Baselight

🔥 Most Viewed Hindi Music Videos On YouTube 🎵

Rhythms of India: Charting Bollywood's Viral Beats

@kaggle.kanchana1990_most_viewed_hindi_music_videos_on_youtube

About this Dataset

🔥 Most Viewed Hindi Music Videos On YouTube 🎵

Title: "🔥 Most Viewed Hindi Music Videos on YouTube 🎵"

Description:

Dive into a rich dataset capturing the essence of India's vibrant music industry, featuring some of the most viewed Hindi music videos on YouTube. This unique collection amalgamates data from the three paramount channels of Indian music: T-Series, Zee Music, and Tips Official. Each entry is a testament to the songs and artists that have left an indelible mark on audiences nationwide and globally.

Dataset Compilation: Compiled from the extensive libraries of T-Series, Zee Music, and Tips Official, this dataset offers a diverse range of videos, each resonating with millions of fans. As you navigate through the data, keep an eye out for duplicates or near duplicates, especially for popular videos featured across multiple channels. We encourage users to employ their data wrangling skills to identify and manage these instances for a more streamlined analysis.

Column Descriptors:

  • Channel: The originating YouTube channel of the video.
  • Title: The title of the video as it appears on YouTube.
  • Published_At: The date and time the video was made available on YouTube.
  • Duration: The total length of the video.
  • View_Count: The number of times the video has been viewed.
  • Like_Count: The number of likes the video has received.
  • Comment_Count: The number of comments on the video.

Potential Uses:

  • Trend Analysis: Discover the evolution of music tastes over time by analyzing view counts, likes, and comments.
  • Popularity Metrics: Dive into what makes a video successful by exploring the correlation between different engagement metrics.
  • Comparative Study: Compare the content strategy and audience engagement across the three channels to understand the competitive landscape.

Ethical Consideration and Acknowledgements:

We obtained this data respectfully, using Google's YouTube Data API with strict adherence to rate limits and quota management, ensuring ethical data mining practices. Our heartfelt thanks go to T-Series, Zee Music, and Tips Official for creating content that resonates across borders, and to YouTube for providing a platform that bridges creators and audiences. This dataset stands as a testament to their collective impact on the music industry.

Closing Note:

As you delve into the dataset, remember that each data point represents a story - a song that might have been someone's first dance, a comfort in tough times, or a tune that brings back a flood of memories. Happy analyzing, and may your insights be as profound as the music itself!

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