In this paper, we analyze the Netflix production dataset to gain insights into geographical distribution, temporal trends, genre popularity, and the impact of specific individuals in the content production industry. Using meticulous preprocessing and data analysis techniques, we have obtained insights on how productions have evolved and shifted over time at Netflix.
Netflix, as one of the largest digital streaming platforms, has accumulated extensive data about its films and series, including information about directors, actors, genres, and more. Analyzing this data can help us identify patterns in content production and factors contributing to their success.
Initially, we preprocessed the Netflix dataset to remove inappropriate data and complete missing data. Dates were standardized, and missing data were replaced with default values.
We conducted four primary types of analysis:
The analyses showed that the United States has the highest number of productions, and trends indicate an increase in productions over the years. Drama and comedy genres are the most popular, and the presence of certain actors and directors significantly influences the success of productions.
These analyses can be useful in Netflix's strategic planning for new content production and attracting more viewers. Identifying success factors can also aid in improving the quality of future productions.
Data analysis of Netflix is crucial for identifying trends and making informed decisions. By utilizing accurate data and advanced analysis techniques, we can better understand the market and audience needs.
https://github.com/marzieh135/projectNetflix