Can you remove outliers if they are less than 10% of the datapoints? We have to try and consider the data generating process before we take action, such as deleting outliers Rules of thumb are useful sometimes, but you need to investigate whether they are appropriate for each particular project by using sensitivity analysis or diagnostic tests of the model
Detect and Remove the Outliers using Python - GeeksforGeeks For example when visualizing a dataset with a few extreme values, it might find meaningful patterns in the majority of the data By removing or handling outliers, we prevent these issues and ensure more accurate analysis and predictions Methods for Detecting and Removing Outliers There are several ways to detect and handle outliers in Python
Removing outliers - Crunching the Data Are you wondering how to treat the outliers in your dataset? In this article we tell you everything you need to know about handling and removing outliers
How to Detect, Handle and Visualize Outliers - Towards Data Science In statistics, an outlier is a data point that differs significantly from other observations An outlier may be due to variability in the measurement or it may indicate experimental error; the latter are sometimes excluded from the data set