Begin with this eGuide to explore the entire process of Exploratory Data Analysis or EDA using the R language. This eGuide includes various practical use cases and traversed the business problems for maximum content assimilation.
It unfolds with the brief intro to the EDA and then gives you more insights into different types of data along with a dataset of a bank. You will first understand the overall process of executing a data science problem which is a must for every data scientist to analyze and then define a business problem using an industry standard framework. It also focuses on the journey of EDA, with the help of univariate, bivariate, and multivariate analysis.
Lastly, you will install all the packages & convert the required dataset into a data frame to start with different types of exploratory data analysis with R programming language. It is then followed by a brief summary of giving you a complete picture.
With this eGuide, you will learn:
Intro to Exploratory Data Analysis or EDA
Installation of different packages like ggplot2, cowplot, dplyr, repr
Convert dataset into data frame for exploratory data analysis using R programming
Univariate analysis
Geom_histogram function
Visualizing multiple variables using a histogram
Bivariate analysis & so much more.
Start off with Exploratory Data Analysis with different types of analysis like univariate, bivariate & multivariate using the R programming language.
