title: Remove outliers from a ggplotly() boxplot
body: <p>I have the dataframe below:</p>
  
  <pre><code>etf_id&lt;-c("a","b","c","d","e","a","b","c","d","e","a","b","c","d","e")
  factor&lt;-c("A","A","A","A","A","B","B","B","B","B","C","C","C","C","C")
  normalized&lt;-c(-0.048436801,2.850578601,2.551666490,0.928625186,-0.638111793,
                -0.540615895,-0.501691539,-1.099239823,-0.040736139,-0.192048665,
                0.198915407,-0.092525810,0.214317734,2.550478998,0.024613778)
  df&lt;-data.frame(etf_id,factor,normalized)
  </code></pre>
  
  <p>and Im trying to remove outliers with 2 ways. First I try with <code>outlier.color = NA,outlier.size = 0,outlier.shape = NA</code>:</p>
  
  <pre><code>library(ggplot2)
  library(plotly)
  ggplotly(df %&gt;% 
    ggplot(aes(factor, normalized, color = factor)) +
    geom_boxplot(outlier.color = NA,outlier.size = 0,outlier.shape = NA) +
    coord_cartesian(ylim = quantile(df$normalized, c(0.01, 0.99), na.rm = T)))
  </code></pre>
  
  <p>Second example with diamonds dataset.</p>
  
  <pre><code>p&lt;-ggplotly(diamonds %&gt;% 
    ggplot(aes(cut,price, color = cut)) +
    geom_boxplot(outlier.color = NA,outlier.size = 0,outlier.shape = NA))
  </code></pre>
  
  <p>Then I try with:</p>
  
  <pre><code>ggplotly(df %&gt;% 
    ggplot(aes(factor, normalized, color = factor)) +
    geom_boxplot(outlier.color = NA,outlier.size = 0,outlier.shape = NA) +
    coord_cartesian(ylim = quantile(boxplot.stats(df$normalized)$stats[c(1, 5)]*1.5, c(0.01, 0.99), na.rm = T)))
  </code></pre>
  
  <p>but this way seems to cut my plot y limits and I need a generic solution.</p>