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Identify and Treat Outliers using Python and Excel | One Feature Example with Inter Quartile Range
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In this video, you will learn how to identify and treat Outliers from one feature using Excel and Python.
To write a code in Python, we first need to identify one feature and perform a boxplot on it. This will help us identify if there are outliers in the feature. Then we use the Interquartile range to calculate upper and lower whisker. Using those calculations, we can either choose to remove the outliers or treat them by replacing with the mean, median, mode or the upper and lower whisker values.
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To write a code in Python, we first need to identify one feature and perform a boxplot on it. This will help us identify if there are outliers in the feature. Then we use the Interquartile range to calculate upper and lower whisker. Using those calculations, we can either choose to remove the outliers or treat them by replacing with the mean, median, mode or the upper and lower whisker values.
Join Data Science Masterminds Hub:
Follow me:
Support: