Introduction to Data Cleaning in R in Data Science with R Programming
What is Data Cleaning?
Data cleaning is the process of identifying and correcting errors in datasets. In real-world data science projects, datasets often contain missing values, duplicates, and inconsistencies that must be fixed before analysis.
Why Data Cleaning Matters
- Improves data accuracy
- Enhances model performance
- Removes duplicate records
- Handles missing values
r
data <- data.frame(
name=c("John","Alice",NA),
age=c(25,30,28)
)
Next Tutorial: Handling Missing Values
