(This is my first StackOverflow question ever!)

I have a pandas dataframe that contains solar irradiance values in 15-minute intervals over the course of a single day. This dataframe's index is a "DatetimeIndex" (dtype='datetime64[ns, America/New_York]', and is localized to its respective timezone. So, the index values start as "1997-01-20 00:15:00-05:00", "1997-01-20 00:30:00-05:00" ... "1997-01-21 00:00:00-5:00" (notice the last entry is 12AM of the next day).

When plotting this dataframe (named poa_irradiance_swd_corrected) by itself, everything looks great. Here's an example of my code and its output:

Code:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter
import pvlib as pv
import datetime as dt
import math
import pytz
import time

plt.figure()
poa_irradiance_swd_corrected.plot().get_figure().set_facecolor('white')

Output:

The highest "poa_global" irradiance measurements in this dataframe are between 12:00 PM (noon) and 1:30-ish. This is accurate.

I also have two other dataframes (named poa_irradiance_swd_flat and modeled_poa_irradiance_swd) with similar irradiance measurements. To compare the irradiance measurements visually, I put all 3 dataframes into a single figure using matplotlib's subplot function. However, the X-axis of the subplots are very inaccurate. The code and output are shown below:

Code:

fig, axs = plt.subplots(2,2, sharex=True,sharey=True, facecolor='white',figsize=(12,8))
fig.suptitle('Sunny Winter Day',size='xx-large',weight='bold')
axs[0,0].plot(poa_irradiance_swd_flat)
axs[0,0].set_title('POA Irradiance (Flat)')
axs[0,1].plot(modeled_poa_irradiance_swd)
axs[0,1].set_title('Modeled Data (Tilted)')
axs[1,0].plot(poa_irradiance_swd_corrected)
axs[1,0].set_title('POA Irradiance (Tilted)')
axs[1,1].plot(modeled_poa_irradiance_swd)
axs[1,1].set_title('Modeled Data (Tilted)')
for axs in axs.flat:
    axs.set(ylabel='Irradiance $W/m^2$')
    axs.xaxis.set_major_formatter(DateFormatter('%H:%M'))
plt.tight_layout(pad=0, w_pad=0, h_pad=3)
fig.autofmt_xdate()

Output: Note that the two graphs on the right are the exact same. I simply used the graphs to the right to compare to the graphs to the left

Notice how the x-axis is completely off by 6-ish hours. I've cross-checked the dataframes themselves, and again, the highest irradiance times coincide with the times between 12:00 PM (noon) and around 1:30-ish... not around 18:00 (which is 6:00 PM and does not make sense). I even used the same exact dataframe in the axs[1,0].plot(poa_irradiance_swd_corrected) line of code.

How can I get the X-axis to display the accurate times?

EDIT (in response to scespinoza):

So I tried passing the respective .index and .values values from the dataframe, and it successfully plotted... but still with the same problem.

Then, I tried passing the ax commands into the plot function itself like this: poa_irradiance_swd_flat.plot(ax=axs[0, 0]) for each subplot. After importing matplotlib as mpl, I also added mpl.rcParams['timezone'] = 'UTC' to the top of my code.

Now, I'm getting a ValueError:

ValueError                                Traceback (most recent call last)
File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/IPython/core/formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/IPython/core/pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/backend_bases.py:2295, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2289     renderer = _get_renderer(
   2290         self.figure,
   2291         functools.partial(
   2292             print_method, orientation=orientation)
   2293     )
   2294     with getattr(renderer, "_draw_disabled", nullcontext)():
-> 2295         self.figure.draw(renderer)
   2297 if bbox_inches:
   2298     if bbox_inches == "tight":

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/artist.py:73, in _finalize_rasterization.<locals>.draw_wrapper(artist, renderer, *args, **kwargs)
     71 @wraps(draw)
     72 def draw_wrapper(artist, renderer, *args, **kwargs):
---> 73     result = draw(artist, renderer, *args, **kwargs)
     74     if renderer._rasterizing:
     75         renderer.stop_rasterizing()

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/figure.py:2810, in Figure.draw(self, renderer)
   2807         # ValueError can occur when resizing a window.
   2809 self.patch.draw(renderer)
-> 2810 mimage._draw_list_compositing_images(
   2811     renderer, self, artists, self.suppressComposite)
   2813 for sfig in self.subfigs:
   2814     sfig.draw(renderer)

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/axes/_base.py:3046, in _AxesBase.draw(self, renderer)
   3043     for spine in self.spines.values():
   3044         artists.remove(spine)
-> 3046 self._update_title_position(renderer)
   3048 if not self.axison:
   3049     for _axis in self._get_axis_list():

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/axes/_base.py:2986, in _AxesBase._update_title_position(self, renderer)
   2983 for ax in axs:
   2984     if (ax.xaxis.get_ticks_position() in ['top', 'unknown']
   2985             or ax.xaxis.get_label_position() == 'top'):
-> 2986         bb = ax.xaxis.get_tightbbox(renderer)
   2987     else:
   2988         bb = ax.get_window_extent(renderer)

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/axis.py:1103, in Axis.get_tightbbox(self, renderer, for_layout_only)
   1100 if not self.get_visible():
   1101     return
-> 1103 ticks_to_draw = self._update_ticks()
   1105 self._update_label_position(renderer)
   1107 # go back to just this axis's tick labels

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/axis.py:1046, in Axis._update_ticks(self)
   1041 """
   1042 Update ticks (position and labels) using the current data interval of
   1043 the axes.  Return the list of ticks that will be drawn.
   1044 """
   1045 major_locs = self.get_majorticklocs()
-> 1046 major_labels = self.major.formatter.format_ticks(major_locs)
   1047 major_ticks = self.get_major_ticks(len(major_locs))
   1048 self.major.formatter.set_locs(major_locs)

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/ticker.py:224, in Formatter.format_ticks(self, values)
    222 """Return the tick labels for all the ticks at once."""
    223 self.set_locs(values)
--> 224 return [self(value, i) for i, value in enumerate(values)]

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/ticker.py:224, in <listcomp>(.0)
    222 """Return the tick labels for all the ticks at once."""
    223 self.set_locs(values)
--> 224 return [self(value, i) for i, value in enumerate(values)]

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/dates.py:636, in DateFormatter.__call__(self, x, pos)
    635 def __call__(self, x, pos=0):
--> 636     result = num2date(x, self.tz).strftime(self.fmt)
    637     return _wrap_in_tex(result) if self._usetex else result

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/dates.py:528, in num2date(x, tz)
    526 if tz is None:
    527     tz = _get_rc_timezone()
--> 528 return _from_ordinalf_np_vectorized(x, tz).tolist()

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/numpy/lib/function_base.py:2163, in vectorize.__call__(self, *args, **kwargs)
   2160     vargs = [args[_i] for _i in inds]
   2161     vargs.extend([kwargs[_n] for _n in names])
-> 2163 return self._vectorize_call(func=func, args=vargs)

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/numpy/lib/function_base.py:2246, in vectorize._vectorize_call(self, func, args)
   2243 # Convert args to object arrays first
   2244 inputs = [asanyarray(a, dtype=object) for a in args]
-> 2246 outputs = ufunc(*inputs)
   2248 if ufunc.nout == 1:
   2249     res = asanyarray(outputs, dtype=otypes[0])

File ~/opt/miniconda3/envs/pvlib/lib/python3.10/site-packages/matplotlib/dates.py:350, in _from_ordinalf(x, tz)
    347 dt = (np.datetime64(get_epoch())  
    348       np.timedelta64(int(np.round(x * MUSECONDS_PER_DAY)), 'us'))
    349 if dt < np.datetime64('0001-01-01') or dt >= np.datetime64('10000-01-01'):
--> 350     raise ValueError(f'Date ordinal {x} converts to {dt} (using '
    351                      f'epoch {get_epoch()}), but Matplotlib dates must be '
    352                       'between year 0001 and 9999.')
    353 # convert from datetime64 to datetime:
    354 dt = dt.tolist()

ValueError: Date ordinal 14228655 converts to 40926-09-26T00:00:00.000000 (using epoch 1970-01-01T00:00:00), but Matplotlib dates must be between year 0001 and 9999.

CodePudding user response：

Can't really reproduce your problem, but maybe you can try passing the index and values of the series by separate to the plot function.

...
axs[0,0].plot(poa_irradiance_swd_flat.index, poa_irradiance_swd_flat.values)
...

Also, note that you can pass an ax attribute to the .plot() function of a Series, so you can refactor your code to something like this:

fig, axs = plt.subplots(2,2, sharex=True,sharey=True, facecolor='white',figsize=(12,8))
fig.suptitle('Sunny Winter Day',size='xx-large',weight='bold')
poa_irradiance_swd_flat.plot(ax=axs[0, 0])
axs[0,0].set_title('POA Irradiance (Flat)')
modeled_poa_irradiance_swd.plot(ax=axs[0, 1])
axs[0,1].set_title('Modeled Data (Tilted)')
poa_irradiance_swd_corrected.plot(ax=axs[1, 0])
axs[1,0].set_title('POA Irradiance (Tilted)')
modeled_poa_irradiance_swd.plot(ax=axs[1, 1])
axs[1,1].set_title('Modeled Data (Tilted)')
for axs in axs.flat:
    axs.set(ylabel='Irradiance $W/m^2$')
    # axs.xaxis.set_major_formatter(DateFormatter('%H:%M'))
plt.tight_layout(pad=0, w_pad=0, h_pad=3)
fig.autofmt_xdate()

Update

I think the error may come from DateFormatter converting the timezone of your date values. Try adding this on the top of your program.

import matplotlib as mpl

mpl.rcParams['timezone'] = 'UTC'