Merge pull request #591 from ghousiya47/Most-Subscribed-YouTube-Chann…

…els-Analysis

Most Subscribed YouTube Channels Analysis #575

Most Subscribed YouTube Channels Analysis/Dataset/README.md

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+# Most Subscribed YouTube Channels Dataset
+
+The Dataset used here is taken from the Kaggle database website. You can download the file from the link given here, Most Subscribed YouTube Channels Analysis.(https://www.kaggle.com/datasets/surajjha101/top-youtube-channels-data )
+
+## About the dataset
+
+This data contains the 7 attributes about the top 1000 YouTube channels as per number of subscribers they have. These attributes with their proper description are as follows:
+
+- rank: Rank of the channel as per number of subscribers they have
+
+- youtuber: Channel Official Name
+
+- subscribers: Number of subscribers channel have
+
+- video views: Number for which all videos have been watched collectively
+
+- video count: Number of videos channel has uploaded so far
+
+- category: Category (genre) of the channel
+
+- started: Year when the channel was started
+
+Hence the dataset has 1000 rows and 7 columns.

Most Subscribed YouTube Channels Analysis/README.md

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+<h1>Most Subscribed YouTube Channels Analysis</h1>
+
+**GOAL**
+
+To visualize and perform EDA and study relationship between different atttributes.
+
+**DATASET**
+
+[https://www.kaggle.com/datasets/surajjha101/top-youtube-channels-data]
+
+**DESCRIPTION**
+
+This data contains the 7 attributes about the top 1000 YouTube channels as per number of subscribers they have. These attributes with their proper description are as follows:
+
+rank: Rank of the channel as per number of subscribers they have
+
+youtuber: Channel Official Name
+
+subscribers: Number of subscribers channel have
+
+video views: Number for which all videos have been watched collectively
+
+video count: Number of videos channel has uploaded so far
+
+category: Category (genre) of the channel
+
+started: Year when the channel was started
+
+Hence the dataset has 1000 rows and 7 columns.
+
+### Visualization and EDA of different attributes:
+
+<img alt="Aggregate Video Views per Category" src="./Images/IMG1.png">
+
+<img alt="Category column Plot" src="./Images/img2.png">
+
+<img alt="Category column Piechart" src="./Images/img3.png">
+
+<img alt="Aggregate subscribers per Category" src="./Images/img4.png">
+
+<img alt="Aggregate Video Views for Age of Channel" src="./Images/img5.png">
+
+<img alt="Aggregate Video Views for Each Channel" src="./Images/img6.png">
+
+<img alt="Youtube Channel Creation for Each Yeart" src="./Images/img7.png">
+
+**Distribution Plot, KDE Plot, BOX Plot**
+
+<img alt="Distribution" src="./Images/img8.png">
+
+**Correlation heatmap**
+
+<img alt="Correlation Heatmap" src="./Images/img9.png">
+
+**WHAT I HAD DONE**
+
+* Load the dataset which is CSV format.
+* It has 1000 entries(Rows), 7 columns(attributes).
+* Checked for missing values and cleaned the data accordingly.
+* Analyzed the data, found insights and visualized them accordingly.
+
+**LIBRARIES NEEDED**
+
+1. Pandas
+2. Matplotlib
+3. NumPy
+4. Seaborn
+
+**CONCLUSION**
+
+- From various visualizations we can see that Music Category channels are most subscribed
+- We can notice that there's high correlation 0.82 with subscribers and video views.
+- Music, education, Film & Animation are top3 categories that have most subscribers.
+- Includes: T-Series, YouTube Movies and Cocomelon - Nuresery Rhymes
+
+
+**YOUR NAME**
+
+*Ghousiya Begum*
+
+[![LinkedIn](https://img.shields.io/badge/linkedin-%230077B5.svg?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/ghousiya-begum-a9b634258/)  [![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)](https://github.com/ghousiya47)

Most Subscribed YouTube Channels Analysis/requirements.txt

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+numpy==1.19.2
+pandas==1.4.3
+matplotlib==3.7.1
+scikit-learn~=1.0.2
+seaborn==0.10.1