Why Clean Your Data?
Data cleaning is a crucial step in the data analysis process. It ensures the accuracy and quality of your data, which is vital for making reliable conclusions and decisions. 🐱🏍
Steps to Clean Data
- Remove Duplicates: Identify and remove redundant data entries to avoid skewed results.
- Handle Missing Values: Decide whether to fill, estimate, or remove missing data.
- Normalize Data: Ensure consistency in data formats for accurate analysis.
- Validate Data: Verify data accuracy and correct erroneous information.
Visit our resources page for detailed tutorials and best practices on data cleaning. 🌟