“Data will talk, if you are willing to listen”- Jim Bergeson
With the proper use of data, one can gain insights and use it for numerous purposes. Raw data has no story to tell. So, to understand and gain insights from data, after the data collection process, exploratory data analysis comes into the picture. It is a crucial process to recognize patterns and understand data to prepare the model.
This article is divided into the following sections:
The process to explore and understand data to gain insights from the data. It can be context as “Look at the first sight” for solving any Data Science problem. It takes a step closer to the goal of solving the problem at hand.
To summarize important features, to recognize patterns & distribution curves, to detect outliers and anomalies, to find a number of classes, or distribution of data/classes, to test underlying assumptions, etc by analyzing and visualizing. Basically to know what the data is trying to say!
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