First: mplfinance is a super great program for helping with my stock trading: thank you.
Once a week, I download, and use mplfinance to graph the stocks on the S&P 500. I would like to scan the stocks using the P&F charting method and identify the stocks where the last column contains three or more "X" plots without having to physically view each chart. I would appreciate any ideas.
Thanks,
Manny
New version (0.12.7a12
) of mplfinance is now released:
pip install --upgrade mplfinance
In this version, if you do the following:
cv = {}
mpf.plot(df,type=pnf,return_calculated_values=cv)
Then the "calculated values" dict, cv
, will be filled with the following items:
dict_keys(['pnf_dates', 'pnf_counts', 'pnf_values', 'pnf_avgvals',
'pnf_size', 'pnf_volumes', 'minx', 'maxx', 'miny', 'maxy'])
cv['pnf_counts']
will contain the number of boxes for each date in cv['pnf_dates']
. It will be a positive value for up boxes, X, and a negative value for down boxes, O.cv['pnf_values']
will be a list of lists. The outer list corresponds to each pnf date, and the inner list at each date corresponds to the beginning value of each box on that date: "beginning" means it is the lower bound of an upward box, or the upper bound of a downward box. For an upward box, the X spans from this value to (value + pnf_size), and for a downward box, the O spans from this value to (value - pnf_size)cv['pnf_avgvals']
is the average of all pnf_values for a given date, and is the same as pnf_bricks
that was returned by the previous version of mplfinance.Hope this helps. All the best.