Netflix data has some of movies and tv-shows, that have rating, duration, country produced and category.

Using Jupyter Notebook to dig deep in Netflix Dataset. Analyzed and interpreted data from 1000+ movies and TV series to identify audience preferences and optimize content recommendations.

Use the package manager pip or use the Conda package manager

pip install pandas
pip install matplotlib
pip install seaborn

conda install pandas
conda install matplotlib
conda install seaborn

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

• Checking if there is any duplicate, and remove it.
• Checking if there is any null value.

• The (Show_id) and (Director) for 'House of Cards'.
• The highest number of movies and TV shows released in a Year.
• Number of TV shows and Movies are in the Dataset.
• All Movies that released in 2020.
• Show all the Titles of all TV shows that are released in India
• Top 10 Directors that have the highest number of movies and tv shows.
• Show all the Records that their (Category) is Movie and the (Type) is Comedies or (Country) is UK.
• Movies and TV shows that Tom Cruise was in the cast.
• The Different Ratings defined by Netflix.
• Movies that got the 'TV-14' rating, In Canada.
• TV Show got the 'R' rating after 2018.
• The maximum duration of a Movie/Show on Netflix.
• The Country that has the Highest No. of TV Shows.
• Sorting the Dataset by Year.
• All the instances where: Category is Movie and Type is Dramas OR Category is 'TV Show' and Type is 'Kids' TV'