Feature Request: Multiple time frame plot

[hubofjon]

Is your feature request related to a problem? Please describe. "Monthly-Weekly-Daily" horizonal view is very helpful

Describe the solution you'd like Maybe a wrapper on top of exiting functions, eg. mpl_plot_multiple_frame( horizonal_frame=3) and in current functions add one more arg: eg. horizonal_frame_no= 1, just an idea, bet you could achieve it with better solutions Describe alternatives you've considered A clear and concise description of any alternative solutions or features you've considered.

Additional context Add any other context or screenshots about the feature request here.

[DanielGoldfarb]

@hubofjon Looking into this. I am curious to know if you have tried yet making such a wrapper.

I have been thinking from time to time to extend the panels method to be able to also handle horizontal colums of panels. It is definitely do-able, but not trivial so I have been putting it off in favor of other simpler enhancements for the time being. I'd like to do something like this within the next few months.

Please let me know if you have done any experimenting with this on your own. Thanks. --Daniel

[hubofjon]

hi Daniel, Glad that it is on your list. I uses subplot method to achieve this to some extent -but using 'ax' is just plain plot(code below). Instead of plotting each ax separately, I'd love to see a mpf wrapper to extend the panel, or alternatively, similar to subplot concept, allowing 1*N , each subplot can be an independent mpf plot. just my two cents

--part of my code as concept-- fig, ax = plt.subplots(nrows=6, ncols=2, figsize=(16, 16)) ax1, ax2, ax3, ax4, ax5, ax6, ax7, ax8, ax9, ax10, ax11, ax12 = ax.flatten() ax1=p_mdate(ax1) df['close'].plot(x=df['date'],kind='line', title='daily_close', ax=ax1)

ax2=p_mdate(ax2)
plt.sca(ax2)
df['close_weekly'].plot(x=df['date'],kind='line', title='weeky_close', ax=ax2)

[hubofjon]

btw, approach-1 can be 'panel extension' - constraints is that data source is the same, but allow different time frame, like M-W-D approach--2 is 'subplot 1*N', each sub can have its own data source, ie, an independent mpf plot (if this approach is easier to tackle first)