bucketed
音标为：['b?kt?d]
基础释义：
1. 按照一定数量分成的（桶、箱子等）
2. 分隔成若干小部分或等级的
例句：The company's profits have been bucketed into different funds.
公司的利润被分成了不同的基金。
bucketed基础释义
bucketed是一个英语单词，意思是“分桶的”。在数据分析中，分桶是一种常用的数据预处理技术，它将数据按照一定的规则分成不同的桶，以便于进行进一步的分析和处理。
bucketed的发音
发音为/?b?kt?d/。
英文范文
标题：分桶技术在数据分析中的应用
在当今的数据时代，数据分析已经成为各行各业不可或缺的一部分。而在数据分析中，分桶技术是一种常用的数据预处理技术。通过分桶，我们可以将数据按照一定的规则分成不同的桶，以便于进行进一步的分析和处理。
在我们的实际工作中，我们经常需要处理大量的数据。这些数据不仅数量庞大，而且种类繁多。如果不进行分桶处理，我们很难有效地利用这些数据。因此，分桶技术可以帮助我们更好地理解和分析数据，从而更好地制定决策和优化业务。
举个例子，假设我们正在进行一项市场调研，我们需要收集和分析大量的消费者数据。通过分桶技术，我们可以将消费者按照年龄、性别、收入等不同的特征分成不同的桶，以便于更好地了解不同群体的消费习惯和需求。这样，我们就可以更好地制定营销策略，提高销售效果。
总的来说，分桶技术是一种非常有用的数据分析工具。通过分桶，我们可以更好地理解和利用数据，从而更好地制定决策和优化业务。因此，我们应该在数据分析中广泛应用分桶技术，以提高我们的工作效率和效果。
bucketed
Bucketed is a term used in data analysis to refer to the process of grouping data into smaller, more manageable subsets or "buckets". This process is often used to analyze trends, patterns, and relationships in large datasets.
For example, if we have a dataset containing sales data for a certain product over a period of time, we might bucket the data by month to identify trends and patterns in sales over time. By grouping the data into smaller buckets, we can more easily identify patterns and trends that might be hidden in the larger dataset.
In other contexts, bucketed may refer to other types of grouping or classification of data. For instance, it might be used to refer to the process of grouping data based on certain characteristics, such as gender, age, or geographic location.
In this context, bucketed can be a valuable tool for analyzing and understanding data. It allows us to break down large datasets into smaller, more manageable chunks, which can help us identify patterns and trends that might otherwise be difficult or impossible to see.
Sample English Essay:
In today's data-driven world, bucketed analysis is an essential tool for understanding and analyzing large datasets. By grouping data into smaller buckets, we can more easily identify patterns and trends that might otherwise be hidden in the larger dataset.
For example, consider the case of a company that is trying to understand its customer base. By bucketed analysis, the company can break down its customer data into groups based on age, gender, and geographic location, and then analyze how these groups are purchasing behavior. This allows the company to identify trends and patterns that can inform its marketing strategies and better target its advertising efforts.
Overall, bucketed analysis is a valuable tool for analyzing large datasets and understanding patterns and trends in data. It allows us to break down complex information into smaller, more manageable chunks, which can help us make better decisions and develop effective strategies for our businesses.
