title: How to remove outliers correctly and visualize right skewed data clearly while piping?
body: <p>I am trying to solve the following problem:</p>
  <p>Need to visualize clearly this data that is right skewed. This is data from one column in my dataframe. See screenshot.</p>
  <p><a href="https://i.stack.imgur.com/MbhEb.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/MbhEb.png" alt="distribution column of data" /></a></p>
  <p>I managed to remove the outliers with the following script:</p>
  <pre><code>testdf &lt;- IdentifiedCars$ConnectionTimeHours[!IdentifiedCars$ConnectionTimeHours %in% boxplot.stats(IdentifiedCars$ConnectionTimeHours)$out]
  </code></pre>
  <p>How can I implement this piece of code in my current code (see below) to remove the outliers correctly of the ConnectionTimeHours column? The testdf script returns now a value ..</p>
  <pre><code>df_image_CTH &lt;- IdentifiedCars %&gt;%
    group_by(ConnectionTimeHours = round(ConnectionTimeHours, 0)) %&gt;%
    summarise(counts = n())
  
  theme_set(theme_bw())
  
  ggplot(df_image_CTH, aes(x=ConnectionTimeHours, y=counts)) + 
    geom_bar(stat=&quot;identity&quot;, width=.5, fill=&quot;tomato3&quot;) + 
    labs(title=&quot;Distribution ConnectionTimeHours&quot;) + 
    theme(axis.text.x = element_text(angle=0, vjust=0.5))
  </code></pre>
  <p>column of my data where I want remove outliers of:</p>
  <pre><code>dput(head(IdentifiedSixtShareCars$ConnectionTimeHours, 10))
  c(12.0102777777778, 0.00305555555555556, 6.29361111111111, 3.34416666666667, 
  1.43361111111111, 2.54472222222222, 3.86694444444444, 14.3997222222222, 
  1.3175, 1.75888888888889)
  </code></pre>