python - Issue with matplotlib formatting using pandas -

i'm looking on issue have graphs.

i'm trying plot financial data contained inside dataframe dates , hours index, however, matplotlib standard dates formatting doesn't trick here don't want evenly spread ticks on x axis, shows big horizontal lines between business hours.

the solution came plot graph using np.arange on x axis, , use index label on x axis, not using matplotlib date formatting, still displaying dates on graph.

my code following:

l = np.arange(len(dax_m15.index))  def format_date(x, pos=none):     return dax_m15.index[x].strftime("%y-%m-%d %h-%m-%s")  fig, ax = plt.subplots() ax.plot(l, dax_m15["open"]) ax.xaxis.set_major_formatter(ticker.funcformatter(format_date)) ax.set_title("custom tick formatter") fig.autofmt_xdate() 

however, following error when using this:

 file "d:\anaconda\lib\site-packages\matplotlib\backends\backend_qt5agg.py", line 197, in __draw_idle_agg     figurecanvasagg.draw(self)   file "d:\anaconda\lib\site-packages\matplotlib\backends\backend_agg.py", line 464, in draw     self.figure.draw(self.renderer)   file "d:\anaconda\lib\site-packages\matplotlib\artist.py", line 63, in draw_wrapper     draw(artist, renderer, *args, **kwargs)   file "d:\anaconda\lib\site-packages\matplotlib\figure.py", line 1144, in draw     renderer, self, dsu, self.suppresscomposite)   file "d:\anaconda\lib\site-packages\matplotlib\image.py", line 139, in _draw_list_compositing_images     a.draw(renderer)   file "d:\anaconda\lib\site-packages\matplotlib\artist.py", line 63, in draw_wrapper     draw(artist, renderer, *args, **kwargs)   file "d:\anaconda\lib\site-packages\matplotlib\axes\_base.py", line 2426, in draw     mimage._draw_list_compositing_images(renderer, self, dsu)   file "d:\anaconda\lib\site-packages\matplotlib\image.py", line 139, in _draw_list_compositing_images     a.draw(renderer)   file "d:\anaconda\lib\site-packages\matplotlib\artist.py", line 63, in draw_wrapper     draw(artist, renderer, *args, **kwargs)   file "d:\anaconda\lib\site-packages\matplotlib\axis.py", line 1136, in draw     ticks_to_draw = self._update_ticks(renderer)   file "d:\anaconda\lib\site-packages\matplotlib\axis.py", line 969, in _update_ticks     tick_tups = [t t in self.iter_ticks()]   file "d:\anaconda\lib\site-packages\matplotlib\axis.py", line 969, in <listcomp>     tick_tups = [t t in self.iter_ticks()]   file "d:\anaconda\lib\site-packages\matplotlib\axis.py", line 916, in iter_ticks     i, val in enumerate(majorlocs)]   file "d:\anaconda\lib\site-packages\matplotlib\axis.py", line 916, in <listcomp>     i, val in enumerate(majorlocs)]   file "d:\anaconda\lib\site-packages\matplotlib\ticker.py", line 386, in __call__     return self.func(x, pos)   file "d:/finance python/test_data_formatter.py", line 40, in format_date     return dax_m15.index[x].strftime("%y-%m-%d %h-%m-%s")   file "d:\anaconda\lib\site-packages\pandas\tseries\base.py", line 247, in __getitem__     raise valueerror valueerror 

would have idea on issue here , how solve it?

thanks.

as said in comments, problem index of list or series needs integer between 0 , length of list. dax_m15.index[4.5] not work.

in order ensure locations have datapoint associated them ticked, may use matplotlib.ticker.indexlocator. e.g. if want label every fifth point of list,

ax.xaxis.set_major_locator(ticker.indexlocator(5,0)) ax.xaxis.set_major_formatter(ticker.funcformatter(format_date)) 

inside formatter need make sure index integer , within range of allowed values.

def format_date(x, pos=none):     if int(x) >= len(df.index) or int(x) < 0: return ""     return df.index[int(x)].strftime("%y-%m-%d %h-%m-%s") 

a complete example:

import matplotlib.pyplot plt import matplotlib.ticker ticker import numpy np import pandas pd  inx = pd.datetimeindex(start="2017-05-05", freq="7h", periods=45) df = pd.dataframe({"open" : np.random.rand(len(inx))}, index=inx)   l = np.arange(len(df.index))  def format_date(x, pos=none):     return df.index[int(x)].strftime("%y-%m-%d %h-%m-%s")  fig, ax = plt.subplots() ax.plot(l, df["open"]) ax.xaxis.set_major_locator(ticker.indexlocator(5,0)) ax.xaxis.set_major_formatter(ticker.funcformatter(format_date)) ax.set_title("custom tick formatter") fig.autofmt_xdate()  plt.show()