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TST: Ensure makeCategoricalIndex categories are unique (#46429)
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3 files changed

+4
-4
lines changed

3 files changed

+4
-4
lines changed

asv_bench/benchmarks/categoricals.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -187,7 +187,7 @@ def time_remove_categories(self):
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class Rank:
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def setup(self):
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N = 10**5
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ncats = 100
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ncats = 20
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self.s_str = pd.Series(tm.makeCategoricalIndex(N, ncats)).astype(str)
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self.s_str_cat = pd.Series(self.s_str, dtype="category")

pandas/_testing/__init__.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -305,7 +305,7 @@ def makeUnicodeIndex(k=10, name=None):
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def makeCategoricalIndex(k=10, n=3, name=None, **kwargs):
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"""make a length k index or n categories"""
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x = rands_array(nchars=4, size=n)
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x = rands_array(nchars=4, size=n, replace=False)
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return CategoricalIndex(
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Categorical.from_codes(np.arange(k) % n, categories=x), name=name, **kwargs
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)

pandas/_testing/_random.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -14,12 +14,12 @@ def randbool(size=(), p: float = 0.5):
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)
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def rands_array(nchars, size, dtype="O"):
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def rands_array(nchars, size, dtype="O", replace=True):
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"""
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Generate an array of byte strings.
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"""
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retval = (
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np.random.choice(RANDS_CHARS, size=nchars * np.prod(size))
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np.random.choice(RANDS_CHARS, size=nchars * np.prod(size), replace=replace)
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.view((np.str_, nchars))
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.reshape(size)
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)

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