Data Science, Data Visualization, Analytics, Data Engineering, Data Analysis.
predict missing values based on other variables. Deletion: Sometimes, it’s best to remove rows or columns with missing values, especially if they comprise a significant portion of your data. df.dropna(inplace=True) 2. Outliers: Outliers can significantly skew your results. Here’s how you can detect