I’ve spent almost a week trying to get why is plotly doing this with my data. Now I’m giving up and asking for your kind help.
I have two frame columns that I want to graph using a scatter plot. Both of them correspond to measurements at various time instants.
In the above you can appreciate the resulting scatter plot as well as some points of the X-column. There, my problem is easy to understand: the upper value in the plot corresponds to the 1.61E+12 in red to the right while the precedent one is the 8.06E+11 also in red to the right. It means that plotly is ignoring the points in the middle (positions 43 to 46) and making a kind of extrapolation. Besides, it cuts the trace because the subsequent values in the X-column are lower than 1.61E+12. This “interpolation” issue is basically happening along the whole trace every time that X(t)>X(t+1).
I already verified the resulting fig object and all the data is duly passed. I only want to appreciate my measurement results along the time, even if there were oscillations, that is why, sorting my columns is not an option.
Basically, the code I’m using for the scatter plot is:
fig = px.scatter(x=frame[‘a’], y=frame[‘b’])
fig.update_traces(mode=‘lines+markers’, connectgaps=False, showlegend=True)
Then I update the layout to get the log scale in the axis as well as the scientific exponential notation.
Thank you in advance for your answer and for your help.