The FIC IPC Acute Food Insecurity Classifications domain provides Food Insecurity Classification (FIC) data as an indicator to identify famine and determine the severity of food security and nutrition crises. This data is compatible with the Integrated Phase Classification (IPC) system.
The FIC IPC Acute Food Insecurity Classifications domain is broken into three two sections:
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Filter
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You can filter the available data series using one or more of the following criteria:
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Period: Filters by the collection/reporting period.
Start date:
End date:
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Data
The Acute Food Insecurity Classifications domain includes the following options for filtering data:
Start date and End date:Filters Data Series by the period dates of all Data Points within the series. All Data Series with at least one Data Point that has a period date inside the date range will be displayed.
Geographic area: Filters by location of the FIC data. This filter aggregates items into
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multi-level lists (e.g.,
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Admin 1 units are aggregated into countries, which are aggregated into regions). Selecting the higher-level item in the list will automatically select all the lower-level items in the list.
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You must select one or more geographic areas before choosing additional filters. |
Scale
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: Filers by the food security classification scale used
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, e.g.,
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*You can search using any of the above criteria marked with an asterisk. You can also search, but not filter, by:
Data Source Document: The name of the document used as the primary source of information or data.
Data Source Organization: The name or unique numeric id of the organization that provided the data source document.
Geographic unit name and code: Name and/or code of a geographic area or point such as a portion of a country or other region delineated for a specific purpose, such as an Administrative Unit (Province, District, County, etc.), Livelihood Zone, or Market.
Scenario code:
2. Data Selection
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Once you have applied your search terms and filters, you will be presented with a list of all available data series that match your criteria. A data series is a collection of related data points from a single data source that are viewable as a single row within a table of data. They represent the change over time of a specific indicator. Data series are presented in table format where each row represents a single data series. The IPC FIC domain data selection table includes the following columns:
In addition to selecting data series, you can interact with the data selection table in the following ways:
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3. Data Visualization and Export
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Options within the IPC FIC domain allows for aggregation or conversion of the data. The available parameters are:
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The Table tab for the IPC FIC domain includes the following metadata:
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The Export tab includes the following options:
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Integrated Phase Classification (IPC) scale versions 2.0, 3.0 and 3.1.
Scenario: There are two scenario options available:
Best Available: Shows the current situation for all periods. Only the most recent near and medium term projections will be included.
All: Shows all scenarios for all periods, including near and medium term projections from past periods.
Data usage policy: Filters by the data usage policy assigned to the Data Series.
2. Data Visualization and Export
Visualize
The Acute Food Insecurity Classifications domain currently includes a Table visualization. The Metadata tab contains descriptions and definitions of the metadata included in the visualizations and export data.
Customize Export
The Acute Food Insecurity Classifications domain includes the following options:
File format: Choose from one of the available file formats. This will apply to both downloads and refreshable links.
Download: Provides a download of a static dataset. This will export only the data series that you have selected.
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Flat format CSV
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Copy link: Copies a refreshable link that connects directly to the FEWS NET Data Warehouse database server, allowing Excel, your browser, or another application to automatically fetch data from the server whenever the link is accessed.
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CSV
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HTML
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JSON
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