District Level Data (DLD) and Dashboard for Agriculture and Allied-sectors in India
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The District Level Database (DLD) for Indian agriculture and allied sectors provide a comprehensive one-stop-shop for India's rural sector. The DLD time-series data will be used to identify relevant regions/districts in India for targeted programs and development initiatives. It acts as a link between country-level macro data and household-level microdata. The dataset, which consists of district-level data from 1966-2017, covers 592 districts from 20 states.The DLD database has two types of datasets, namely unapportioned and apportioned datasets. The unapportioned dataset corresponds to the current district's data. In contrast, the apportioned dataset was created by giving back the newly formed districts' data to the parent districts based on the geographical area percentage. The DLD database now has three apportioned datasets wit' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Agricultural statistics","Census","Crops","District","Environmental factors","India","Infrastructure","Livestock","Population dynamics","Statistical data"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The District Level Database (DLD) for Indian agriculture and allied sectors provide a comprehensive one-stop-shop for India's rural sector. The DLD time-series data will be used to identify relevant regions/districts in India for targeted programs and development initiatives. It acts as a link between country-level macro data and household-level microdata. The dataset, which consists of district-level data from 1966-2017, covers 592 districts from 20 states.The DLD database has two types of datasets, namely unapportioned and apportioned datasets. The unapportioned dataset corresponds to the current district's data. In contrast, the apportioned dataset was created by giving back the newly formed districts' data to the parent districts based on the geographical area percentage. The DLD database now has three apportioned datasets wit' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The District Level Database (DLD) for Indian agriculture and allied sectors provide a comprehensive one-stop-shop for India's rural sector. The DLD time-series data will be used to identify relevant regions/districts in India for targeted programs and development initiatives. It acts as a link between country-level macro data and household-level microdata. The dataset, which consists of district-level data from 1966-2017, covers 592 districts from 20 states.The DLD database has two types of datasets, namely unapportioned and apportioned datasets. The unapportioned dataset corresponds to the current district's data. In contrast, the apportioned dataset was created by giving back the newly formed districts' data to the parent districts based on the geographical area percentage. The DLD database now has three apportioned datasets wit
Agricultural statistics; Census; Crops; District; Environmental factors; India; Infrastructure; Livestock; Population dynamics; Statistical data