基于菜品消费情况分析食堂菜品满意程度数据

本数据能够客观反映学校食堂不同菜品的受欢迎程度，通过分析菜品的消费情况和顾客满意度，食堂可以了解哪些菜品受欢迎，哪些菜品需要改进，从而提升菜品的整体质量。 根据菜品的销售数据和顾客的满意度反馈，食堂可以调整菜单，增加受欢迎菜品的供应，减少不受欢迎菜品的供应，实现菜单的优化，使菜品设计更符合师生口味，提升师生的整体满意度。通过分析菜品的消费情况，食堂可以更准确地预测食材需求，优化库存管理，减少浪费，控制成本。本数据可为行业内其他食堂单位的菜品设计提供参考，这些单位通过本数据可以了解本地区的菜品受欢迎程度情况，具有较大的参考价值。本数据还能为科研机构开展食品安全和营养学的相关研究提供实证支持。1.数据抽取和预处理： （1）数据抽取：在自研的5G智慧食安工业物联网数字化管理平台数据库中抽取相关学校食堂的菜品消费数据，包括日期、学校编号、所在地区、菜品名称、该菜品当期消费人数、该菜品上期消费人数、食堂当期就餐总人数、食堂上期就餐总人数。（2）数据预处理：对抽取的数据进行清洗，去除重复、错误或无关的信息，以便后续的分析和建模。 2.基于菜品消费情况分析其受欢迎程度： （1）计算该菜品当期和上期的消费率：当期消费率=当期消费人数÷食堂当期就餐总人数×100%；上期消费率=上期消费人数÷食堂上期就餐总人数×100%；（2）计算该菜品消费率较上期的变化：该菜品消费率较上期的变化=当期消费率-上期消费率；（3）建立菜品受欢迎程度评估模型：受欢迎指数=当期消费率×x+消费率较上期的变化×y；x和y为对应的系数，属于商业秘密，故不作详细列举；最后对菜品受欢迎程度进行判定：指数为80-100为非常受欢迎，60（含）-80为比较受欢迎，40（含）-60为一般受欢迎，20（含）-40为不太受欢迎，20以下为不受欢迎。

This dataset objectively reflects the popularity of different dishes in school canteens. By analyzing dish consumption data and customer satisfaction feedback, canteen operators can identify popular dishes and those requiring improvement, thereby enhancing the overall quality of their offerings.
Based on dish sales data and customer satisfaction feedback, canteens can adjust their menus by increasing the supply of popular dishes and reducing that of unpopular ones, achieving menu optimization, aligning dish designs with the tastes of teachers and students, and improving their overall satisfaction.
By analyzing dish consumption data, canteens can more accurately forecast ingredient demand, optimize inventory management, reduce waste, and control operating costs.
This dataset also provides valuable reference for other canteen operators in the industry: they can use it to understand the popularity of dishes in their local region, making it highly referential. Additionally, this dataset can offer empirical support for research institutions conducting relevant studies on food safety and nutrition.

1. Data Extraction and Preprocessing
(1) Data Extraction: Extract relevant school canteen dish consumption data from the database of the self-developed 5G Smart Food Safety Industrial Internet of Things (IIoT) Digital Management Platform. The collected data includes: date, school ID, location, dish name, number of consumers of the dish in the current period, number of consumers of the dish in the previous period, total number of diners in the canteen in the current period, and total number of diners in the canteen in the previous period.
(2) Data Preprocessing: Clean the extracted data by removing duplicate, erroneous, or irrelevant information to support subsequent analysis and modeling.

2. Popularity Analysis Based on Dish Consumption Data
(1) Calculate the consumption rates of the dish in the current and previous periods:
Current period consumption rate = (Number of consumers of the dish in the current period / Total number of diners in the canteen in the current period) * 100%;
Previous period consumption rate = (Number of consumers of the dish in the previous period / Total number of diners in the canteen in the previous period) * 100%;
(2) Calculate the change in the dish's consumption rate compared to the previous period:
Change in consumption rate = Current period consumption rate - Previous period consumption rate;
(3) Establish a dish popularity assessment model:
Popularity Index = Current period consumption rate * x + Change in consumption rate * y;
The coefficients x and y are commercial secrets and are not detailed herein. Finally, determine the popularity level of the dish according to the index:
- 80-100: Very Popular
- 60 (inclusive) - 80: Relatively Popular
- 40 (inclusive) - 60: Moderately Popular
- 20 (inclusive) - 40: Slightly Unpopular
- Below 20: Unpopular

AI搜集汇总

数据集介绍

特点

该数据集通过分析学校食堂菜品的消费情况，评估菜品的受欢迎程度，帮助食堂优化菜单和食材管理，提升师生满意度。数据每日更新，包含533条记录，适用于餐饮业和科研机构。