8000 REF: avoid special case in DTA/TDA.median, flesh out tests by jbrockmendel · Pull Request #37423 · pandas-dev/pandas · GitHub
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REF: avoid special case in DTA/TDA.median, flesh out tests #37423

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Merged
merged 7 commits into from
Oct 31, 2020
Merged

REF: avoid special case in DTA/TDA.median, flesh out tests #37423

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65fe4e4
REF: avoid special case in DTA/TDA.median, flesh out tests
jbrockmendel Oct 26, 2020
178f3e3
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel Oct 26, 2020
c52b0bc
suppress warning
jbrockmendel Oct 26, 2020
52497db
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel Oct 29, 2020
956bd95
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel Oct 30, 2020
533e72c
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel Oct 30, 2020
ea9384a
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel Oct 31, 2020
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suppress warning
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@jbrockmendel
jbrockmendel committed Oct 26, 2020
commit c52b0bce6f4f38aa1e1eccd1d6142ee1cb8f526b
13 changes: 11 additions & 2 deletions pandas/core/nanops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import itertools
import operator
from typing import Any, Optional, Tuple, Union, cast
import warnings

import numpy as np

Expand Down Expand Up @@ -643,7 +644,11 @@ def get_median(x):
mask = notna(x)
if not skipna and not mask.all():
return np.nan
return np.nanmedian(x[mask])
with warnings.catch_warnings():
# Suppress RuntimeWarning about All-NaN slice
warnings.filterwarnings("ignore", "All-NaN slice encountered")
res = np.nanmedian(x[mask])
return res

values, mask, dtype, _, _ = _get_values(values, skipna, mask=mask)
if not is_float_dtype(values.dtype):
Expand Down Expand Up @@ -671,7 +676,11 @@ def get_median(x):
)

# fastpath for the skipna case
return _wrap_results(np.nanmedian(values, axis), dtype)
with warnings.catch_warnings():
# Suppress RuntimeWarning about All-NaN slice
warnings.filterwarnings("ignore", "All-NaN slice encountered")
res = np.nanmedian(values, axis)
return _wrap_results(res, dtype)

# must return the correct shape, but median is not defined for the
# empty set so return nans of shape "everything but the passed axis"
Expand Down
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