@jonny-sexton wrote:
Hi all,
I am currently working on a Data Visualization project:
Is there any built-in function that enables me to automatically plot Regression lines and confidence intervals to this plot, or would I have to compute this manually from the scatter plot data and then plot this to the same graph? Checking the documentation I couldn’t find anything that supports this.
For reference, here is the code I am using for one of the plots:
dcc.Graph( id='km/h-speedcoefficient', figure={ 'data': [ dict( x=df[df['SpeedCoefficient'] == i]['SpeedCoefficient'], y=df[df['SpeedCoefficient'] == i]['Km/h'], text=df[df['SpeedCoefficient'] == i]['Subproject'], mode='markers', opacity=0.7, marker={ 'size': 15, 'line': {'width': 0.5, 'color': 'white'}, 'color': df[df['SpeedCoefficient'] == i]['SpeedCoefficient'], 'cmin': min(df['SpeedCoefficient']), 'cmax': max(df['SpeedCoefficient']), 'colorscale': [[0.0, '#01cdfe'], [1.0, '#ff71ce']],#"Bluered", 'autocolorscale': False, 'showscale': True }, name=i ) for i in df.SpeedCoefficient.unique() ], 'layout': dict( title={'text': 'Km/h per SpeedCoefficient (0.1, 0.5, 1.0)'}, xaxis={'type': 'lin', 'title': 'Speed Coefficient', 'color': 'white'}, yaxis={'title': 'Km/h', 'color': 'white'}, margin={'l': 40, 'b': 40, 't': 100, 'r': 10}, legend={'x': 0, 'y': 1}, showlegend=False, hovermode='closest', font={'color': 'white'}, paper_bgcolor='#303030', plot_bgcolor='#424242' ) } )Any help would be greatly appreciated, many thanks in advance!
Jonny
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