Exploratory Data Analysis

“Let the data speak for themselves… Exploratory Data Analysis is not “fishing” or “torturing” the data set until it confesses.”

• Exploratory Data Analysis (EDA) consists of techniques that are typically applied to gain insight into a dataset before doing any formal modelling.

• EDA helps us to uncover the underlying structure of the dataset, identify important variables, detect outliers and anomalies, and test underlying assumptions. With EDA, we identify relevant variables, their transformations, and interaction among variables with respect to the model we want to build. EDA can also point out missing data as may be relevant to building desired models.

• EDA uses techniques of statistical graphics but has a broader scope. It’s an approach rather than just a set of techniques.

Hands on !

Basic Graphs, treating Missing values and Working with Continuous and Categorical Variables

CLICK HERE FOR THE WORKSHOP NOTES

---