Man pages for gpw13/billionaiRe
Calculate the WHO Triple Billions
| accelerate_adult_obese | Accelerate adult_obese |
| accelerate_alcohol | Accelerate alcohol |
| accelerate_anc4 | Accelerate anc4 |
| accelerate_art | Accelerate art |
| accelerate_beds | Accelerate beds |
| accelerate_bp | Accelerate bp |
| accelerate_child_obese | Accelerate child_obese |
| accelerate_child_viol | Accelerate child_viol |
| accelerate_cholera | Accelerate cholera |
| accelerate_devontrack | Accelerate devontrack |
| accelerate_dnr | Accelerate Detect, Notify, Respond, and Detect and Respond |
| accelerate_doctors | Accelerate doctors |
| accelerate_dtp3 | Accelerate dtp3 |
| accelerate_espar | Accelerate espar |
| accelerate_fh | Accelerate fh |
| accelerate_fp | Accelerate fp |
| accelerate_fpg | Accelerate fpg |
| accelerate_fuel | Accelerate fuel |
| accelerate_hpop_sanitation | Accelerate hpop_sanitation |
| accelerate_hpop_sanitation_rural | Accelerate hpop_sanitation_rural |
| accelerate_hpop_sanitation_urban | Accelerate hpop_sanitation_urban |
| accelerate_hpop_tobacco | Accelerate hpop_tobacco |
| accelerate_hwf | Accelerate hwf |
| accelerate_ipv | Accelerate ipv |
| accelerate_itn | Accelerate itn |
| accelerate_measles | Accelerate measles |
| accelerate_meningitis | Accelerate meningitis |
| accelerate_nurses | Accelerate nurses |
| accelerate_overweight | Accelerate overweight |
| accelerate_pm25 | Accelerate pm25 |
| accelerate_pneumo | Accelerate pneumo |
| accelerate_polio | Accelerate polio |
| accelerate_road | Accelerate road |
| accelerate_stunting | Accelerate stunting |
| accelerate_suicide | Accelerate suicide |
| accelerate_target_anc4 | Accelerate anc4 to 95% by 2030 |
| accelerate_target_art | Accelerate art to 90.25 by 2025 |
| accelerate_target_beds | Accelerate beds to 18 by 2025 |
| accelerate_target_bp | Accelerate bp |
| accelerate_target_doctors | Accelerate doctors |
| accelerate_target_dtp3 | Accelerate dtp3 |
| accelerate_target_fh | Accelerate fh |
| accelerate_target_fp | Accelerate fp |
| accelerate_target_fpg | Accelerate fpg |
| accelerate_target_hwf | Accelerate hwf |
| accelerate_target_itn | Accelerate itn |
| accelerate_target_nurses | Accelerate nurses |
| accelerate_target_pneumo | Accelerate pneumo |
| accelerate_target_tb | Accelerate tb |
| accelerate_target_uhc_sanitation | Accelerate uhc_sanitation |
| accelerate_target_uhc_tobacco | Accelerate uhc_tobacco |
| accelerate_tb | Accelerate tb |
| accelerate_transfats | Accelerate transfats |
| accelerate_uhc_sanitation | Accelerate uhc_sanitation |
| accelerate_uhc_tobacco | Accelerate uhc_tobacco |
| accelerate_wasting | Accelerate wasting |
| accelerate_water | Accelerate water |
| accelerate_water_rural | Accelerate water_rural |
| accelerate_water_urban | Accelerate water_urban |
| accelerate_yellow_fever | Accelerate yellow_fever |
| add_hep_populations | Add Population Figures for HEP Billion |
| add_hpop_populations | Add Population Figures for HPOP Billion |
| add_missing_xmart_rows | Add missing rows for xMart upload |
| add_populations | Add Population Figures for all billions |
| add_scenario | Add scenario to data frame |
| assert_data_calculation_hep | Assert presence of minimum HEP data |
| assert_data_calculation_hpop | Assert presence of minimum HPOP data |
| assert_data_calculation_uhc | Assert minimum data for UHC calculations |
| billionaiRe_add_columns | Add columns to data frame if not already existing |
| billion_group_mean | Calculate average per Billion group |
| billion_ind_codes | Indicator codes for the Billions |
| calculate_aarc | Calcualte Average annual rate of change |
| calculate_aroc | Calculate Average rate of change |
| calculate_contribution_sums | Calculate global/regional billions contributions |
| calculate_hep_billion | Calculate HEP Billion |
| calculate_hep_components | Calculate HEP component indicators |
| calculate_hepi | Calculate HEPI |
| calculate_hep_prevent_ind | Calculate prevent indicators |
| calculate_hpop_billion | Calculate HPOP Billion |
| calculate_hpop_billion_change | Calculate the HPOP Billion using columns of change |
| calculate_hpop_billion_single | Calculate the HPOP Billion for one column of change |
| calculate_hpop_change_vector | Calculate the change for vectors, used in... |
| calculate_hpop_contributions | Calculate HPOP Indicator Contributions |
| calculate_uhc_billion | Calculate UHC Billion |
| calculate_uhc_billion_single | Calculate UHC Billion for one set of columns |
| calculate_uhc_contribution | Calculate UHC contribution |
| convert_ind_codes | Convert indicator codes between types |
| country_shares | Country shares data |
| exec_scenario | Execute a scenario |
| fill_cols_scenario | Infills scenarios with 'values' when 'cols' are missing... |
| fixed_target | Scenario to reach a fixed target |
| flat_extrapolation | Flat extrapolation |
| generate_hpop_populations | Generate HPOP Population Table |
| get_aarr | Get Average Annual Rate of Reduction |
| get_baseline_value | Get last value from baseline |
| get_baseline_year | Get last year from baseline |
| get_country_shares | Get country shares data |
| get_data_lake_name | Return the name of the 3B data lake |
| get_ind_billion | Denotes which billion a given indicator belongs to |
| get_ind_metadata | Get metadata for a Triple Billions indicator(s) |
| get_last_value | Get last value for the filter |
| get_last_year_scenario | Get last value for the filter in default scenario |
| get_latest_aarc | Get the latest AARC for data frame |
| get_percent_change_aarc | Get AARC for data frame based on a percent change to baseline |
| get_sdi_ratio | Get SDI ratio data |
| get_target_aarc | Get AARC for data frame based on a target |
| get_whdh_path | Generate file paths for the Triple Billions WHDH data lake |
| has_xmart_cols | Check data frame for xMart4 columns |
| hep_df | HEP generated example data |
| hpop_df | HPOP generated example data |
| indicator_df | Dataset of indicators used within the Billions calculations. |
| linear_change | Scenario to add a linear point change |
| load_billion_data | Load Billions indicator data |
| load_billion_data_legacy | Load Raw Billions Indicator Data |
| load_billion_data_whdh | Load Billions indicator data from WHDH |
| load_billion_data_xmart | Load Billions indicator data from xMart |
| load_misc_data | Load miscellaneous data |
| pathogen_calc | Calculate the vaccine coverage for a specific pathogen |
| pipe | Pipe operator |
| pop_links | HPOP Billion population links |
| recycle_data | Recycle data between scenarios |
| reduce_type | Helper to reduce type to unique value |
| remove_recycled_data | Remove recycled values from 'df' |
| remove_unwanted_scenarios | Remove unwanted scenarios from df |
| save_gho_backup_to_whdh | Backup GHO data to the WHDH Data Lake |
| save_wrangled_output | Save the output to disk after ensuring column specs |
| scenario_aroc | Scenario to use the average annual rate of change |
| scenario_bau | Scenario establish a business as usual scenario |
| scenario_best_in_region | Scenario to add a linear percentage point aimed at regional... |
| scenario_best_of | Scenario to pick the best scenario out of a list of scenarios |
| scenario_covid_delayed_return | Scenario COVID delayed return to normal |
| scenario_covid_never_return | Scenario COVID never return to normal |
| scenario_covid_rapid_return | Scenario COVID rapid return to normal |
| scenario_covid_sustained_disruption | Scenario COVID sustained disruption to normal |
| scenario-dip-recover | Scenario dip and recover |
| scenario_percent_baseline | Scenario to change by a fixed percentage from a baseline... |
| scenario_quantile | Scenario to add a linear percentage point aimed at quantiles |
| scenario_return_previous_trajectory | Scenario return to previpus trajectory |
| scenario_top_n_iso3 | Scenario to reach the top performing rate of change countries |
| sdg_adult_obese | Accelerate adult_obese to SDG target |
| sdg_alcohol | Accelerate alcohol to SDG target |
| sdg_anc4 | Accelerate anc4 to SDG target |
| sdg_art | Accelerate art to SDG target |
| sdg_beds | Accelerate beds to SDG target |
| sdg_bp | Accelerate bp to SDG target |
| sdg_child_obese | Accelerate child_obese to SDG target |
| sdg_child_viol | Accelerate child_viol to SDG target |
| sdg_devontrack | Accelerate devontrack to SDG target |
| sdg_doctors | Accelerate doctors to SDG target |
| sdg_dtp3 | Accelerate dtp3 to SDG target |
| sdg_fh | Accelerate fh to SDG target |
| sdg_fp | Accelerate fp to SDG target |
| sdg_fpg | Accelerate fpg to SDG target |
| sdg_fuel | Accelerate fuel to SDG target |
| sdg_hpop_sanitation | Accelerate hpop_sanitation to SDG target |
| sdg_hpop_sanitation_rural | Accelerate hpop_sanitation_rural to SDG target |
| sdg_hpop_sanitation_urban | Accelerate hpop_sanitation_urban to SDG target |
| sdg_hpop_tobacco | Accelerate hpop_tobacco to SDG target |
| sdg_hwf | Accelerate hwf to SDG target |
| sdg_ipv | Accelerate ipv to SDG target |
| sdg_itn | Accelerate itn to SDG target |
| sdg_nurses | Accelerate nurses to SDG target |
| sdg_overweight | Accelerate overweight to SDG target |
| sdg_pm25 | Accelerate pm25 to SDG target |
| sdg_pneumo | Accelerate pneumo to SDG target |
| sdg_road | Accelerate road to SDG target |
| sdg_stunting | Accelerate stunting to SDG target |
| sdg_suicide | Accelerate suicide to SDG targets |
| sdg_tb | Accelerate tb to SDG target |
| sdg_transfats | Accelerate transfats to SDG targets |
| sdg_uhc_sanitation | Accelerate uhc_sanitation to SDG target |
| sdg_uhc_tobacco | Accelerate uhc_tobacco to SDG target |
| sdg_wasting | Accelerate wasting to SDG targets |
| sdg_water | Accelerate water to SDG target |
| sdg_water_rural | Accelerate water_rural to SDG target |
| sdg_water_urban | Accelerate water_urban to SDG target |
| sdi_ratio | Socio-Demographic Index data |
| transform_hep_data | Transform Raw Indicator Values for HEP Billion |
| transform_hpop_data | Transform Raw Indicator Values for HPOP Billion |
| transform_hpop_single | Perform a transformation on a single column |
| transform_prev_cmpgn_data | Transform Prevent campaigns data |
| transform_prev_routine_data | Transform Prevent routine data |
| transform_uhc_data | Transform Raw Indicator Values for UHC Billion |
| transform_uhc_single | Perform a transformation on a single column |
| trim_values | Trim values |
| trim_years | Trim values |
| uhc-benchmarking | Benchmarking scenarios |
| uhc_df | UHC example data |
| untransform_hpop_data | Untransform Indicator Values for HPOP Billion |
| untransform_hpop_single | Perform a transformation on a single column |
| untransform_uhc_data | Untransform Indicator Values for UHC Billion |
| untransform_uhc_single | Perform a transformation on a single column |
| upload_billion_data | Upload Billions indicator data |
| wrangle_gho_data | Put GHO data into billionaiRe format |
| wrangle_gho_rural_urban_data | Wrangle GHO data with TOTL/RUR/URB dimensions |
| wrangle_unsd_data | Put UNSD data into billionaiRe format |
| xmart_cols | Get names of xMart4 columns |
| xmart_col_types | Get the column types for xMart columns |
