BUG: scatter and line matplotlib plots not compatible for sharex=True datetime plots

[jonbanks87]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

datetime_list = [datetime.datetime(year = 2025, month = 1, day = 1, hour = n) for n in range(23)]
y = [n for n in range(23)]

df = pd.DataFrame(columns = ['datetime','y'])
for i, n in enumerate(datetime_list):
    df.loc[len(df)] = [n,y[i]]

#Plotting with pandas - first subplot shows up as blank
fig, ax = plt.subplots(2, sharex=True)
df.plot.scatter(x = 'datetime', y = 'y', ax = ax[0])
df.plot(x = 'datetime', y = 'y', ax = ax[1])

#Plotting with matplotlib - this works
fig, ax = plt.subplots(2, sharex=True)
ax[0].scatter(df['datetime'],df['y'])
ax[1].plot(df['datetime'],df['y'])

Issue Description

When I am trying to plot a line plot and scatter plot using df.plot and df.plot.scatter, the scatter plot shows up as blank when I select sharex=True when making the figure and axes.

#Plotting with pandas - first subplot shows up as blank
fig, ax = plt.subplots(2, sharex=True)
df.plot.scatter(x = 'datetime', y = 'y', ax = ax[0])
df.plot(x = 'datetime', y = 'y', ax = ax[1])

However, if I plot using the standard matplotlib way of plotting (ax.scatter and ax.plot), both subplots show up correctly when I set sharex=True for the figure.

#Plotting with matplotlib - this works
fig, ax = plt.subplots(2, sharex=True)
ax[0].scatter(df['datetime'],df['y'])
ax[1].plot(df['datetime'],df['y'])

Expected Behavior

I would expect for the both subplots to show up, not blank. The behavior should be more similar to the traditional way of plotting with matplotlib.

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.13.1
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.3
numpy : 2.2.2
pytz : 2025.1
dateutil : 2.9.0.post0
pip : 24.3.1
Cython : None
sphinx : None
IPython : 8.32.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.5
lxml.etree : None
matplotlib : 3.10.0
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.15.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.1
qtpy : None
pyqt5 : None

[snitish]

I was able to reproduce the bug on main. This seems to be due to the two plots (scatter and line) having different xaxis types. The scatter plot keeps the 'datetime' column as is, but the line plot converts it to a PeriodIndex due to

pandas/pandas/plotting/_matplotlib/core.py

Line 1543 in d1ec1a4

data = maybe_convert_index(self._get_ax(0), self.data)

I was able to fix this by setting x_compat = True in the line plot:

df.plot(x = 'datetime', y = 'y', ax=ax[1], x_compat=True)

For a more robust fix, I'm guessing we should probably support automatic tick resolution in scatter plots similar to line plots?