def tree_map_district_dated_data(
*,
outlier,
indicator,
district,
target_year,
target_month,
reference_year,
reference_month,
trends_treemap_agg,
**kwargs,
):
db = Database()
df = db.raw_data
indicator = db.switch_indic_to_numerator(indicator)
df = db.filter_by_indicator(df, indicator)
df = filter_by_district(df, district)
df = get_ratio(df, indicator, agg_level="facility")[0]
isratio = get_ratio(df, indicator, agg_level="facility")[2]
df_district_dated = get_df_period(
df,
indicator,
target_year,
target_month,
reference_year,
reference_month,
trends_treemap_agg,
index=["id", "facility_name"],
isratio=isratio,
)
if trends_treemap_agg == "Show only month of interest":
agg = "Contribution"
period = f"on {target_month}-{target_year}"
else:
period = f"between {reference_month}-{reference_year} and {target_month}-{target_year}"
if trends_treemap_agg == "Show sum between month of reference and month of interest period":
if isratio:
agg = "Average contribution"
else:
agg = "Total contribution"
else:
agg = "Average contribution"
title = f"""{agg} of individual facilities in {district} district to
{db.get_indicator_view(indicator)} {period}"""
df_district_dated = df_district_dated.rename(columns={indicator: title})
return df_district_dated
def scatter_facility_data(*, outlier, indicator, district, facility, **kwargs):
db = Database()
df = db.raw_data
indicator = db.switch_indic_to_numerator(indicator)
df = db.filter_by_indicator(df, indicator)
df = filter_by_district(df, district)
df, index = get_ratio(df, indicator, agg_level="facility")[0:2]
if not facility:
facility = (df.sort_values(
df.columns[-1], ascending=False).reset_index().facility_name[0])
df = df[df.facility_name == facility].reset_index(drop=True)
title = f"Evolution of {db.get_indicator_view(indicator)} in {facility}"
df = df.rename(columns={indicator: title})
df = df.set_index(index)
return df
def map_bar_country_period_data(
*,
outlier,
indicator,
target_year,
target_month,
reference_year,
reference_month,
trends_map_period_agg,
**kwargs,
):
db = Database()
df = db.raw_data
df = db.filter_by_indicator(df, indicator)
df, _, isratio = get_ratio(df, indicator, agg_level="district")
df = get_df_period(
df,
indicator,
target_year,
target_month,
reference_year,
reference_month,
trends_map_period_agg,
isratio=isratio,
)
if trends_map_period_agg == "Show only month of interest":
title = (
title
) = f"Total {db.get_indicator_view(indicator)} on {target_month}-{target_year} by district"
else:
if trends_map_period_agg == "Show sum between month of reference and month of interest period":
if isratio:
data = "Average"
else:
data = "Total"
else:
data = "Average"
title = f"{data} {db.get_indicator_view(indicator)} between {reference_month}-{reference_year} and {target_month}-{target_year}"
df = df.rename(columns={indicator: title})
return df
def scatter_country_data(*, outlier, indicator, **kwargs):
# dfs, static,
db = Database()
df = db.raw_data
df = db.filter_by_indicator(df, indicator)
df, index = get_ratio(df, indicator, agg_level="country")[0:2]
df = df.set_index(index)
title = f"Total {db.get_indicator_view(indicator)} across the country"
df = df.rename(columns={indicator: title})
return df
def scatter_district_data(*, outlier, indicator, district, **kwargs):
db = Database()
df = db.raw_data
df = db.filter_by_indicator(df, indicator)
df = filter_by_district(df, district)
df, index = get_ratio(df, indicator, agg_level="district")[0:2]
df = df.set_index(index)
title = f"Total {db.get_indicator_view(indicator)} in {district} district"
df = df.rename(columns={indicator: title})
return df
def map_bar_country_compare_data(
*,
outlier,
indicator,
target_year,
target_month,
reference_year,
reference_month,
trends_map_compare_agg,
**kwargs,
):
db = Database()
df = db.raw_data
df = db.filter_by_indicator(df, indicator)
df = get_ratio(df, indicator, agg_level="district")[0]
df = get_df_compare(
df,
indicator,
target_year,
target_month,
reference_year,
reference_month,
trends_map_compare_agg,
)
if trends_map_compare_agg == "Compare quarters averages, using the three month periods ending on month of interest and month of reference":
quarter = "the three months periods ending in "
else:
quarter = ""
title = f"Percentage change in {db.get_indicator_view(indicator)} between {quarter}{reference_month}-{reference_year} and {target_month}-{target_year}"
df = df.rename(columns={indicator: title})
return df