Simple map price when the diagram below is a continuous curve,
but once time as the x axis data is a discrete price curve, shown in the following figure,
I want a result is price curve is continuous, but the following can happen time corresponds to the price, help you a great god, and see if there are any good method?
Source code is too large, contains data for everybody great god help debugging, on the 1st floor, thank you!
CodePudding user response:
Code data on we
# coding=utf-8
The from __future__ import division
The import matplotlib. Pyplot as PLT
The import pandas as pd
Duan="-- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -" # of difference in the console line breaks
If __name__=="__main__" :
Nump_array_date=[' 20170808210000 ', '20170808210100', '20170808210200', '20170808210300'
, '20170808210400', '20170808210500', '20170808210600', '20170808210700'
, '20170808210800', '20170808210900', '20170808211000', '20170808211100'
, '20170808211200', '20170808211300', '20170808211400', '20170808211500'
, '20170808211600', '20170808211700', '20170808211800', '20170808211900'
, '20170808212000', '20170808212100', '20170808212200', '20170808212300'
, '20170808212400', '20170808212500', '20170808212600', '20170808212700'
, '20170808212800', '20170808212900', '20170808213000', '20170808213100'
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, '20170808213600', '20170808213700', '20170808213800', '20170808213900'
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, '20170808220400', '20170808220500', '20170808220600', '20170808220700'
, '20170808220800', '20170808220900', '20170808221000', '20170808221100'
, '20170808221200', '20170808221300', '20170808221400', '20170808221500'
, '20170808221600', '20170808221700', '20170808221800', '20170808221900'
, '20170808222000', '20170808222100', '20170808222200', '20170808222300'
, '20170808222400', '20170808222500', '20170808222600', '20170808222700'
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, '20170808224400', '20170808224500', '20170808224600', '20170808224700'
, '20170808224800', '20170808224900', '20170808225000', '20170808225100'
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, '20170809092700', '20170809092800', '20170809092900', '20170809093000'
, '20170809093100', '20170809093200', '20170809093300', '20170809093400'
, '20170809093500', '20170809093600', '20170809093700', '20170809093800'
, '20170809093900', '20170809094000', '20170809094100', '20170809094200'
, '20170809094300', '20170809094400', '20170809094500', '20170809094600'
, '20170809094700', '20170809094800', '20170809094900', '20170809095000'
, '20170809095100', '20170809095200', '20170809095300', '20170809095400'
, '20170809095500', '20170809095600', '20170809095700', '20170809095800'
, '20170809095900', '20170809100000', '20170809100100', '20170809100200'
, '20170809100300', '20170809100400', '20170809100500', '20170809100600'
, '20170809100700', '20170809100800', '20170809100900', '20170809101000'
, '20170809101100', '20170809101200', '20170809101300', '20170809101400'
, '20170809103000', '20170809103100', '20170809103200', '20170809103300'
, '20170809103400', '20170809103500', '20170809103600', '20170809103700'
, '20170809103800', '20170809103900', '20170809104000', '20170809104100'
, '20170809104200', '20170809104300', '20170809104400', '20170809104500'
nullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnull