(This was the final project submission for the course BAX-431 Data Visualization. I have included the data cleaning steps that was conducted as a group but only included the visualisation that I had personally developed for the hypothesis I had come up with.)
Through this exploratory exercise, we want to build visualizations that showcase how content (Movies/TV shows) hosted on Netflix has progressed over the years. This will tell our users the popularity of content based on their genres and geography. These insights can help content producers understand their target audience and preferences in what they consume. Since Netflix is not just a streaming service anymore but they have also been producing original content in recent years, our conclusions can thus prove to be instrumental in driving content that works well with the audience. This can also help Netflix fine-tune its recommendations based on trends in content consumption in different consumer segments.
We see a slow start for Netflix over several years. Things began to pick up in 2015, with a rapid increase from 2016 for both movies and TV Shows. However, we see a much more rapid growth for movies than shows. Content additions slowed down in 2020, likely due to the COVID-19 pandemic. We see that December and July have the highest number of content added, which also coincides with the winter and summer vacation period, where people will be directed towards watching online content. This will be helpful for our users like Netflix and Content producers to know so they can add more relevant content based on their target audience during this period.
We observe that the Americas region has the highest number of content added over the months, with the highest during December, July, and September. The months of December and July are vacation periods; hence our consumers would watch more content online therefore, our users can develop more content that can be streamed during those months. We can see a content slump in February for the Americas. Similarly for the Asia region, we see an uptick in December, April and March. While for Europe, Oceania and Africa regions we do not necessarily see a pattern for specific months with an almost equal amount of content added over the months. Based on our hypothesis, we do see strong evidence for the Americas region but not for Europe
References: https://www.kaggle.com/code/joshuaswords/netflix-data-visualization