Investigating Netflix Movies and Guest Stars in the Office
Data Science Project - Data Science with Python Course at DataCamp
Introduction
In recent years, Netflix has become a major player in the movie industry, offering a vast selection of movies from various genres and countries. As part of a Data Science with Python Course at DataCamp, we set out to investigate whether movies on Netflix are getting shorter over time. In this article, we present our findings and discuss their implications for the movie and television industries.
Data Collection
To investigate our research questions, we gathered data from the source: Netflix. For Netflix, we used a dataset of over 10,000 movies available on the streaming platform, which we obtained from Kaggle. The dataset includes information on the movie title, director, cast, release year, rating, and duration.
Exploratory Data Analysis
We first explored the distribution of movie duration on Netflix. We found that the average duration of movies on Netflix has decreased slightly since 2011, from around 100 minutes to 95 minutes in 2020. However, there is significant variation in movie duration from year to year, and there are still many movies that are longer than two hours. Our analysis also revealed that the shortest movie on Netflix is only 3 minutes long, while the longest one is over 5 hours.
Next, we looked at trends in movie duration over time. We found that the average duration of movies on Netflix has fluctuated over the years, with no clear pattern of decrease or increase. Additionally, our analysis is limited to movies available on Netflix, and may not be representative of the overall movie industry. Therefore, we cannot make any definitive statements about whether movies are getting shorter or not.
Results:
Based on our analysis, we cannot be certain that movies are getting shorter. While the average duration of movies on Netflix has decreased slightly since 2011, there is significant variation in movie duration from year to year, and there are still many movies that are longer than two hours. Additionally, our analysis is limited to movies available on Netflix, and may not be representative of the overall movie industry. Therefore, we cannot make any definitive statements about whether movies are getting shorter or not.
Future Predictions:
Our study has several limitations that could be addressed in future research. For example, we only analyzed movies available on Netflix, and it would be interesting to compare our findings to those of other streaming platforms or the overall movie industry.
Conclusion:
In conclusion, our investigation into Netflix movies revealed interesting insights about movie duration. While there is some evidence that the average duration of movies on Netflix has decreased slightly since 2011, our findings also show that movie duration varies significantly from year to year and that there are still many movies that are longer than two hours.
Although our study has limitations, such as the focus on only one streaming platform, it provides a starting point for further research in this area. For example, future studies could examine the relationship between movie duration and other TV shows or streaming platforms, or investigate factors that influence guest star appearances. Overall, our findings contribute to a better understanding of the movie and television industries and highlight the importance of data science in uncovering insights from complex datasets.
Comments