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DEPR: implicit resample in plotting #62433

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fdeeb05
Comment that BDay deprecation is unnecessary in one case
jbrockmendel Sep 24, 2025
f88403b
DEPR: secondary_y plotting with implicit resample
jbrockmendel Sep 24, 2025
918e63e
Merge branch 'main' into depr-plotting-resample
jbrockmendel Sep 25, 2025
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17 changes: 16 additions & 1 deletion pandas/plotting/_matplotlib/timeseries.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,8 @@
OFFSET_TO_PERIOD_FREQSTR,
FreqGroup,
)
from pandas.errors import Pandas4Warning
from pandas.util._exceptions import find_stack_level

from pandas.core.dtypes.generic import (
ABCDatetimeIndex,
Expand Down Expand Up @@ -74,6 +76,13 @@ def maybe_resample(series: Series, ax: Axes, kwargs: dict[str, Any]):
series = series.to_period(freq=freq)

if ax_freq is not None and freq != ax_freq:
warnings.warn(
"Plotting with mixed-frequency series is deprecated and "
"will raise in a future version. Align series frequencies "
"before plotting instead.",
Comment on lines +81 to +82
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Could go as far to suggest f"Call series.resample('{freq}') ..."?

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Sure.

But now im wondering how much this will even help in moving towards #54485. In order to check if we're in this situation we still need the state information attached somehow.

I know "nuke it from space" isn't a viable approach to the plotting code, but it is really really bad.

Pandas4Warning,
stacklevel=find_stack_level(),
)
if is_superperiod(freq, ax_freq): # upsample input
series = series.copy()
# error: "Index" has no attribute "asfreq"
Expand Down Expand Up @@ -293,7 +302,13 @@ def maybe_convert_index(ax: Axes, data: NDFrameT) -> NDFrameT:
if isinstance(data.index, ABCDatetimeIndex):
data = data.tz_localize(None).to_period(freq=freq_str)
elif isinstance(data.index, ABCPeriodIndex):
data.index = data.index.asfreq(freq=freq_str, how="start")
# This will convert e.g. freq="60min" to freq="min", but will
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this bit is unrelated, can revert and do it in a separate branch

# retain type(freq). It is not clear to @jbrockmendel why
# this is necessary as of 2025-09-24, but 18 tests fail
# without it.
new_freq = to_offset(freq_str, is_period=True)
assert type(new_freq) is type(data.index.freq)
data.index = data.index.asfreq(freq=new_freq, how="start")
return data


Expand Down
56 changes: 43 additions & 13 deletions pandas/tests/plotting/test_datetimelike.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
BaseOffset,
to_offset,
)
from pandas.errors import Pandas4Warning

from pandas.core.dtypes.dtypes import PeriodDtype

Expand Down Expand Up @@ -628,7 +629,10 @@ def test_gap_upsample(self):

idxh = date_range(low.index[0], low.index[-1], freq="12h")
s = Series(np.random.default_rng(2).standard_normal(len(idxh)), idxh)
s.plot(secondary_y=True)

msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
s.plot(secondary_y=True)
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it isn't clear to me why the warning is emitted here since ax isn't passed. if that keyword isn't the relevant factor in deciding if the statefulness is needed, then #62442 may not achieve its goals

lines = ax.get_lines()
assert len(lines) == 1
assert len(ax.right_ax.get_lines()) == 1
Expand Down Expand Up @@ -821,7 +825,9 @@ def test_mixed_freq_hf_first(self):
low = Series(np.random.default_rng(2).standard_normal(len(idxl)), idxl)
_, ax = mpl.pyplot.subplots()
high.plot(ax=ax)
low.plot(ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
low.plot(ax=ax)
for line in ax.get_lines():
assert PeriodIndex(data=line.get_xdata()).freq == "D"

Expand All @@ -834,7 +840,9 @@ def test_mixed_freq_alignment(self):

_, ax = mpl.pyplot.subplots()
ax = ts.plot(ax=ax)
ts2.plot(style="r", ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
ts2.plot(style="r", ax=ax)

assert ax.lines[0].get_xdata()[0] == ax.lines[1].get_xdata()[0]

Expand All @@ -845,7 +853,9 @@ def test_mixed_freq_lf_first(self):
low = Series(np.random.default_rng(2).standard_normal(len(idxl)), idxl)
_, ax = mpl.pyplot.subplots()
low.plot(legend=True, ax=ax)
high.plot(legend=True, ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
high.plot(legend=True, ax=ax)
for line in ax.get_lines():
assert PeriodIndex(data=line.get_xdata()).freq == "D"
leg = ax.get_legend()
Expand All @@ -859,7 +869,9 @@ def test_mixed_freq_lf_first_hourly(self):
low = Series(np.random.default_rng(2).standard_normal(len(idxl)), idxl)
_, ax = mpl.pyplot.subplots()
low.plot(ax=ax)
high.plot(ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
high.plot(ax=ax)
for line in ax.get_lines():
assert PeriodIndex(data=line.get_xdata()).freq == "min"

Expand Down Expand Up @@ -952,7 +964,9 @@ def test_to_weekly_resampling(self):
low = Series(np.random.default_rng(2).standard_normal(len(idxl)), idxl)
_, ax = mpl.pyplot.subplots()
high.plot(ax=ax)
low.plot(ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
low.plot(ax=ax)
for line in ax.get_lines():
assert PeriodIndex(data=line.get_xdata()).freq == idxh.freq

Expand All @@ -963,7 +977,9 @@ def test_from_weekly_resampling(self):
low = Series(np.random.default_rng(2).standard_normal(len(idxl)), idxl)
_, ax = mpl.pyplot.subplots()
low.plot(ax=ax)
high.plot(ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
high.plot(ax=ax)

expected_h = idxh.to_period().asi8.astype(np.float64)
expected_l = np.array(
Expand Down Expand Up @@ -995,7 +1011,9 @@ def test_from_resampling_area_line_mixed(self, kind1, kind2):

_, ax = mpl.pyplot.subplots()
low.plot(kind=kind1, stacked=True, ax=ax)
high.plot(kind=kind2, stacked=True, ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
high.plot(kind=kind2, stacked=True, ax=ax)

# check low dataframe result
expected_x = np.array(
Expand Down Expand Up @@ -1050,7 +1068,9 @@ def test_from_resampling_area_line_mixed_high_to_low(self, kind1, kind2):
)
_, ax = mpl.pyplot.subplots()
high.plot(kind=kind1, stacked=True, ax=ax)
low.plot(kind=kind2, stacked=True, ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
low.plot(kind=kind2, stacked=True, ax=ax)

# check high dataframe result
expected_x = idxh.to_period().asi8.astype(np.float64)
Expand Down Expand Up @@ -1097,7 +1117,9 @@ def test_mixed_freq_second_millisecond(self):
# high to low
_, ax = mpl.pyplot.subplots()
high.plot(ax=ax)
low.plot(ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
low.plot(ax=ax)
assert len(ax.get_lines()) == 2
for line in ax.get_lines():
assert PeriodIndex(data=line.get_xdata()).freq == "ms"
Expand All @@ -1111,7 +1133,9 @@ def test_mixed_freq_second_millisecond_low_to_high(self):
# low to high
_, ax = mpl.pyplot.subplots()
low.plot(ax=ax)
high.plot(ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
high.plot(ax=ax)
assert len(ax.get_lines()) == 2
for line in ax.get_lines():
assert PeriodIndex(data=line.get_xdata()).freq == "ms"
Expand Down Expand Up @@ -1248,7 +1272,9 @@ def test_secondary_upsample(self):
low = Series(np.random.default_rng(2).standard_normal(len(idxl)), idxl)
_, ax = mpl.pyplot.subplots()
low.plot(ax=ax)
ax = high.plot(secondary_y=True, ax=ax)
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
ax = high.plot(secondary_y=True, ax=ax)
for line in ax.get_lines():
assert PeriodIndex(line.get_xdata()).freq == "D"
assert hasattr(ax, "left_ax")
Expand Down Expand Up @@ -1483,7 +1509,11 @@ def test_secondary_y_mixed_freq_ts_xlim(self):
_, ax = mpl.pyplot.subplots()
ts.plot(ax=ax)
left_before, right_before = ax.get_xlim()
ts.resample("D").mean().plot(secondary_y=True, ax=ax)

rs = ts.resample("D").mean()
msg = "Plotting with mixed-frequency series is deprecated"
with tm.assert_produces_warning(Pandas4Warning, match=msg):
rs.plot(secondary_y=True, ax=ax)
left_after, right_after = ax.get_xlim()

# a downsample should not have changed either limit
Expand Down
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