洞头区农贸市场土豆价格浮动数据

农业生产者可以通过监测蔬菜的均价，及时了解市场动态，调整种植结构和生产计划，以适应市场需求的变化；基于历史均价数据，生产者可以对未来的蔬菜销售价格进行预测，从而更好地规划生产和销售策略，提高经济效益，政府可以通过监测蔬菜均价的变化，评估物价水平，及时采取宏观调控措施，如调整农产品补贴政策、优化流通环节等，以维护市场稳定和消费者利益。1、数据采集：从本地服务器中提取农贸市场关于土豆2022年~2023年当中每日的最高价与最低价：2、处理数据：将每日的最低价与最高价分别进行累加，进而得到A（最低价总和）与B（最高价总和），进一步通过公式（A+B）/2/730得出土豆的C（均价），进一步提取2022年~2023年中最高价的峰值与最低价的谷值，该峰值与谷值分别作为该数据的最高价与最低价，进一步将(最高价与C（均价）的差的绝对值）/C（均价）*100%，从而得出+浮动值，进一步将(最低价与C（均价）的差的绝对值）/C（均价）*100%，从而得出-浮动值。

Agricultural producers can monitor the average price of vegetables to timely grasp market trends, adjust planting structures and production plans to adapt to changes in market demand. Based on historical average price data, producers can forecast future vegetable selling prices, thereby better planning production and sales strategies and improving economic benefits. Governments can monitor changes in vegetable average prices to assess price levels and timely adopt macro-control measures, such as adjusting agricultural product subsidy policies and optimizing circulation links, to maintain market stability and consumer interests.
1. Data Collection: Extract the daily highest and lowest prices of potatoes from local servers at agricultural wholesale markets between 2022 and 2023.
2. Data Processing: Sum the daily lowest and highest prices separately to obtain A (total lowest price) and B (total highest price). Further calculate C (average price) of potatoes using the formula (A+B)/2/730. Extract the peak value of the highest price and the trough value of the lowest price from 2022 to 2023, which are taken as the overall highest and lowest prices of this dataset respectively. Calculate the positive fluctuation value as (|overall highest price - C|)/C * 100%, and calculate the negative fluctuation value as (|overall lowest price - C|)/C * 100%.

搜集汇总

数据集介绍

特点

该数据集记录了2022年至2023年温州市洞头区农贸市场土豆的价格浮动情况，包含最低价、最高价、均价及其浮动比等关键信息。数据规模为732条，更新频次为按需更新，适用于农业生产者调整种植结构和生产计划，以及政府评估物价水平等应用场景。