Keyboard Layout after startup reverts to "ABC - Extended" when using FileVault

If what you are looking at is simply filtering out points that are outliers (e.g. distance bigger than x), then a good solution that I used successfully in the past is to run a nearest neighbour algorithm and filter by maximum distance.

In python this can be achieved very efficiently and fast by using the sklearn package. An example code could be:

from sklearn.neighbors import NearestNeighbors
nn = NearestNeighbors(n_neighbors=2)
nn.fit(samples)
# for each point, the first match is the point itself, the second match is the actual nearest neighbour
indices, distances = nn.kneighbors(samples)
# you can now sort through the "distances" dataset to find values higher than you threshold and delete those entries

You may want to reproject your dataset to a projected coordinate reference system having meters as units. A simple way you can do it is by using geopandas (you mentioned dataframes, so I guess you are familiar with pandas)

samples.to_crs(epsg=3111)

However that can be achieved in many other ways.

NOTE: this method assumes that the outlier is an outlier of any cluster (e.g. away from ANY other point). If this is not the case the method will not work unless you repeat this step iteratively selecting one cluster at the time