult_index_from_prices(gdp)
pf.plot_generic_graph(gdp, type='line', adapter='pythalesians', gp=gp)
__author__ = 'saeedamen'
from pythalesians.util.loggermanager import LoggerManager
from pythalesians.economics.events.histecondatafactory import HistEconDataFactory
from pythalesians.economics.events.popular.commonecondatafactory import CommonEconDataFactory
import datetime
class EconComparison:
pass
if __name__ == '__main__':
logger = LoggerManager.getLogger(__name__)
hist = HistEconDataFactory()
start_date = '01 Jan 1990'
finish_date = datetime.datetime.utcnow()
def __init__(self):
self.logger = LoggerManager().getLogger(__name__)
self.hist_econ_data_factory = HistEconDataFactory()
class CommonEconDataFactory:
def __init__(self):
self.logger = LoggerManager().getLogger(__name__)
self.hist_econ_data_factory = HistEconDataFactory()
def get_econ_data_group(self, start_date, finish_date, country_group, data_type, source):
df = self.hist_econ_data_factory.get_economic_data_history(start_date, finish_date,
country_group, data_type, source = source)
df = df.fillna(method='pad')
return df
def get_GDP_QoQ(self, start_date, finish_date, country_group, source = 'bloomberg'):
return self.get_econ_data_group(start_date, finish_date, country_group, 'GDP QoQ (SAAR)', source = source)
def get_UNE(self, start_date, finish_date, country_group, source = 'bloomberg'):
return self.get_econ_data_group(start_date, finish_date, country_group, 'Unemployment Rate', source = source)
def get_CPI_YoY(self, start_date, finish_date, country_group, source = 'bloomberg'):
return self.get_econ_data_group(start_date, finish_date, country_group, 'CPI YoY', source = source)
def usa_plot_une(self, start_date, finish_date):
country_group = 'usa-states'; source = 'bloomberg'
une = self.get_UNE(start_date, finish_date, country_group, source = 'bloomberg')
une = self.hist_econ_data_factory.grasp_coded_entry(une, -1)
from pythalesians.graphics.graphs.plotfactory import PlotFactory
from pythalesians.graphics.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'USA-states'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'usa'
gp.plotly_projection = 'albers usa'
gp.plotly_world_readable = False
gp.plotly_url = country_group + "-unemployment"
gp.title = "USA Unemployment"
gp.units = 'pc'
pf.plot_generic_graph(une, type = 'choropleth', adapter = 'plotly', gp = gp)
def g10_plot_gdp_cpi_une(self, start_date, finish_date, data_type = 'cpi'):
country_group = 'g10'
if data_type == 'cpi':
df = self.get_CPI_YoY(start_date, finish_date, country_group)
elif data_type == 'gdp':
df = self.get_GDP_YoY(start_date, finish_date, country_group)
elif data_type == 'une':
df = self.get_UNE(start_date, finish_date, country_group)
df = self.hist_econ_data_factory.grasp_coded_entry(df, -1)
from pythalesians.graphics.graphs.plotfactory import PlotFactory
from pythalesians.graphics.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'world'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'world'
gp.plotly_projection = 'Mercator'
gp.plotly_world_readable = False
gp.plotly_url = country_group + "-" + data_type
gp.title = "G10 " + data_type
gp.units = '%'
pf.plot_generic_graph(df, type = 'choropleth', adapter = 'plotly', gp = gp)
def europe_plot_une(self, start_date, finish_date):
country_group = 'all-europe'
une = self.get_UNE(start_date, finish_date, country_group)
une = self.hist_econ_data_factory.grasp_coded_entry(une, -1)
from pythalesians.graphics.graphs.plotfactory import PlotFactory
from pythalesians.graphics.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'europe'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'europe'
gp.plotly_projection = 'Mercator'
gp.plotly_world_readable = False
gp.plotly_url = country_group + "-unemployment"; gp.title = "Europe Unemployment"
gp.units = '%'
pf.plot_generic_graph(une, type = 'choropleth', adapter = 'plotly', gp = gp)
def world_plot_cpi(self, start_date, finish_date):
country_group = 'world-liquid'
cpi = self.get_CPI_YoY(start_date, finish_date, country_group)
cpi = self.hist_econ_data_factory.grasp_coded_entry(cpi, -1)
from pythalesians.graphics.graphs.plotfactory import PlotFactory
from pythalesians.graphics.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.plotly_location_mode = 'world'
gp.plotly_choropleth_field = 'Val'
gp.plotly_scope = 'world'
gp.plotly_projection = 'Mercator'
gp.plotly_world_readable = False
gp.plotly_url = str(country_group) + "-cpi"
gp.title = "World Liquid CPI YoY"
gp.units = '%'
pf.plot_generic_graph(cpi, type = 'choropleth', adapter = 'plotly', gp = gp)
def g10_line_plot_cpi(self, start_date, finish_date):
today_root = datetime.date.today().strftime("%Y%m%d") + " "
country_group = 'g10-ez'
cpi = self.get_CPI_YoY(start_date, finish_date, country_group)
from pythalesians.graphics.graphs.plotfactory import PlotFactory
from pythalesians.graphics.graphs.graphproperties import GraphProperties
gp = GraphProperties()
pf = PlotFactory()
gp.title = "G10 CPI YoY"
gp.units = '%'
gp.scale_factor = 3
gp.file_output = today_root + 'G10 CPI YoY ' + str(gp.scale_factor) + '.png'
cpi.columns = [x.split('-')[0] for x in cpi.columns]
gp.linewidth_2 = 3
gp.linewidth_2_series = ['United States']
pf.plot_generic_graph(cpi, type = 'line', adapter = 'pythalesians', gp = gp)
"""
import datetime
from pythalesians.economics.events.histecondatafactory import HistEconDataFactory
from pythalesians.economics.events.popular.commonecondatafactory import CommonEconDataFactory
from pythalesians.util.loggermanager import LoggerManager
# just change "False" to "True" to run any of the below examples
#### Plot US economic data by state using a choropleth Plotly plot
####
if False:
logger = LoggerManager.getLogger(__name__)
hist = HistEconDataFactory()
start_date = '01 Jan 1990'
finish_date = datetime.datetime.utcnow()
country_group = 'usa-states'
yoy_ret = False
# select as appropriate
# data_type = 'Total Nonfarm'; title = 'Change in non-farm payrolls (YoY)'; freq = 12
# data_type = 'Real GDP'; title = 'Real GDP'; freq = 1
# data_type = 'Economic Activity Index'; title = 'Economic Activity Index (YoY change %)'; yoy_ret = True; freq = 12
# data_type = 'Total Construction Employees'; title = Total Construction Employees'; freq = 12
data_type = 'Unemployment Rate'
title = 'Unemployment Rate'
freq = 12
# data_type = 'Total Personal Income'; title = 'Total Personal Income'; freq = 12
# data_type = 'House Price Index'; title = 'House Price Index (YoY change %)'; yoy_ret = True; freq = 12;