The API endpoint is the following
| Variable Code | Data Type | Accept Null Value | Description | Filtering available in the API |
|---|---|---|---|---|
| id | int | FALSE | Go project id | FALSE |
| project_country_detail | dict | FALSE | Details of the country associated with the project | |
| project_country | int | FALSE | Id of the country associated with the project | FALSE |
| project_districts_detail | list | FALSE | Details of the districts associated with the project | FALSE |
| project_districts | list | FALSE | ID/tags of the districts associated with the project | TRUE |
| reporting_ns_detail | dict | FALSE | Reporting National Society details | |
| reporting_ns | int | FALSE | Id of the National Society | TRUE |
| dtype_detail | dict | TRUE | Type of disaster according to IFRC categories. There are 22 different categories, each appeal is related to one type of category (e.g. Epidemic, Flood, Complex Emergency | |
| dtype | int | FALSE | Id associated with the disaster | FALSE |
| project_admin2_detail | list | |||
| project_admin2 | list | |||
| regional_project_detail | TRUE | FALSE | ||
| regional_project | TRUE | FALSE | ||
| event_detail | dict | TRUE | Details of the associated emergency event | |
| event | int | FALSE | Id associated with the event | FALSE |
| primary_sector_display | str | FALSE | Primary sector associated with the project * | FALSE |
| primary_sector | int | TRUE | Id of the primary sector associated with the project * | TRUE |
| programme_type_display | str | FALSE | Programme type of the project (0 - Bilateral, 1 - Multilateral, 2 - Domestic) | FALSE |
| programme_type | int | TRUE | Id of the programme type (0 - Bilateral, 1 - Multilateral, 2 - Domestic) | TRUE |
| operation_type_display | str | FALSE | Operation type of the project (0 - Programme, 1 - Emergency Operation) | FALSE |
| operation_type | int | TRUE | Key - value pairs of the operation type (0 - Programme, 1 - Emergency Operation) | TRUE |
| status_display | str | FALSE | Status of the Project ( 0 - Planned, 1 - Outgoing, 2 - Completed) | FALSE |
| status | int | FALSE | Id for the status of the project ( 0 - Planned, 1 - Outgoing, 2 - Completed) | TRUE |
| visibility_display | str | FALSE | Visibility of the project (e.g.. Public) | FALSE |
| visibility | str | FALSE | Visibility of the project (e.g.. Public) | FALSE |
| secondary_sectors_display | list | TRUE | Secondary sector associated with the project ** | FALSE |
| secondary_sectors | list | TRUE | Tag of the secondary sector associated with the project ** | TRUE |
| modified_by_detail | dict | TRUE | Details of the national society and the staff member that modified the project details | |
| modified_by | int | FALSE | Id of the staff member of the National society responsible for modification of project details | FALSE |
| modified_at | str | FALSE | Project modification date. Format: YYYY-MM-DDT00:00:00Z | TRUE |
| start_date | str | FALSE | Start date of the project. Format: YYYY-MM-DD | TRUE |
| end_date | str | FALSE | End date of the project. Format: YYYY-MM-DD | TRUE |
| budget_amount | int | TRUE | Budget amount allocated for the project | TRUE |
| actual_expenditure | int | TRUE | Actual expenditure associated with the project | FALSE |
| target_male | int | TRUE | Total target males through the project | FALSE |
| target_female | int | TRUE | Total target females through the project | FALSE |
| target_other | int | TRUE | Other population targeted through the project | FALSE |
| target_total | int | TRUE | Total target population of the project | FALSE |
| reached_male | int | TRUE | Number of males reached through the project | FALSE |
| reached_female | int | TRUE | Number of females reached through the project | FALSE |
| reached_other | int | TRUE | Other population reached through the project | FALSE |
| reached_total | int | TRUE | Total population reached through the project | FALSE |
| user | int | FALSE | FALSE | |
| name | str | FALSE | Name of the project | TRUE |
programme_type:The data of projects carried out can be filtered out by the programme type. e.g.: https://goadmin.ifrc.org/api/v2/project/?programme_type=0. This will filter out all the bilateral projects. To filter out data for more than one primary sector, following example can be used. https://goadmin.ifrc.org/api/v2/project/?programme_type=0%2C1. This will filter out the projects having bilateral and multilateral programme types. primary_sector:The data of projects can be filtered out by specifying the code for the primary sector. e.g.: https://goadmin.ifrc.org/api/v2/project/?primary_sector=0. This will filter out the projects that have WASH as the primary sector. To filter out data for more than one primary sector, following example can be used. https://goadmin.ifrc.org/api/v2/project/?primary_sector=1%2C2. This example will filter out the projects associated with PGI and CEA primary sectors.secondarysectors:To filter out the data of projects according to any secondary sector, following example can be used. https://goadmin.ifrc.org/api/v2/project/?secondarysectors=1. The secondary_sectors parameter is a list and can contain more than one secondary sector associated with a project. This example will filter out all the projects which contain PGI as a secondary sector. To filter out data with more than ne secondary sector users can use the following example. https://goadmin.ifrc.org/api/v2/project/?secondary_sectors=1&secondary_sectors=2&secondary_sectors=3. This example will filter out the projects associated with PGI, CEA and Migration secon dary sectors.operation_type:We can filter out the projects based on operation type using the following example. https://goadmin.ifrc.org/api/v2/project/?operation_type=1. This will filter out the projects having operation type as emergency operation.start_date:The following example can be used to filter out the projects based on start date. https://goadmin.ifrc.org/api/v2/project/?start_date=2012-01-01. This will provide the data of all projects whose start date was 2012-01-01. end_date:The following example can be used to filter out the projects based on end date. https://goadmin.ifrc.org/api/v2/project/?end_date=2013-12-31. This will provide the data of all projects whose end date is 2013-12-31. budget_amount:Projects can also be filtered based on budget amount. e.g.: https://goadmin.ifrc.org/api/v2/project/?budget_amount=896694. This project is associated with forecast based financing response preparedness programme in Ethiopia. status:To filter out ongoing projects the following example can be used. https://goadmin.ifrc.org/api/v2/project/?status=1. Since there are only three statuses associated with projects data, in order to filter out all three of them, following example can be used. https://goadmin.ifrc.org/api/v2/project/?status=0&status=1&status=2reporting_ns:The projects can also be filtered out based on the reporting national Red Cross or Red Crescent Society. https://goadmin.ifrc.org/api/v2/project/?reporting_ns=124. This example will filter out the projects being carried out by the Ugandan Red Cross Society. project_districts:This parameter is a list and it can be used to filter out the projects according to the districts where they are carried out. e.g.: https://goadmin.ifrc.org/api/v2/project/?project_districts=3505. This will give the projects where district number 3505 is mentioned in the project_districts list. At the moment this example filters out the projects carried out in the districts of Zambia.name:You can filter the table through a general search. e.g.: https://goadmin.ifrc.org/api/v2/project/?search=settlementcountry_iso3:The ISO3 codes of countries can also be used to filter out the project data. e.g.: https://goadmin.ifrc.org/api/v2/project/?country_iso3=IND&country_iso3=NPL. This example will filter out the data of projects in Indian and Nepal. country: The country ids can also be used to filter out the projects data. e.g.: https://goadmin.ifrc.org/api/v2/project/?country=84&country=123. This example will filter out the data for India and Nepal.
*The key value pairs for the primary sectors associated with projects data are the following: 0 - WASH, 1 - PGI, 2 - CEA, 3 - Migration, 4 - Health (Public), 5 - DRR, 6 - Shelter, 7 - NS strengthening, 8 - Education, 9 - Livelihood and basic needs.
**There are several secondary sector categories that can be associated with a primary sector category namely: CEA, COVID-19, DRR, Education, Health (Public), Health (Clinical), Internal displacement, Livelihoods and basic needs, Migration, NS strengthening, PGI, Recovery, Shelter, WASH etc.