I have a pandas dataframe with few columns. Now I know that certain rows are outliers based on a certain column value. For instance column Vol has all values around 12xx and one value is 4000 (outl...
With scipy.stats.linregress I am performing a simple linear regression on some sets of highly correlated x,y experimental data, and initially visually inspecting each x,y scatter plot for outliers....
Linear outliers can be found by numpy std function, however, if the data is non-linear, for example, a parabola or cubic function, standard deviation will not handle the task well, since it needs regression to help working out the outliers.
So, I have a data set and know how to get the five number summary using the summary command. Now I need to get the instances above the Q3 + 1.5IQR or below the Q1 - 1.5IQR, since these are just num...
Identifying the outliers in a data set in R - Stack Overflow
A picture is worth a thousand words. Note that the outliers (the + markers in your plot) are simply points outside of the wide [(Q1-1.5 IQR), (Q3+1.5 IQR)] margin below. However, the picture is only an example for a normally distributed data set. It is important to understand that matplotlib does not estimate a normal distribution first and calculates the quartiles from the estimated ...
I like to perform calculation on each cell to the mean and sd to calculate the outliers. For example,
Yes, it is not good to remove 'outliers' from the data but sometimes you need the data without outliers for specific tasks. In an statistics assignment I had recently, we had to visualise a set without its outliers to determine the best regression model to use for the data. So there!