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Fix 28021: Add 5% padding in timeseries line plot #57864

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Fix 28021: Add 5% padding in timeseries line plot #57864

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d7e47ba
Fix 28021: Add 5% padding in timeseries line plot
Compro-Prasad Mar 15, 2024
c16ff9a
Update tests for fixing 28021
Compro-Prasad Mar 16, 2024
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5 changes: 2 additions & 3 deletions pandas/plotting/_matplotlib/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1560,11 +1560,10 @@ def _make_plot(self, fig: Figure) -> None:
self._append_legend_handles_labels(newlines[0], label)

if self._is_ts_plot():
# reset of xlim should be used for ts data
# TODO: GH28021, should find a way to change view limit on xaxis
lines = get_all_lines(ax)
left, right = get_xlim(lines)
ax.set_xlim(left, right)
padding = (right - left) * 0.05
ax.set_xlim(left - padding, right + padding)

# error: Signature of "_plot" incompatible with supertype "MPLPlot"
@classmethod
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32 changes: 20 additions & 12 deletions pandas/tests/plotting/test_datetimelike.py
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Expand Up @@ -460,9 +460,8 @@ def test_get_finder(self):
def test_finder_daily(self):
day_lst = [10, 40, 252, 400, 950, 2750, 10000]

msg = "Period with BDay freq is deprecated"
with tm.assert_produces_warning(FutureWarning, match=msg):
xpl1 = xpl2 = [Period("1999-1-1", freq="B").ordinal] * len(day_lst)
xpl1 = [7565, 7564, 7553, 7546, 7518, 7428, 7066]
xpl2 = [7566, 7564, 7554, 7546, 7519, 7429, 7066]
rs1 = []
rs2 = []
for n in day_lst:
Expand All @@ -484,7 +483,8 @@ def test_finder_daily(self):
def test_finder_quarterly(self):
yrs = [3.5, 11]

xpl1 = xpl2 = [Period("1988Q1").ordinal] * len(yrs)
xpl1 = [68, 72]
xpl2 = [72, 72]
rs1 = []
rs2 = []
for n in yrs:
Expand All @@ -506,7 +506,8 @@ def test_finder_quarterly(self):
def test_finder_monthly(self):
yrs = [1.15, 2.5, 4, 11]

xpl1 = xpl2 = [Period("Jan 1988").ordinal] * len(yrs)
xpl1 = [216, 216, 204, 204]
xpl2 = [216, 216, 216, 204]
rs1 = []
rs2 = []
for n in yrs:
Expand Down Expand Up @@ -536,8 +537,7 @@ def test_finder_monthly_long(self):
assert rs == xp

def test_finder_annual(self):
xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]
xp = [Period(x, freq="Y").ordinal for x in xp]
xp = [16, 16, 20, 20, 25, 50, 0, 0]
rs = []
for nyears in [5, 10, 19, 49, 99, 199, 599, 1001]:
rng = period_range("1987", periods=nyears, freq="Y")
Expand All @@ -559,9 +559,8 @@ def test_finder_minutely(self):
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period("1/1/1999", freq="Min").ordinal

assert rs == xp
assert rs == 15248880

def test_finder_hourly(self):
nhours = 23
Expand All @@ -571,9 +570,8 @@ def test_finder_hourly(self):
ser.plot(ax=ax)
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period("1/1/1999", freq="h").ordinal

assert rs == xp
assert rs == 254206

def test_gaps(self):
ts = Series(
Expand Down Expand Up @@ -1541,7 +1539,15 @@ def test_plot_outofbounds_datetime(self):
ax.plot(values)

def test_format_timedelta_ticks_narrow(self):
expected_labels = [f"00:00:00.0000000{i:0>2d}" for i in np.arange(10)]
expected_labels = [
"-1 days 23:59:59.999999998",
"00:00:00.000000000",
"00:00:00.000000002",
"00:00:00.000000004",
"00:00:00.000000006",
"00:00:00.000000008",
"00:00:00.000000010",
]

rng = timedelta_range("0", periods=10, freq="ns")
df = DataFrame(np.random.default_rng(2).standard_normal((len(rng), 3)), rng)
Expand All @@ -1556,6 +1562,7 @@ def test_format_timedelta_ticks_narrow(self):

def test_format_timedelta_ticks_wide(self):
expected_labels = [
"-2 days 20:13:20",
"00:00:00",
"1 days 03:46:40",
"2 days 07:33:20",
Expand All @@ -1565,6 +1572,7 @@ def test_format_timedelta_ticks_wide(self):
"6 days 22:40:00",
"8 days 02:26:40",
"9 days 06:13:20",
"10 days 10:00:00",
]

rng = timedelta_range("0", periods=10, freq="1 d")
Expand Down
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