Nowadays, huge amounts of data are generated every day at an unprecedented speed from various sources, including data on the Internet. The existence of the Internet increases the amount of data contained on a website, every company, and organization definitely needs website development to meet the needs of their company or organization, this can be an opportunity for data engineers to process this amount of data into useful statistics for companies or researchers. That's why we need an efficient method to collect the amount of data on a website, and web scraping is one of them. In this study, the researcher implemented a web scraping method on the myanimelist.net site which is the largest community and database about anime and manga in the world. The purpose of this study is to analyze the relationship between the company (animated studio) and the anime it produces through correlation analysis method. This research method broadly consists of four stages, including data extracting, data processing, correlation test, and data visualization. The research tools used for scraping are beautifulsoup and pandas which are python libraries, tools for processing and analyzing the scraped data are google collaborative and pandas which are data processing applications, while for the data visualization process researchers use an additional matplotlib library. The results of this study indicate that web scraping can be implemented on the myanimelist.net site effectively. Researchers can collect 17982 rows of data from 129 companies. The results of the correlation analysis show that the popularity of the company has a low relationship with the popularity of the anime they produce.