Link to Content:

11 Steps for Data Exploration in R

Created/Published/Taught by:

Analytics Vidhya

Content Found Via:

Open Data Science

Free? Yes

Tags: exploratory data analysis / R

Content Type: Cheat Sheets / References, Learning Guides, Etc.

Difficulty Rating:

Difficulty Rating:

“Data Exploration not only uncovers the hidden trends and insights, but also allows you to take the first steps towards building a highly accurate model. Considering the popularity of R Programming and its fervid use in data science, I’ve created a cheat sheet of data exploration stages in R. This cheat sheet is highly recommended for beginners who can perform data exploration faster using these handy codes. All you need to do is, customize the codes according your need.”

This cheat sheet covers the following topics:

- Commonly used R libraries
- How to load a data file
- How to convert a variable to a different data type
- How to transpose a data set
- How to sort a DataFrame
- How to create plots (histogram)
- How to generate frequency tables with R
- How to sample data sets in R
- How to remove duplicate values of a varaible
- How to find class level count average and sum in R
- How to recognize and treat missing values and outliers
- How to merge/join data sets

Recommended Prerequisites: none

Go to Content: Cheatsheet – 11 Steps for Data Exploration in R (with codes)

Log in to post a review.