Here's a complete code snippet with mean +/- one standard deviation as well: import plotly.figure_factory as ff Line = dict(color = 'blue', dash = 'dash')) If that's the case you can calculate your measures using np.mean() and add that to the figure using: fig.add_shape(type="line",x0=mean, x1=mean, y0 =0, y1=0.4, xref='x', yref='y', You haven't specified how you'd like to display your added data, so I can only assume that this is what you're looking for: Title = 'Proper Motion Histogram + Gaussian distribution ', If (PM-4.5 and pmra1 and pmdec<3):Ĭolor = #Here we are onlly taking the range from tehabove contour plot where there is a Is there any other way to achieve the same results using any other plotly function? GAIA = pd.read_csv(r'C:\Users\Admin\Desktop\New folder\6 SEM Python\WORK\Astrometry\DistancePM.csv')ĭf = pd.DataFrame(GAIA, columns = ) I could not find anything which allows me to add more traces to this plot. 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.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |