A substantial aspect of any effective data analysis pipeline is addressing null values. These instances, often represented as N/A, can negatively impact statistical models and data visualization. Ignoring these records can lead to biased results and incorrect conclusions. Strategies for dealing with missing data include replacement with median valu… Read More