Netflix Data Analysis using Python | DataHour by Munmun Das

Exploratory Data Analysis (EDA) is a process of analyzing and understanding a dataset in order to identify patterns, trends, and relationships within the data. It is an iterative process that involves generating hypotheses, visualizing the data, and testing those hypotheses.

There are a variety of techniques that can be used for EDA, including: Visualization, Descriptive statistics, Outlier detection, Correlation analysis.

EDA is an important step in the data analysis process because it helps you to understand your data and identify any potential issues or problems that may need to be addressed before proceeding with more advanced analysis.

In this DataHour, Munmun will be demonstrating how to perform feature engineering steps like data cleaning, missing value treatment, outliers treatment, data description, binning, correlation of variables, univariate, bivariate and multivariate analysis with proper visualizations using the Netflix dataset.

Prerequisites: Basic understanding of statistics and zeal of learning Data Science.

Who is this DataHour for?
1. Students & Freshers who want to build a career in the Data-tech domain.
2. Working professionals who want to transition to the Data-tech domain.
3. Data science professionals who want to accelerate their career growth

Munmun is a professional and research scholar with 16 + years of experience in Software Project Management, Product development, Product strategy, and delivery of large-scale, complex automation/transformation solutions, web and mobile applications. She has also mentored industry tech-force as an Industry Speaker, Corporate Mentor, and Guest Lecturer.

She has implemented handshaking projects on RPA with Dot Net web applications and successfully built on-demand RPA.