Is there a numpy builtin to reject outliers from a list

Question

Is there a numpy builtin to do something like the following? That is, take a list d and return a list filtered_d with any outlying elements removed

Answer 1

Building on Benjamin's, using pandas.Series, and replacing MAD with IQR:

def reject_outliers(sr, iq_range=0.5):
    pcnt = (1 - iq_range) / 2
    qlow, median, qhigh = sr.dropna().quantile([pcnt, 0.50, 1-pcnt])
    iqr = qhigh - qlow
    return sr[ (sr - median).abs() <= iqr]

For instance, if you set iq_range=0.6, the percentiles of the interquartile-range would become: 0.20 <--> 0.80, so more outliers will be included.