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The week two task in my boot camp with Sidehustle is to analyze the Netflix dataset gotten from Kaggle. The objectives of this task for myself and the team members were to;
Identify the most popular shows and movies on Netflix based on viewership data.
Analyze viewer behavior and preferences to understand which genres and types of content are most popular.
Investigate the relationship between user ratings and viewership data to understand how ratings impact viewership.
Evaluate the performance of Netflix's original content versus licensed content.
Identify potential areas for growth and expansion for the company.
Limitation/ Challenges
Some of the columns needed for this analysis to be done according to the task requirements were not provided in the dataset, hence this is reported as a limitation.
Loading the dataset
Visuals
The dataset was ready for transformed and ready for the analysis
A summary page of the key performing indicators was created alongside one Stacked column chart which revealed that the Year with the most release is 2019 with a total of Two thousand and sixteen (2,016) releases.
The summary page also showed the top three showing ratings with the most release, the Title rating TV-MA has the top, and TV-PG at the lowest in the top three.
The dashboard
In the image above, the USA has the highest number of Titles in North America, furthermore, Brazil has the highest in South America, Nigeria with the highest in Africa followed by South Africa with a total of thirty-five (35) titles. Europe has the highest number of countries in it and the country with the highest number of titles is the UK.
Other countries with a high number of titles include Japan, India, and Australia.
Potential areas of growth
There are countries, where quite several movie listings are not been made for viewers, Kids Tv, Children, and Family shows, are not popular in Africa, User relatable content is recommended for this, Africa has an overall high number of titles for a small distribution of countries in it.
End of documentation.