Data Wrangling

For this portion of the project, you will examine your dataset for incorrect data. Any incorrect data should be removed, corrected, or imputed. Follow these steps:

• Remove irrelevant data. If you are unsure if it is irrelevant, then keep it.
• Remove duplicate records that are repeated.
• Make sure numbers are interpreted as numerical data types.
• Fix typos.
• Standardize.
• Investigate outliers.
• Check and manage missing values.
• Format and normalize data if needed.
• Change categorical values into numbers if needed.

Once you have completed this, you will need to provide a Word document summarizing the pre-processing steps performed on your dataset.