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I am new to box plots and I am trying to understand it. Consider the following figures :

enter image description here

According to my understanding, outliers will exist after the max. line and before the min. line. So according to the above figures, we can see that outliers exist ( except for the EXT_Source 2 and EXT_Source 3 attributes) , which are labelled as black small circles after the max. value of each variable, am I right ??

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Your interpretation of a boxplot is correct.

But outlier definition in general terms is subjective... to simplify the idea let´s consider just the top outliers (but probably you should consider the bottom ones too): you could use the 1% top values to consider them outliers, or do as the boxplot does and take the ones that exceed Q3 + 1.5 IQR, or do as Tukey and consider Q3 + 3IQR.

If you use R, you could leverage this chapter of the Data Science Live Book

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