An In-depth Analysis of YouTube text Data using various tools and Visualization.
- It shows how to use Text-Data to gain actionable insights and patterns and what all different type of analysis we can apply according to the Problem Statements in-hand.
- Problem Statements:
- Performing Sentiment Analysis
- Performing Word-Cloud Analysis
- Emoji Analysis (New and Interesting)
- Analysing the Most liked category?
- Is the audience engaged or not?
- Which channels have the largest number of trending videos?
- Does Punctuations in title_name column have any relation with views, likes, dislikes, comment_count features?
- Pandas
- Numpy
- Matplotlib
- Seaborn
- Plotly
- TextBlob
- Emoji
- Word-Cloud