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I am having trouble with some coding of using a specialized colorscale and the basemap

 levels=[35,45,55,65,75,85,95,105,115]
 CB_color_cycle = ['#377eb8', '#ff7f00', '#4daf4a','#f781bf', '#a65628', 
 '#984ea3','#999999', '#e41a1c', '#dede00']
 fig=plt.figure(501)
 m=Basemap(projection='merc',llcrnrlat=27,urcrnrlat=47,llcrnrlon=234,urcrnrlon=285,resolution='h')

 px,py=N.meshgrid(lon+360,lat,sparse="True")
 X,Y=m(px,py)


 m.drawcoastlines()
 m.drawcountries()
 m.drawstates()
 m.fillcontinents(color='gray',alpha=0.1,lake_color='aqua')
 m.drawcounties()


 #plotting contours

 cs=m.contourf(lon+360,lat,tempsfc,levels=levels,cmap=CB_color_cycle,latlon=True,extend='both')
cs2=m.contour(lon+360,lat,tempsfc,levels=levels,latlon=True,colors='k',linestyles='solid')

 cbar=plt.colorbar(cs)
 cbar.add_lines(cs2)
 cbar.ax.set_ylabel('Temp F')

 plt.suptitle("SFC Temperature June 26,2017 at 19Z")
 plt.show()

But I got this error although I have experience with Python, I have never had to deal with this before as I am trying to use a special color scale.

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmpl_toolkitsbasemap__init__.py:3608: MatplotlibDeprecationWarning: The ishold function was deprecated in version 2.0.
 b = ax.ishold()
C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmpl_toolkitsbasemap__init__.py:3675: MatplotlibDeprecationWarning: axes.hold is deprecated.
 See the API Changes document (http://matplotlib.org/api/api_changes.html)
 for more details.
 ax.hold(b)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
C:UsersstratusDocumentsTestforMattsPaper.py in <module>()
 36 #plotting contours
 37 
---> 38 cs=m.contourf(lon+360,lat,tempsfc,levels=levels,cmap=CB_color_cycle,latlon=True,extend='both')
 39 cs2=m.contour(lon+360,lat,tempsfc,levels=levels,latlon=True,colors='k',linestyles='solid')
 40 

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmpl_toolkitsbasemap__init__.pyc in with_transform(self, x, y, data, *args, **kwargs)
 519 # convert lat/lon coords to map projection coords.
 520 x, y = self(x,y)
--> 521 return plotfunc(self,x,y,data,*args,**kwargs)
 522 return with_transform
 523 

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmpl_toolkitsbasemap__init__.pyc in contourf(self, x, y, data, *args, **kwargs)
 3671 mask = np.logical_or(ma.getmaskarray(data),xymask)
 3672 data = ma.masked_array(data,mask=mask)
-> 3673 CS = ax.contourf(x,y,data,*args,**kwargs)
 3674 except:
 3675 ax.hold(b)

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmatplotlib__init__.pyc in inner(ax, *args, **kwargs)
 1890 warnings.warn(msg % (label_namer, func.__name__),
 1891 RuntimeWarning, stacklevel=2)
-> 1892 return func(ax, *args, **kwargs)
 1893 pre_doc = inner.__doc__
 1894 if pre_doc is None:

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmatplotlibaxes_axes.pyc in contourf(self, *args, **kwargs)
 5827 self.cla()
 5828 kwargs['filled'] = True
-> 5829 contours = mcontour.QuadContourSet(self, *args, **kwargs)
 5830 self.autoscale_view()
 5831 return contours

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmatplotlibcontour.pyc in __init__(self, ax, *args, **kwargs)
 862 self._transform = kwargs.get('transform', None)
 863 
--> 864 self._process_args(*args, **kwargs)
 865 self._process_levels()
 866 

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmatplotlibcontour.pyc in _process_args(self, *args, **kwargs)
 1427 self._corner_mask = mpl.rcParams['contour.corner_mask']
 1428 
-> 1429 x, y, z = self._contour_args(args, kwargs)
 1430 
 1431 _mask = ma.getmask(z)

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmatplotlibcontour.pyc in _contour_args(self, args, kwargs)
 1518 warnings.warn('Log scale: values of z <= 0 have been masked')
 1519 self.zmin = float(z.min())
-> 1520 self._contour_level_args(z, args)
 1521 return (x, y, z)
 1522 

C:UsersstratusAppDataLocalEnthoughtCanopyUserlibsite-packagesmatplotlibcontour.pyc in _contour_level_args(self, z, args)
 1184 warnings.warn("Contour levels are not increasing")
 1185 else:
-> 1186 raise ValueError("Contour levels must be increasing")
 1187 
 1188 def _process_levels(self):

ValueError: Contour levels must be increasing

The indenting is not the problem but rather the CB_color_cycle since I am trying to help a friend with coding for colorblindness.

CB_color_cycle is just a list of colors, so use the colors keyword instead of cmap:

cs = m.contourf(lon+360, lat, tempsfc, levels=levels, colors=CB_color_cycle, latlon=True, extend='both')

Here's what it says about the colors keyword in the contourf docs:

colors : color string or sequence of colors, optional
The colors of the levels, i.e. the lines for contour and the areas for contourf.

The sequence is cycled for the levels in ascending order. If the sequence is shorter than the number of levels, it's repeated.

As a shortcut, single color strings may be used in place of one-element lists, i.e. 'red' instead of ['red'] to color all levels with the same color. This shortcut does only work for color strings, not for other ways of specifying colors.

By default (value None), the colormap specified by cmap will be used.

If you were actually trying to do something fancier involving a real ColorMap, see the documentation for ListedColorMap or LinearSegmentedColormap (and maybe also this SO answer) for details on converting a list of colors into a proper ColorMap.