def scatter_reporting_district_data(*, indicator, district, target_year,
target_month, reference_year,
reference_month, **kwargs):
db = Database()
df = db.rep_data
indicator = db.switch_indic_to_numerator(indicator, popcheck=False)
df = db.filter_by_indicator(df, indicator)
df = filter_by_district(df, district)
date_list = get_date_list(target_year, target_month, reference_year,
reference_month)
min_date = min(date_list[0], date_list[3])
max_date = max(date_list[0], date_list[3])
df = df[(df.date >= min_date) & (df.date <= max_date)]
title = f'Percentages of facilities reporting on their 105:1 form, and percentage of reporting facilities that reported a value of one or above for {db.get_indicator_view(indicator)} in {district} district'
df = df.rename(columns={indicator: title})
return df
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 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 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_reporting_compare_data(
*,
indicator,
target_year,
target_month,
reference_year,
reference_month,
report_map_compare_agg,
**kwargs,
):
db = Database()
df = db.rep_data
indicator = db.switch_indic_to_numerator(indicator, popcheck=False)
df = db.filter_by_indicator(df, indicator)
df = get_df_compare(
df,
indicator,
target_year,
target_month,
reference_year,
reference_month,
report_map_compare_agg,
report=True,
)
if report_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 proportion of reporting facilities that reported a non-zero number for
{db.get_indicator_view(indicator)} by district between
{quarter}{reference_month}-{reference_year} and {target_month}-{target_year}"""
df = df.rename(columns={indicator: title})
return df
def map_reporting_period_data(
*,
indicator,
target_year,
target_month,
reference_year,
reference_month,
report_map_period_agg,
**kwargs,
):
db = Database()
df = db.rep_data
indicator = db.switch_indic_to_numerator(indicator, popcheck=False)
df = db.filter_by_indicator(df, indicator)
df = get_df_period(
df,
indicator,
target_year,
target_month,
reference_year,
reference_month,
report_map_period_agg,
report=True,
)
if report_map_period_agg == "Show only month of interest":
title = f"""Proportion of reporting facilities that reported a non-zero number for
{db.get_indicator_view(indicator)} on {reference_month}-{reference_year}"""
else:
title = f"""Average proportion of reporting facilities that reported a non-zero number for
{db.get_indicator_view(indicator)} between {reference_month}-{reference_year} and {target_month}-{target_year}"""
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
def overview_data(
*,
outlier,
target_year,
target_month,
reference_year,
reference_month,
**kwargs,
):
db = Database()
df = db.raw_data
df = filter_df_by_dates(df, target_year, target_month, reference_year,
reference_month)
return df
def get_title_country_overview(data, indicator_view_name, **controls):
"""
get title for the first section based on a percentage calcution and the inputs
"""
country_descrip = get_time_diff_perc(data, **controls)
title = f"""Overview: Across the country, the {indicator_view_name} {country_descrip}
between {controls.get('reference_month')}-{controls.get('reference_year')}
and {controls.get('target_month')}-{controls.get('target_year')} """
return title
# DATACARD 1 #
db = Database()
# TODO The class would need to include this title function by default to avoid repetition
default_title = get_title_country_overview(
scatter_country_plot(init_data_set),
db.get_indicator_view(DEFAULTS.get("indicator")),
**DEFAULTS,
)
country_overview_scatter = ChartDataCard(
title=default_title,
fig_title="$label$",
data=init_data_set,
data_transform=scatter_country_plot,
fig_type="Scatter",
@timeit
def scatter_facility_plot(data):
data = data.get("facility")
data = data[data[data.columns[-1]] > 0]
data = get_year_and_month_cols(data)
data = get_sub_dfs(data, "year", YEARS, "month")
return data
# DATACARD 4 #
db = Database()
dropdown = NestedDropdown(
id="treemap-agg-dropdown",
options=[
"Show only month of interest",
"Show sum between month of reference and month of interest period",
"Show average between month of reference and month of interest period",
],
visible_id=False,
)
tree_map_district = AreaDataCard(
fig_title="$label$",
data=init_data_set,
data_transform=tree_map_district_dated_plot,
def get_title_reporting_country(data, indicator_view_name, **controls):
"""
get title for the reporting section based on a percentage calculation and the inputs
"""
descrip_reported, descrip_positive = get_report_perc(data, **controls)
title = f'''Reporting: on {controls.get('target_month')}-{controls.get('target_year')},
{descrip_reported} of facilities reported on their 105:1 form, and, out of those,
{descrip_positive} reported one or above for {indicator_view_name}'''
return title
# DATACARD 5 #
db = Database()
default_title = get_title_reporting_country(
bar_reporting_country_plot(init_data_set),
db.get_indicator_view(DEFAULTS.get('indicator')), **DEFAULTS)
stacked_bar_reporting_country = ChartDataCard(
data=init_data_set,
data_transform=bar_reporting_country_plot,
title=default_title,
fig_title="$label$",
fig_object="Scatter",
trace_params=bar_reporting_country_plot_tooltip(init_data_set),
)
stacked_bar_reporting_country.set_colors({