def __create_measures(self):
df_cym, df_cyd, df_pmt, df_hr_scorecard, df_hr_absences, df_hr_sickness, df_hr_training, df_dcs_complaints = self.get_data_frames()
if df_cym is None:
raise RGError('Unable to create measures from invalid data frame object [{}]'.format(df_cym))
self.__entities = list()
d_list = list()
m_list = list()
m_ids = set()
for idx, line in df_cym.iterrows():
m = RGMeasureFactory.create_measure(m_type=get_val(line, MEASURE_TYPE).upper(), df=line)
m_ids.add(m.m_id)
m_list.append(m)
for idx, line in df_cyd.iterrows():
d_list.append(RGDataFactory.create_data(m_type=get_val(line, MEASURE_TYPE).upper(), df=line))
m_ids = sorted(m_ids)
m_list.sort(key=lambda x: x.m_id)
d_list.sort(key=lambda x: x.m_id)
for m_id in m_ids:
m_cfy = None
m_lfy = None
d_cfy = None
d_lfy = None
for m in m_list:
if m.m_id == m_id:
if m.f_year == get_cfy_prefix(cfy=self.year):
m_cfy = m
continue
if m.f_year == get_lfy_prefix(cfy=self.year):
m_lfy = m
continue
if m_cfy is not None:
d_cfy = self.__get_data_for_measure(m_cfy, d_list)
if m_lfy is not None:
d_lfy = self.__get_data_for_measure(m_lfy, d_list)
if m_cfy is not None and m_lfy is not None and \
d_cfy is not None and len(d_cfy) > 0 and \
d_lfy is not None and len(d_lfy) > 0:
self.__entities.append(
RGEntityFactory.create_entity(m_type=m_cfy.m_type, data_cfy=d_cfy, data_lfy=d_lfy,
measure_cfy=m_cfy, measure_lfy=m_lfy))
# parse unknown data frame
self.__parse_abnormal_data(df_pmt, PMT_ADDITIONAL)
self.__parse_abnormal_data(df_hr_scorecard, HR_SCORECARD)
self.__parse_abnormal_data(df_hr_absences, HR_ABSENCES)
self.__parse_abnormal_data(df_hr_sickness, HR_SICKNESS)
self.__parse_abnormal_data(df_hr_training, HR_TRAINING)
self.__parse_abnormal_data(df_dcs_complaints, DCS_COMPLAINTS)
logging.debug('[{}] entities has been parsed'.format(len(self.__entities)))
def __init__(self, m_type=HR_ABSENCES, df=None):
HrDataModel.__init__(self, m_type=m_type, df=df)
self.adult_social_care = get_val(df, ADULTS_SOCIAL_CARE, is_float=True)
self.education_and_skills = get_val(df,
EDUCATION_AND_SKILLS,
is_float=True)
self.inclusive_growth = get_val(df, INCLUSIVE_GROWTH, is_float=True)
self.finance_and_governance = get_val(df,
FINANCE_AND_GOVERNANCE,
is_float=True)
self.neighbourhoods = get_val(df, NEIGHBOURHOODS, is_float=True)
self.pip = get_val(df,
PARTNERSHIPS_INSIGHT_AND_PREVENTION,
is_float=True)
self.digital_and_customer_services = get_val(
df, DIGITAL_AND_CUSTOMER_SERVICES, is_float=True)
self.hr_and_od = get_val(df,
HR_AND_ORGANISATION_DEVELOPMENT,
is_float=True)
self.bcc = get_val(df, BIRMINGHAM_CITY_COUNCIL, is_float=True)
self.cwg = get_val(df, COMMONWEALTH_GAMES, is_float=True)
def __init__(self, m_type=None, df=None):
if m_type is None or df is None:
raise RGError(
'Invalid measure type [{}] or data frame [{}] provided'.format(
m_type, df))
self.m_type = m_type
self.f_year = get_val(df, FISCAL_YEAR)
self.m_id = get_val(df, MEASURE_ID)
self.m_ref_no = get_val(df, MEASURE_REF_NO)
self.m_title = get_val(df, MEASURE_TITLE)
self.month = get_val(df, MONTH)
if self.m_title is None:
self.m_title = get_val(df, MEASURE)
self.year = get_val(df, YEAR)
self.year_month = get_val(df, YEAR_MONTH)
def __init__(self, m_type=PMT_ADDITIONAL, df=None):
RGModelBase.__init__(self, m_type=m_type, df=df)
self.frequency = get_val(df, FREQUENCY, is_str=True)
self.quarter = get_val(df, QUARTER, is_str=True)
self.measure_text_column_1 = get_val(df,
MEASURE_TEXT_COLUMN_1,
is_str=True)
self.measure_text_column_2 = get_val(df,
MEASURE_TEXT_COLUMN_2,
is_str=True)
self.dmt_sign_off_date = get_val(df, DMT_SIGN_OFF_DATE, is_date=True)
self.cabinet_members_sign_off_date = get_val(
df, CABINET_MEMBERS_SIGN_OFF_DATE, is_date=True)
def __init__(self, m_type=None, df=None):
RGModelBase.__init__(self, m_type=m_type, df=df)
self.m_desc = get_val(df, MEASURE_DESCRIPTION)
self.frequency = get_val(df,
FREQUENCY_MONTHLY_QUARTERLY_1_2_YEARLY_ANNUAL,
is_str=True)
self.outcome = get_val(df, OUTCOME, is_str=True)
self.outcome_no = get_val(df, OUTCOME_NO, is_int=True)
self.outcome_priority_no = get_val(df,
OUTCOME_PRIORITY_NO,
is_int=True)
self.priority = get_val(df, PRIORITY)
self.additional_kpi_information = get_val(df, ADDITIONAL_KPI_INFO)
self.new_existing = get_val(df, NEW_EXISTING)
self.pref_dot = get_val(df, PREFERRED_DOT)
self.aim = get_val(df, AIM)
self.data_format = get_val(df, DATA_FORMAT, is_str=True)
self.data_presented = get_val(df, DATA_PRESENTED)
self.baseline = get_val(df, BASELINE, is_float=True)
self.tolerance = get_val(df, TOLERANCES)
self.directorate = get_val(df, DIRECTORATE)
self.cabinet_member_portfolio = get_val(df, CABINET_MEMBER_PORTFOLIO)
self.corporate_director = get_val(df, CORPORATE_DIRECTOR)
self.responsible_officer = get_val(df, RESPONSIBLE_OFFICER)
self.measure_owner = get_val(df, MEASURE_OWNER)
self.data_source = get_val(df, DATA_SOURCE)
self.expected_availability = get_val(df, EXPECTED_AVAILABILITY)
self.final_dqaf_received = get_val(df, FINAL_DQAF_RECEIVED)
self.theme = get_val(df, THEME)
self.theme_priority_no = get_val(df, THEME_PRIORITY_NO)
def __init__(self, m_type=None, df=None):
RGModelBase.__init__(self, m_type=m_type, df=df)
self.frequency = get_val(df, FREQUENCY, is_str=True)
self.quarter = get_val(df, QUARTER)
self.result = get_val(df, RESULT)
self.target = get_val(df, TARGET)
self.performance = get_val(df, PERFORMANCE)
self.variance_from_target = get_val(df, VARIANCE_FROM_TARGET)
self.dot_from_previous_month = get_val(df,
DOT_FROM_PREVIOUS_MONTH,
is_str=True)
self.dot_from_previous_quarter = get_val(df,
DOT_FROM_PREVIOUS_QUARTER,
is_str=True)
self.dot_from_same_period_last_year = get_val(
df, DOT_FROM_SAME_PERIOD_LAST_YEAR, is_str=True)
self.status = get_val(df, STATUS_PROVISIONAL_CONFIRMED, is_str=True)
self.d_comments = get_val(df, DIRECTORATE_COMMENTARY, is_str=True)
self.r_comments = get_val(df, REPORT_COMMENTARY, is_str=True)
self.bck_nationally = get_val(df,
BENCHMARKABLE_NATIONALLY,
is_str=True)
self.bck_result = get_val(df, BENCHMARK_RESULT, is_float=True)
self.bck_group = get_val(df,
BENCHMARK_GROUP_FOR_REPORTING_PURPOSES,
is_str=True)
self.brum_result_at_bck = get_val(
df, BIRMINGHAM_RESULT_AT_TIME_OF_BENCHMARK, is_float=True)
self.brum_quartile_pos = get_val(df,
BIRMINGHAM_QUARTILE_POSITION,
is_str=True)
self.year_of_bck_data = get_val(df,
YEAR_OF_BENCHMARK_DATA,
is_str=True)
self.reason_of_no_national_bck = get_val(
df, REASON_FOR_NON_NATIONAL_BENCHMARK_IF_RELEVANT, is_str=True)
self.quartile_projection = get_val(df, QUARTILE_PROJECTION)
self.assistant_director_sign_off = get_val(
df, ASSISTANT_DIRECTOR_SIGN_OFF)
self.dmt_sign_off_date = get_val(df, DMT_SIGN_OFF_DATE)
self.cabinet_mem_sign_off_date = get_val(
df, CABINET_MEMBERS_SIGN_OFF_DATE)
self.year_quarter = get_val(df, YEAR_QUARTER)
def __init__(self, m_type=None, df=None):
RGModelBase.__init__(self, m_type=m_type, df=df)
self.data_format = get_val(df, DATA_FORMAT)
def __init__(self, m_type=HR_SICKNESS, df=None):
HrDataModel.__init__(self, m_type=m_type, df=df)
self.total = get_val(df, TOTAL, is_int=True)
self.percentage = get_val(df, PERCENTAGE, is_float=True)