Technology Tales<p>Outliers are common in data across various industries. This guide by Iván Palomares Carrascosa details strategies to handle them, from removal to transformation, using Python. Techniques include removing outliers based on z-scores, applying transformations like logarithmic scaling, and capping/winsorizing values. <a href="https://mstdn.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataScience</span></a> <a href="https://mstdn.social/tags/Outliers" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Outliers</span></a> <a href="https://mstdn.social/tags/Python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Python</span></a> <a href="https://mstdn.social/tags/DataAnalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataAnalysis</span></a> <a href="https://www.kdnuggets.com/dealing-with-outliers-a-complete-guide" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">kdnuggets.com/dealing-with-out</span><span class="invisible">liers-a-complete-guide</span></a></p>