In an increasingly interconnected and multicultural world, the linguistic landscape is characterized by the pervasive phenomenon of code-mixing, where individuals seamlessly blend multiple languages within their communication. This study delves into the realm of sentiment analysis applied to code-mixed comments, aiming to unravel the intricate emotional nuances embedded in multilingual discourse. The research employs a hybrid approach, combining rule-based techniques and machine learning algorithms to discern sentiments within code-mixed textual data. A diverse dataset comprising comments sourced from social media platforms, forums, and user-generated content is utilized for comprehensive analysis. The code-mixing phenomena are explored in both intra-sentential and inter-sentential contexts. This study advances our understanding of sentiment analysis in the context of code-mixed comments, emphasizing the importance of considering linguistic diversity in deciphering the emotional landscape of online communication.