def update_backup(self):
day_after = self.df_fra_backup.index[-1] + pandas.Timedelta(1,
unit='d')
self.df_fra_backup = pandas.concat([
self.df_fra_backup.loc[:, ['cases']],
self.df_fra_nat.loc[day_after:, ['cases']]
])
df_fct.export_df([['Fra_Backup', self.df_fra_backup]], ['raw'])
def main(self):
self.clean_up_CountryLatLong()
self.clean_up_WorldShp()
self.clean_up_pop_World()
self.append_data_world()
df_fct.export_df([['World_pop', self.World_pop]], ['processed'])
return self.World_JH
def main(self):
self.clean_up_testing_1()
self.clean_up_testing_2()
self.concat_testing()
df_fct.export_df([['Fra_Testing', self.fra_testing]], ['processed'])
return self.fra_testing
def main(self):
self.clean_up_USShp()
self.clean_up_pop_US()
self.clean_up_data_US()
self.df_us = self.append_data('df_us', 'US_States_shapefile', 'US_pop')
self.df_us = self.rel_values('df_us')
df_fct.export_df([['US_pop', self.US_pop]], ['processed'])
return self.df_us
def main(self):
self.indic_nat()
self.indic_dpt()
df_fct.export_df([['Fra_Indic_Nat', self.df_indic_nat],
['Fra_Indic_Dpt_graph', self.df_indic_dpt_graph]],
['processed', 'processed'])
return self.df_indic_dpt_map
def main(self):
self.clean_up_nat()
self.clean_up_reg()
self.clean_up_dpt()
df_fct.export_df(
[['Fra_Nat', self.df_fra_nat], ['Fra_Reg', self.df_fra_reg],
['Fra_Dpt', self.df_fra_dpt], ['Fra_Backup', self.df_fra_backup]],
['processed', 'processed', 'processed', 'processed'])
def main(self, period, center):
self.import_db()
self.clean_up_JH()
#self.clean_up_Fra_gen ()
self.ajust_values()
self.complete_data()
self.smooth(period, center)
self.remove_neg_val()
df_fct.export_df([['World_JH', self.df_world]], ['processed'])
return self.df_world
def clean_up_nat_v2(self):
self.df_fra_nat_v2 = self.df_fra_test[0]
self.df_fra_nat_v2.loc['jour'] = pandas.to_datetime(
self.df_fra_nat_v2['jour'], format='%Y-%m-%d')
self.df_fra_nat_v2 = self.df_fra_nat_v2[self.df_fra_nat_v2['cl_age90']
== 0]
self.df_fra_nat_v2 = self.df_fra_nat_v2.set_index(
pandas.DatetimeIndex(self.df_fra_nat_v2['jour']))
self.df_fra_nat_v2 = self.df_fra_nat_v2[['P', 'T']]
self.df_fra_nat_v2.index = self.df_fra_nat_v2.index.rename('date')
self.df_fra_nat_v2 = self.df_fra_nat_v2.rename(columns={
'P': 'cases',
'T': 'tests'
})
df_fct.export_df([
['Fra_Nat_v2', self.df_fra_nat_v2],
], [
'processed',
])
def main(self):
self.clean_up_testing()
df_fct.export_df([['US_Testing', self.us_testing]], ['processed'])
return self.us_testing
def main(self):
self.clean_up_vax()
df_fct.export_df([['Fra_Vax', self.data_vax]], ['processed'])
return self.data_vax
