surveyweathertool.src.survey.balanced_dataset_poverty_indicators

Module Contents

Functions

merge_all(→ pandas.DataFrame)

Merges all survey dataframes into one.

balanced_panel_analysis(→ pandas.DataFrame)

Not fully completed balanced panel creation for Child <18 and waves 1 & 2 and 3

make_health_dimension_columns(df)

Applies health filters to make a column of a value indicating both whether or not a household/individual is deprived and the severity of this deprivation

make_housing_dimension_columns(df)

Applies shelter, sanitation, and water filters to make a column of a value indicating both whether or not a household/individual is deprived and the severity of this deprivation

make_education_dimension_columns(df)

make_nutrition_dimension_columns(df)

create_unicef_poverty_index(→ pandas.DataFrame)

From the combined raw survey data, create the poverty index based on UNICEF definition/conditions.

surveyweathertool.src.survey.balanced_dataset_poverty_indicators.merge_all(roster: pandas.DataFrame, df_list: list[pandas.DataFrame]) pandas.DataFrame

Merges all survey dataframes into one.

METHODOLOGY

Current methodology is to left join all the individual subdomains onto the survey ‘roster’ file.

This is because the survey roster contains all the (hhid,indiv,wave,visit) combinations ever recorded in any part of the survey

surveyweathertool.src.survey.balanced_dataset_poverty_indicators.balanced_panel_analysis(processed_filepath: str, domains_to_merge: List, data_format: str) pandas.DataFrame

Not fully completed balanced panel creation for Child <18 and waves 1 & 2 and 3

surveyweathertool.src.survey.balanced_dataset_poverty_indicators.make_health_dimension_columns(df)

Applies health filters to make a column of a value indicating both whether or not a household/individual is deprived and the severity of this deprivation

Keyword arguments: filepath (Path) - Path to health csv

NOTES

health_indicator_values = [0,1,2], 0 if no data or not poor. 1 if moderate, 2 if severe

surveyweathertool.src.survey.balanced_dataset_poverty_indicators.make_housing_dimension_columns(df)

Applies shelter, sanitation, and water filters to make a column of a value indicating both whether or not a household/individual is deprived and the severity of this deprivation

Keyword arguments: filepath (Path) - Path to health csv

NOTES

shelter_indicator_values = [0,1,2], 0 if no data or not poor. 1 if moderate, 2 if severe sanitation_indicator_values = [0,1,2], 0 if no data or not poor. 1 if moderate, 2 if severe shelter_indicator_values = [0,1,2], 0 if no data or not poor. 1 if moderate, 2 if severe

surveyweathertool.src.survey.balanced_dataset_poverty_indicators.make_education_dimension_columns(df)
surveyweathertool.src.survey.balanced_dataset_poverty_indicators.make_nutrition_dimension_columns(df)
surveyweathertool.src.survey.balanced_dataset_poverty_indicators.create_unicef_poverty_index(df: pandas.DataFrame) pandas.DataFrame

From the combined raw survey data, create the poverty index based on UNICEF definition/conditions.

REFERENCE

Please see XXXX link for UNICEF definitions