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Merged
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Aug 1, 2021
Merged

Sync Fork from Upstream Repo #248

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c79e7ee
TST: fix read_stata doctest #42670 (#42701)
KrishnaSai2020 Jul 31, 2021
a5f8c9a
TST: Catch warnings due to division by 0 (#42836)
rhshadrach Jul 31, 2021
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1 change: 1 addition & 0 deletions ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -123,6 +123,7 @@ if [[ -z "$CHECK" || "$CHECK" == "doctests" ]]; then
pandas/io/sql.py \
pandas/io/formats/format.py \
pandas/io/formats/style.py \
pandas/io/stata.py \
pandas/tseries/
RET=$(($RET + $?)) ; echo $MSG "DONE"

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19 changes: 17 additions & 2 deletions pandas/io/stata.py
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Expand Up @@ -160,15 +160,30 @@

Examples
--------

Creating a dummy stata for this example
>>> df = pd.DataFrame({{'animal': ['falcon', 'parrot', 'falcon',
... 'parrot'],
... 'speed': [350, 18, 361, 15]}})
>>> df.to_stata('animals.dta')

Read a Stata dta file:

>>> df = pd.read_stata('filename.dta')
>>> df = pd.read_stata('animals.dta')

Read a Stata dta file in 10,000 line chunks:
>>> values = np.random.randint(0, 10, size=(20_000, 1), dtype="uint8")
>>> df = pd.DataFrame(values, columns=["i"])
>>> df.to_stata('filename.dta')

>>> itr = pd.read_stata('filename.dta', chunksize=10000)
>>> for chunk in itr:
... do_something(chunk)
... # Operate on a single chunk, e.g., chunk.mean()
... pass

>>> import os
>>> os.remove("./filename.dta")
>>> os.remove("./animals.dta")
"""

_read_method_doc = f"""\
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9 changes: 7 additions & 2 deletions pandas/tests/test_expressions.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import operator
import re
import warnings

import numpy as np
import pytest
Expand Down Expand Up @@ -167,8 +168,12 @@ def testit():

op = getattr(operator, opname)

result = expr.evaluate(op, left, left, use_numexpr=True)
expected = expr.evaluate(op, left, left, use_numexpr=False)
with warnings.catch_warnings():
# array has 0s
msg = "invalid value encountered in true_divide"
warnings.filterwarnings("ignore", msg, RuntimeWarning)
result = expr.evaluate(op, left, left, use_numexpr=True)
expected = expr.evaluate(op, left, left, use_numexpr=False)
tm.assert_numpy_array_equal(result, expected)

result = expr._can_use_numexpr(op, op_str, right, right, "evaluate")
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