Dicionário de Dados

ID
id
Tipo
int4
Rótulo
index

ID
date
Tipo
text
Rótulo
Date

ID
state_name
Tipo
text
Rótulo
State Name

ID
state_code
Tipo
text
Rótulo
State Code

ID
commodity
Tipo
text
Rótulo
Commodity

ID
price
Tipo
numeric
Rótulo
Price

Informações Adicionais

Campo Valor
Dados atualizados pela última vez 16 de setembro de 2024
Metadados atualizados pela última vez 19 de dezembro de 2025
Criado 16 de setembro de 2024
Formato CSV
Licença Open Data Commons Attribution License
Additional infonan
Data extraction pagenan
Data insightsInsights from the "State Level Daily Wholesale Price Data" include identifying price trends and volatility for various commodities over time. By analyzing the average, maximum, minimum, and modal prices, one can assess market stability, detect unusual price spikes or drops, and determine the most frequent price points. This data can help in forecasting price movements, understanding the impact of seasonal factors, supply-demand fluctuations, and regional variations, and assist policymakers, traders, and businesses in making informed decisions regarding commodity pricing and procurement.
Data last updated16-09-2024
Data retreival date16-09-2024
Datastore activeTrue
District no0
FrequencyDaily
Geo columns['state_code']
Gp no0
GranularityState
Has viewsTrue
Ide6b8a69f-2701-4017-b24a-d16614c62000
Idp readyTrue
Lgd mappingyes
Methodologynan
No indicators1
Package id1a59d7e5-baf1-4c4a-b10f-55a6367f82f7
Position2
Size116 MiB
Skumocafpd-wholesale_price-st-dl-rrr
Stateactive
States uts no34
Tehsil no0
Url typeupload
Years covered2015 - 2024
Methodology nan
Indicators []
Similar Resources
Granularity Level State
Data Extraction Page nan
Data Retreival Date 16-09-2024
Data Last Updated 16-09-2024
Sku mocafpd-wholesale_price-st-dl-rrr
Dataset Frequency Daily
Years Covered 2015 - 2024
No of States/UT(s) 34
No of Districts 0
No of Tehsils/blocks 0
No of Gram Panchayats 0
Informações Adicionais nan
Number of Indicators 1
Insights from the dataset Insights from the "State Level Daily Wholesale Price Data" include identifying price trends and volatility for various commodities over time. By analyzing the average, maximum, minimum, and modal prices, one can assess market stability, detect unusual price spikes or drops, and determine the most frequent price points. This data can help in forecasting price movements, understanding the impact of seasonal factors, supply-demand fluctuations, and regional variations, and assist policymakers, traders, and businesses in making informed decisions regarding commodity pricing and procurement.
IDP Ready Yes
LGD Mapping Yes
Mapping Status %
Geo Columns ['state_code']