Data Wrangling and Analysis

In this project, data wrangling techniques were employed to gather, assess, and clean data from multiple sources, particularly web scraping of Twitter data related to dogs. The data included details about tweets, images, and engagement metrics. After the data was cleaned, it was analyzed to gain insights into popular dog breeds, engagement patterns, rating distributions, and more. The project involved using Python libraries such as Pandas, Matplotlib, and Seaborn, and the final clean dataset was used to generate visualizations for meaningful insights.