- Set up Python's virtual environment (Windows)
py -m venv /path/to/virtual/environment/inside/the/project
- Install Pandas and Matplotlib
py -m pip install pandas
py -m pip install matplotlib
- Save all the packages in the text file requirements.txt
creat requirements.txt inside the project
py -m pip freeze > requirements.txt
py -m pip install -r requirements.txt
In this project, I will solve a real-world data science problem. I will use everything from lists and loops to pandas and matplotlib to discover if Netflix's movies are getting shorter over time and which guest stars appear in the most popular episode of "The Office"
It looks like there is something to the idea that movie lengths have decreased over the past ten years!!!
What if we have a close look on only type "Movies" on Netflix? A line plot is no longer a good choice for our data, so let's try a scatter plot instead
We can also see that, while newer movies are overrepresented on the platform, many short movies have been released in the past two decades. Upon further inspection, something else is going on. Some of these films are under an hour long! Let's filter our DataFrame for movies with a duration under 60 minutes and look at the genres. This might give us some insight into what is dragging down the average.
- 🔴 genre "Children"
- 🔵 genre "Documentaries"
- 🟢 genre "Stand-up"
- ⚫ others
After performing an exploratory analysis, the question is that "Are movies getting shorter?"
Well, as we suspected, non-typical genres such as children's movies and documentaries are all clustered around the bottom half of the plot. But we can't know for certain until we perform additional analyses. Now the answer is "no" or "maybe"
The highest view is 22.91 million that are at episode 77
The guest stars who were in the most watched Office episode are Cloris Leachman, Jack Black, Jessica Alba
