Understanding Bucketing in Data Analysis

Bucketing is a technique used in data analysis to group similar data points together and summarize them. It involves dividing the data into smaller subgroups or "buckets" based on certain characteristics, such as range of values or frequency of occurrence.

For example, if you have a dataset of exam scores, you might bucket the scores into ranges like this:

* Bucket 1: Scores below 50
* Bucket 2: Scores between 50-60
* Bucket 3: Scores between 60-70
* Bucket 4: Scores above 70

By grouping the data in this way, you can quickly see how many scores fall into each range and identify any patterns or trends that emerge. This can be useful for identifying outliers, detecting anomalies, and summarizing large datasets.

There are different ways to define buckets, such as using fixed ranges or dynamic ranges based on the data. The choice of bucket definition will depend on the specific goals of the analysis and the nature of the data.