def get_indicators_df(area_level, id_len=7):
path = pf.get_indic(area_level)
if not os.path.isfile(path):
return None
else:
df = pd.read_csv(path, encoding="utf-8")
df = replace_index(df, id_len)
return df
def get_indicators_df(area_level, id_len=7):
path = pf.get_indic(area_level)
if not os.path.isfile(path):
return None
else:
df = pd.read_csv(path, encoding="utf-8")
df = replace_index(df, id_len)
return df
def add_indicator(area_level, indic_name, indicator):
indicators = get_or_create_indicators_df(area_level)
if type(indicator) == pd.core.series.Series:
indicators[indic_name] = indicator
elif type(indicator) == dict:
indicators[indic_name] = indicators[IDS_GCBA[area_level]].map(indicator)
else:
raise Exception("Indicator must be dict or ")
indicators.to_csv(pf.get_indic(area_level), encoding="utf-8")
return indicators
def add_indicator(area_level, indic_name, indicator):
indicators = get_or_create_indicators_df(area_level)
if type(indicator) == pd.core.series.Series:
indicators[indic_name] = indicator
elif type(indicator) == dict:
indicators[indic_name] = indicators[
IDS_GCBA[area_level]].map(indicator)
else:
raise Exception("Indicator must be dict or ")
indicators.to_csv(pf.get_indic(area_level), encoding="utf-8")
return indicators
def add_dbf_indicator_by_id(area_level, context_shp_name, context_id_field, context_indic_field):
indicators = get_or_create_indicators_df(area_level)
if context_indic_field in indicators.columns:
indicators.drop(context_indic_field, 1, inplace=True)
dbf = Dbf5(get_context_shp_path(context_shp_name) + ".dbf")
context_df = dbf.to_dataframe()
context_df.drop_duplicates(context_id_field, inplace=True)
context_df.set_index(context_id_field, inplace=True)
indicators = indicators.join(context_df[context_indic_field])
indicators.to_csv(pf.get_indic(area_level), encoding="utf-8")
return indicators
def add_dbf_indicator_by_id(area_level, context_shp_name, context_id_field,
context_indic_field):
indicators = get_or_create_indicators_df(area_level)
indicators.drop(context_indic_field, 1, inplace=True)
dbf = Dbf5(get_context_shp_path(context_shp_name) + ".dbf")
context_df = dbf.to_dataframe()
context_df.drop_duplicates(context_id_field, inplace=True)
context_df.set_index(context_id_field, inplace=True)
indicators = indicators.join(context_df[context_indic_field])
indicators.to_csv(pf.get_indic(area_level), encoding="utf-8")
return indicators
