First time poster, long time lurker
I have a dataframe with a structure as such:
columns = names, time, date, measurement, measurement2, measurement3
I want to create a plot using sub_plots (or whatever you recommend) that loops through names column and makes plots of measurement1 vs measurement2.
Further I want the sub_plots to be roughly square shaped and dynamically adjustable (e.g. if i have 34 unique names i want to have a 6 x 6 shaped plot matrix and fill 34 of the 36 plots), and if i have 20 names i want it to be a 5x5 shape etc.
Where i’m struggling is how to generate a separate plot for each of the “name” variable and then how to properly place those unique plots into the correct row and column of the sub_plot matrix.
I’ve attempted to do this using make_subplots, but was hoping there is a smarter way to do this by concatenating the plots into a square shaped matrix, thoughts?
sample code (probably not working)
fig = make_subplots(rows=max_row, cols=max_col) for i, name in enumerate(names,1): fig.add_trace(go.Scatter(x=df['measurement1'].loc[df.names==name], y=df['measurement2'].loc[df.names==name], name=name), #row=don't know what to put here, #col=don't know what to put herel,)