Four 1 million-level apparel sales datasets（dresses, jeans, sweaters, and sweatshirts）

These datasets were developed through a collaboration between Zhejiang Sci-Tech University and Hangzhou Zhiyi Technology Co., Ltd., encompassing a four-year span from January 2019 to October 2023. We comprehensively document daily sales records of dresses, jeans, sweatshirts, and sweaters that maintained a sales volume exceeding 50 pieces and continued to sell for over 100 days. The dress dataset witnessed a maximum surge to 6.1 million, more than 12 times the smooth value at the surge point, while the jeans dataset recorded a peak of 7.3 million, over 18 times the smooth value. Similarly, the sweatshirt and sweater datasets exhibited surges of 13 and 16 times the smooth values, respectively. Such extreme volatility in the datasets poses a challenge for conventional algorithmic models to learn mutation data effectively without compromising linear fitting accuracy.