汽车聚类分析

赛题以竞品分析为背景，通过数据的聚类，为汽车提供聚类分类。对于指定的车型，可以通过聚类分析找到其竞品车型。通过这道赛题，鼓励学习者利用车型数据，进行车型画像的分析，为产品的定位，竞品分析提供数据决策。
选手需要对该汽车数据进行聚类分析，并找到vokswagen汽车的相应竞品。要求选手在天池实验室中用notebook完成以上任务，并分享到比赛论坛。
（聚类分析是常用的数据分析方法之一，不仅可以帮助我们对用户进行分组，还可以帮我们对产品进行分组（比如竞品分析） 这里的聚类个数选手可以根据数据集的特点自己指定，并说明聚类的依据）

This competition problem is framed in the context of competitive product analysis, aiming to categorize automobiles through data clustering. For a specified vehicle model, its competitive products can be identified via cluster analysis. This competition encourages participants to leverage vehicle datasets to conduct vehicle profiling analysis, thereby providing data-driven decision support for product positioning and competitive product analysis. Participants are required to perform cluster analysis on the provided automotive dataset and identify the matching competitive products for Volkswagen vehicles. Participants are requested to complete all the aforementioned tasks using Jupyter Notebook in Tianchi Lab, and share their submissions on the competition forum. (Cluster analysis is one of the most commonly used data analysis techniques. It can not only facilitate user segmentation, but also support product grouping for scenarios such as competitive product analysis. Participants can determine the number of clusters based on the characteristics of the dataset, and are required to explicitly explain the adopted clustering rationale.)

搜集汇总

背景与挑战

背景概述

该数据集名为“汽车聚类分析”，是一个用于竞品分析的公共数据集，旨在通过聚类方法对汽车进行分组，以识别特定车型（如volkswagen）的竞品。数据集包含两个文件：car_price.csv和car_price_dictionary.xlsx，涵盖了26个字段，包括汽车公司、燃料类型、车身、尺寸、发动机参数和价格等分类与数值变量，支持车型画像分析和数据驱动的产品定位决策。