continuous-error-bars.md

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jupytext kernelspec language_info plotly notebook_metadata_filter text_representation all extension format_name format_version jupytext_version .md markdown 1.2 1.4.2 display_name language name Python 3 python python3 codemirror_mode file_extension mimetype name nbconvert_exporter pygments_lexer version name version ipython 3 .py text/x-python python python ipython3 3.7.7 description display_as language layout name order page_type permalink thumbnail Add continuous error bands to charts in Python with Plotly. statistical python base Continuous Error Bands 15 u-guide python/continuous-error-bars/ thumbnail/error-cont.jpg

Continuous error bands are a graphical representation of error or uncertainty as a shaded region around a main trace, rather than as discrete whisker-like error bars. They can be implemented in a manner similar to filled area plots using scatter traces with the fill attribute.

Filling within a single trace

In this example we show how to construct a trace that goes from low to high X values along the upper Y edge of a region, and then from high to low X values along the lower Y edge of the region. This trace is then 'self-filled' using fill='toself'.

importplotly.graph_objsasgox= [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] y= [1, 2, 7, 4, 5, 6, 7, 8, 9, 10] y_upper= [2, 3, 8, 5, 6, 7, 8, 9, 10, 11] y_lower= [0, 1, 5, 3, 4, 5, 6, 7, 8, 9] fig=go.Figure([ go.Scatter( x=x, y=y, line=dict(color='rgb(0,100,80)'), mode='lines' ), go.Scatter( x=x+x[::-1], # x, then x reversedy=y_upper+y_lower[::-1], # upper, then lower reversedfill='toself', fillcolor='rgba(0,100,80,0.2)', line=dict(color='rgba(255,255,255,0)'), hoverinfo="skip", showlegend=False ) ]) fig.show()

Filling between two traces

In this example we show how to construct the bounds of the band using two traces, with the lower trace using fill='tonexty' to fill an area up to the upper trace.

importplotly.graph_objsasgoimportpandasaspddf=pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/wind_speed_laurel_nebraska.csv') fig=go.Figure([ go.Scatter( name='Measurement', x=df['Time'], y=df['10 Min Sampled Avg'], mode='lines', line=dict(color='rgb(31, 119, 180)'), ), go.Scatter( name='Upper Bound', x=df['Time'], y=df['10 Min Sampled Avg']+df['10 Min Std Dev'], mode='lines', marker=dict(color="#444"), line=dict(width=0), showlegend=False ), go.Scatter( name='Lower Bound', x=df['Time'], y=df['10 Min Sampled Avg']-df['10 Min Std Dev'], marker=dict(color="#444"), line=dict(width=0), mode='lines', fillcolor='rgba(68, 68, 68, 0.3)', fill='tonexty', showlegend=False ) ]) fig.update_layout( yaxis=dict(title=dict(text='Wind speed (m/s)')), title=dict(text='Continuous, variable value error bars'), hovermode="x" ) fig.show()