Data Analysis and Visualization on Netflix Data to provide insights and recommendations to improve their userbase.
| Column | #Description |
|---|---|
| Show_id | Unique ID for every Movie / Tv Show |
| Type | Identifier - A Movie or TV Show |
| Title | Title of the Movie / Tv Show |
| Director | Director of the Movie |
| Cast | Actors involved in the movie/show |
| Country | Country where the movie/show was produced |
| Date_added | Date it was added on Netflix |
| Release_year | Actual Release year of the movie/show |
| Rating | TV Rating of the movie/show |
| Duration | Total Duration - in minutes or number of seasons |
| listed_in | Genre |
| description | The summary description |
Netflix is one of the most popular media and video streaming platforms. They have over 10000 movies or tv shows available on their platform, as of mid-2021, they have over 222M Subscribers globally. This tabular dataset consists of listings of all the movies and tv shows available on Netflix, along with details such as - cast, directors, ratings, release year, duration, etc.
Aim while exploring this dataset is to analyze the data and generate insights that could help in deciding which type of shows or movies to produce and how they can grow the business in different countries.
We are interested in increasing the revenue of Netflix, hence our main objective is to figure out which all shows and movies performed the best.
- Data Cleaning
- Analysis
- Visualization
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Observations on the shape of data, data types of all the attributes, conversion of categorical attributes to 'category', missing value detection, statistical summary
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Non-Graphical Analysis: Value counts and unique attributes
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Visual Analysis - Univariate, Bivariate after pre-processing of the data
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For continuous variable(s): Distplot, countplot, histogram for univariate analysis
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For categorical variable(s): Boxplot
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For correlation: Heatmaps, Pairplots
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Missing Value & Outlier check
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Insights based on Non-Graphical and Visual Analysis
. Comments on the range of attributes
. Comments on the distribution of the variables and relationship between them
. Comments for each univariate and bivariate plot
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Business Insights & Recommendations : Includes patterns observed in the data along with what can infer from it
Netflix_Business_Case_Study.ipynb - Colaboratory notebook containing the code for analysis