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Fix Axes.hist crash for numpy timedelta64 inputs #31203

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Merged
timhoffm merged 10 commits into from
Mar 11, 2026
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Merged

Fix Axes.hist crash for numpy timedelta64 inputs #31203

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2275f59
Fix Axes.hist crash for numpy timedelta64 inputs
jayaprajapatii Feb 26, 2026
bb8ed97
Raise explicit TypeError for numpy.timedelta64 inputs in Axes.hist
jayaprajapatii Mar 2, 2026
df468b2
remove duplicate pytest import
jayaprajapatii Mar 2, 2026
5fa7cc0
raise TypeError for timedelta64 in Axes.hist and remove bin logic cha…
jayaprajapatii Mar 3, 2026
4d257c6
Handle numpy.timedelta64 and datetime.timedelta explicitly
jayaprajapatii Mar 3, 2026
6c45d7c
fix object check and formatting
jayaprajapatii Mar 5, 2026
62d0716
merge timedelta checks and added datetime.timedelta regression tests
jayaprajapatii Mar 6, 2026
ea2b96d
merge timedelta checks and added datetime.timedelta regression test
jayaprajapatii Mar 6, 2026
432f787
fix python style
jayaprajapatii Mar 6, 2026
c07a991
Fix indentation
timhoffm Mar 6, 2026
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29 changes: 18 additions & 11 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7416,7 +7416,16 @@

# Massage 'x' for processing.
x = cbook._reshape_2D(x, 'x')
nx = len(x) # number of datasets
nx = len(x)
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Check warning on line 7420 in lib/matplotlib/axes/_axes.py

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GitHub Actions / ruff 

[rdjson] reported by reviewdog 🐶
Blank line contains whitespace

Raw Output:
message:"Blank line contains whitespace"  location:{path:"/home/runner/work/matplotlib/matplotlib/lib/matplotlib/axes/_axes.py"  range:{start:{line:7420  column:1}  end:{line:7420  column:9}}}  severity:WARNING  source:{name:"ruff"  url:"https://docs.astral.sh/ruff"}  code:{value:"W293"  url:"https://docs.astral.sh/ruff/rules/blank-line-with-whitespace"}  suggestions:{range:{start:{line:7420  column:1}  end:{line:7420  column:9}}}
new_x = []
for xi in x:
arr = np.asarray(xi)
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@timhoffm timhoffm Feb 27, 2026

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This is unnecessary. cbook._reshape_2D() already returns a list of arrays.

So at least

x = [arr / np.timedelta64(1, 'D') if np.issubdtype(arr.dtype, np.timedelta64) else arr
     for arr in x]

is possible.

Another question to be investigated: Is arr / np.timedelta64(1, 'D') equivalent to arr.astype(float) for timedelta arrays? If so, would a general x = [arr.astype(float) for arr in x] be reasonable?

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@oscargus oscargus Feb 27, 2026

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Is arr / np.timedelta64(1, 'D') equivalent to arr.astype(float) for timedelta arrays?

No, which is the whole problem here. If it was possible to cast timedelta64 to float, the comparison would work.

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@rcomer rcomer Feb 27, 2026

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astype(float) is valid, and I think is the better solution. Dividing by one day is going to give you tiny numbers if you started with seconds, and is going to error if you started with months or years.

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@kdpenner kdpenner Feb 27, 2026

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astype(float) is unsafe so if you choose to cast in this function you should be explicit in the documentation

if np.issubdtype(arr.dtype, np.timedelta64):
arr = arr / np.timedelta64(1, 'D')
new_x.append(arr)

x = new_x

# Process unit information. _process_unit_info sets the unit and
# converts the first dataset; then we convert each following dataset
Expand Down Expand Up @@ -7470,16 +7479,14 @@
# does not do this for us when guessing the range (but will
# happily ignore nans when computing the histogram).
if bin_range is None:
xmin = np.inf
xmax = -np.inf
for xi in x:
if len(xi):
# python's min/max ignore nan,
# np.minnan returns nan for all nan input
xmin = min(xmin, np.nanmin(xi))
xmax = max(xmax, np.nanmax(xi))
if xmin <= xmax: # Only happens if we have seen a finite value.
bin_range = (xmin, xmax)
flat = [np.ravel(xi) for xi in x if len(xi)]
if flat:
all_data = np.concatenate(flat)
xmin = np.nanmin(all_data)
xmax = np.nanmax(all_data)
bin_range = (xmin, xmax)
else:
bin_range = None
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# If bins are not specified either explicitly or via range,
# we need to figure out the range required for all datasets,
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9 changes: 9 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -2461,6 +2461,15 @@ def test_hist_log_barstacked():
assert axs[0].get_ylim() == axs[1].get_ylim()


def test_hist_timedelta_no_crash():
import numpy as np
import matplotlib.pyplot as plt

arr = np.array([1,2,5,7], dtype="timedelta64[D]")
fig, ax = plt.subplots()
ax.hist(arr)

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@image_comparison(['hist_bar_empty.png'], remove_text=True)
def test_hist_bar_empty():
# From #3886: creating hist from empty dataset raises ValueError
Expand Down
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