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Pin blosc to 1.14.3 for travis-27 build #22429

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Merged
merged 5 commits into from
Aug 20, 2018
Merged

Pin blosc to 1.14.3 for travis-27 build #22429

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855b1b7
Revert "CI: add missing tzlocal dependency (rpy2, doc build) (#22424)"
TomAugspurger Aug 20, 2018
71b4878
Fix conflict with 83be235ab8470dc3a4e2fa55c79d54db3abc7e58
TomAugspurger Aug 20, 2018
c33c1bc
Revert "Revert "CI: add missing tzlocal dependency (rpy2, doc build) …
TomAugspurger Aug 20, 2018
f83a8ae
Pin blosc
TomAugspurger Aug 20, 2018
099e1e8
use integer_array
TomAugspurger Aug 20, 2018
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1 change: 1 addition & 0 deletions ci/travis-27.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ dependencies:
- PyCrypto
- pymysql=0.6.3
- pytables
- blosc=1.14.3
- python-blosc
- python-dateutil=2.5.0
- python=2.7*
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4 changes: 2 additions & 2 deletions pandas/tests/extension/integer/test_integer.py
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Expand Up @@ -770,7 +770,7 @@ def test_groupby_mean_included():
df = pd.DataFrame({
"A": ['a', 'b', 'b'],
"B": [1, None, 3],
"C": IntegerArray([1, None, 3], dtype='Int64'),
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I would do this in a separate PR

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Keeping it here, now that we know that the doc PR isn't related.

"C": integer_array([1, None, 3], dtype='Int64'),
})

result = df.groupby("A").sum()
Expand All @@ -784,7 +784,7 @@ def test_groupby_mean_included():

def test_astype_nansafe():
# https://github.com/pandas-dev/pandas/pull/22343
arr = IntegerArray([np.nan, 1, 2], dtype="Int8")
arr = integer_array([np.nan, 1, 2], dtype="Int8")

with tm.assert_raises_regex(
ValueError, 'cannot convert float NaN to integer'):
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6 changes: 3 additions & 3 deletions pandas/tests/frame/test_block_internals.py
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Expand Up @@ -12,7 +12,7 @@

from pandas import (DataFrame, Series, Timestamp, date_range, compat,
option_context, Categorical)
from pandas.core.arrays import IntegerArray, IntervalArray
from pandas.core.arrays import IntervalArray, integer_array
from pandas.compat import StringIO
import pandas as pd

Expand Down Expand Up @@ -440,9 +440,9 @@ def test_get_numeric_data(self):
def test_get_numeric_data_extension_dtype(self):
# GH 22290
df = DataFrame({
'A': IntegerArray([-10, np.nan, 0, 10, 20, 30], dtype='Int64'),
'A': integer_array([-10, np.nan, 0, 10, 20, 30], dtype='Int64'),
'B': Categorical(list('abcabc')),
'C': IntegerArray([0, 1, 2, 3, np.nan, 5], dtype='UInt8'),
'C': integer_array([0, 1, 2, 3, np.nan, 5], dtype='UInt8'),
'D': IntervalArray.from_breaks(range(7))})
result = df._get_numeric_data()
expected = df.loc[:, ['A', 'C']]
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