title: Plotly: How to add mean and standard deviation to a create_displot figure?
body: <p>I am trying to make changes to the histogram and the normal distribution curve here that is made using the create_distplot fuction in plotly. I could not find anything which allows me to add more traces to this plot. Is there any other way to achieve the same results using any other plotly function?</p>
  <pre><code>GAIA = pd.read_csv(r'C:\Users\Admin\Desktop\New folder\6 SEM Python\WORK\Astrometry\DistancePM.csv')
      df = pd.DataFrame(GAIA, columns = ['ra','dec','rest','b_rest','B_rest','pmra','pmra_error','pmdec','pmdec_error','PM'])
      ra = df['ra'].tolist()
      dec = df['dec'].tolist()
      rest = df['rest'].tolist()
      b_rest = df['b_rest'].tolist()
      B_rest = df['B_rest'].tolist()
      pmra = df['pmra'].tolist()
      pmra_E = df['pmra_error'].tolist()
      pmdec = df['pmdec'].tolist()
      pmdec_E = df['pmdec_error'].tolist()
      PM = df['PM'].tolist() 
      PM1 = []
      c = 0
      #Here we are onlly taking the range from tehabove contour plot where there is a 
      #clustering of data points x = [-4.5, 1.5] and y = [3, 1]
      for i in range(len(PM)):
          if (PM[i]&lt;100 and pmra[i]&gt;-4.5 and pmra[i]&lt;1.5 and pmdec[i]&gt;1 and pmdec[i]&lt;3):
              PM1.append(PM[i])
              c+=1
      group_labels = ['Proper Motion']
      color = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880', '#FF97FF', '#FECB52']    
      fig = ff.create_distplot(
          [PM1], 
          group_labels,
          bin_size = 0.05,
          curve_type='normal',
          colors = color
      )
      fig.update_layout(
          title = 'Proper Motion Histogram + Gaussian distribution ',
          xaxis = dict(
              title='Proper Motion'
          ),
          yaxis = dict(
              title='Density'
          ),
          template = 'plotly_dark',
          showlegend = True
      )
      fig.show()
      print(c)[![enter image description here][1]][1]
      
      
        [1]: https://i.stack.imgur.com/lOBvY.png
  </code></pre>
  <p><a href="https://i.stack.imgur.com/WDPCt.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/WDPCt.png" alt="This is how the figure looks like" /></a></p>