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)
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 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 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_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 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 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 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 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)
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)
df = hist.grasp_coded_entry(df, -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_url = country_group + data_type.replace(' ', '-')
gp.plotly_world_readable = False
gp.title = title
gp.units = 'Value'
# do a map plot by US state
pf.plot_generic_graph(df, type = 'choropleth', adapter = 'cufflinks', gp = gp)
#### uses CommonEconDataFactory to get more common forms of economic data and plot
####
if True:
logger = LoggerManager.getLogger(__name__)
cedf = CommonEconDataFactory()
start_date = '01 Jan 2014'
finish_date = datetime.datetime.utcnow()
# select as appropriate!
# cedf.g10_plot_gdp_cpi_une(start_date, finish_date)
df = hist.grasp_coded_entry(df, -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_url = country_group + data_type.replace(' ', '-')
gp.plotly_world_readable = False
gp.title = title
gp.units = 'Value'
# do a map plot by US state
pf.plot_generic_graph(df, type='choropleth', adapter='cufflinks', gp=gp)
#### uses CommonEconDataFactory to get more common forms of economic data and plot
####
if True:
logger = LoggerManager.getLogger(__name__)
cedf = CommonEconDataFactory()
start_date = '01 Jan 2014'
finish_date = datetime.datetime.utcnow()
# select as appropriate!
# cedf.g10_plot_gdp_cpi_une(start_date, finish_date)