Exploratory Data Analysis (EDA)

Exploratory Data Analysis

I. Movie exploratory

Problem Statement - I

100 top-rated movies from the past decade along with various pieces of information about the movie, its actors, and the voters who have rated these movies online. In this notebook there is a Python code to explore the data, gain insights into the movies, actors, votes, ratings and collections.

II. Bank loan

Problem Statement - I

In this EDA we:

1. Identify the missing data and use appropriate method to deal with it. (Remove columns/or replace it with an appropriate value)
2. Identify if there are outliers in the dataset. Also, mention why do you think it is an outlier. Again, remember that for this exercise, it is not necessary to remove any data points
3. Identify if there is data imbalance in the data. Find the ratio of data imbalance.
4. Explain the results of univariate, segmented univariate, bivariate analysis, etc. in business terms.
5. Find the top 10 correlation for the Client with payment difficulties and all other cases (Target variable).