The objective of Exploratory Data Analysis (EDA) on any dataset is to ensure that it is free of duplicates, incorrect values, and null values. When we work on developing the model, identifying the relevant characteristics in the dataset and removing the unwanted noise in the dataset that might impair the accuracy of the results.
EDA is commonly used to achieve the following objectives:
- Evaluating a single variable and examining patterns across time
- Error-checking the data
- Confirming assumptions
- Analyzing the connections between variables