Exploratory Data Analysis in R

Learn basic steps to perform Exploratory Data Analysis(EDA) in R using tidyverse.

You have received a large dataset and would like to understand the data, the data pattern in the data including outliers and relationships between different variables. Learn the basic steps to perform EDA in R in this post.

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Why Exploratory Data Analysis(EDA)?

EDA is a data analysis step to better understand the data without assumptions. During EDA, you look for data patterns, trends and summarize the dataset’s main characteristics.

EDA starts by asking questions related to specific parts of the data to perform data investigation like a data detective.

As an example, you have flights arrival and departure data along with weather data. You can ask how weather impacts the flight on-time arrivals/departure, what temperatures and wind conditions are ideal for flying in winter, and conditions that delay the flight.

During the EDA process, collect as many thought-provoking questions as possible related to the data without any judgment; you never know what insights are waiting for you to be explored in the dataset.

Exploratory Data Analysis Goal

• Get a detailed…