8000 CLN: use float64_t consistently instead of double, double_t by jbrockmendel · Pull Request #23583 · pandas-dev/pandas · GitHub
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CLN: use float64_t consistently instead of double, double_t #23583

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Merged
merged 19 commits into from
Nov 11, 2018
Merged

CLN: use float64_t consistently instead of double, double_t #23583

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fa38001
use float64_t instead of double
jbrockmendel Nov 7, 2018
af27870
make memoryview arguments const where needed; use C NAT lookups inste…
jbrockmendel Nov 7, 2018
83ca237
Merge branch 'master' of https://github.com/pandas-dev/pandas into cln1
jbrockmendel Nov 7, 2018
367969e
remove boundschecks
jbrockmendel Nov 8, 2018
16d75a3
Merge branch 'master' of https://github.com/pandas-dev/pandas into cln1
jbrockmendel Nov 8, 2018
4f4d1cf
de-duplicate using checknull_with_nat
jbrockmendel Nov 8, 2018
d1511f7
remove non-standard imports of np.nan
jbrockmendel Nov 8, 2018
c9ef170
revert not-worth it NAT, remove extraneous nan
jbrockmendel Nov 8, 2018
1445830
Merge branch 'master' of https://github.com/pandas-dev/pandas into cln1
jbrockmendel Nov 8, 2018
d46d516
standardize iNaT-->NPY_NAT
jbrockmendel Nov 8, 2018
f2f4b8d
comment cleanup
jbrockmendel Nov 8, 2018
e7adaf2
Merge branch 'master' of https://github.com/pandas-dev/pandas into cln1
jbrockmendel Nov 8, 2018
03ae9cf
remove unncessary cpdef
jbrockmendel Nov 8, 2018
9f51831
Merge branch 'master' of http 8000 s://github.com/pandas-dev/pandas into cln1
jbrockmendel Nov 8, 2018
33fc12d
delete unused or commented-out
jbrockmendel Nov 8, 2018
8bc71b8
remove unused
jbrockmendel Nov 8, 2018
5e50897
whitespace fixup
jbrockmendel Nov 8, 2018
52ede45
Merge branch 'master' of https://github.com/pandas-dev/pandas into cln1
jbrockmendel Nov 10, 2018
23344b2
remove unliked comment
jbrockmendel Nov 10, 2018
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remove non-standard imports of np.nan
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@jbrockmendel
jbrockmendel committed Nov 8, 2018
commit d1511f7001d7251bb1820a4b35ed8260dbcdb33a
4 changes: 2 additions & 2 deletions pandas/tests/arrays/sparse/test_array.py
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Expand Up @@ -3,7 +3,6 @@
import warnings

import numpy as np
from numpy import nan
import pytest

from pandas._libs.sparse import IntIndex
Expand All @@ -24,7 +23,8 @@ def kind(request):
class TestSparseArray(object):

def setup_method(self, method):
self.arr_data = np.array([nan, nan, 1, 2, 3, nan, 4, 5, nan, 6])
self.arr_data = np.array([np.nan, np.nan, 1, 2, 3,
np.nan, 4, 5, np.nan, 6])
self.arr = SparseArray(self.arr_data)
self.zarr = SparseArray([0, 0, 1, 2, 3, 0, 4, 5, 0, 6], fill_value=0)

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3 changes: 1 addition & 2 deletions pandas/tests/frame/test_operators.py
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Expand Up @@ -6,7 +6,6 @@

import pytest

from numpy import nan
import numpy as np

from pandas.compat import range
Expand Down Expand Up @@ -328,7 +327,7 @@ def test_combineFrame(self):
frame_copy = self.frame.reindex(self.frame.index[::2])

del frame_copy['D']
frame_copy['C'][:5] = nan
frame_copy['C'][:5] = np.nan

added = self.frame + frame_copy

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5 changes: 2 additions & 3 deletions pandas/tests/frame/test_repr_info.py
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Expand Up @@ -7,7 +7,6 @@
import sys
import textwrap

from numpy import nan
import numpy as np
import pytest

Expand Down Expand Up @@ -49,8 +48,8 @@ def test_repr_mixed_big(self):
biggie = DataFrame({'A': np.random.randn(200),
'B': tm.makeStringIndex(200)},
index=lrange(200))
biggie.loc[:20, 'A'] = nan
biggie.loc[:20, 'B'] = nan
biggie.loc[:20, 'A'] = np.nan
biggie.loc[:20, 'B'] = np.nan

foo = repr(biggie) # noqa

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7 changes: 3 additions & 4 deletions pandas/tests/frame/test_timeseries.py
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Expand Up @@ -6,7 +6,6 @@

import pytest

from numpy import nan
from numpy.random import randn
import numpy as np

Expand Down Expand Up @@ -517,8 +516,8 @@ def test_first_last_valid(self, data, idx,
expected_first, expected_last):
N = len(self.frame.index)
mat = randn(N)
mat[:5] = nan
mat[-5:] = nan
mat[:5] = np.nan
mat[-5:] = np.nan

frame = DataFrame({'foo': mat}, index=self.frame.index)
index = frame.first_valid_index()
Expand All @@ -534,7 +533,7 @@ def test_first_last_valid(self, data, idx,
assert empty.first_valid_index() is None

# GH17400: no valid entries
frame[:] = nan
frame[:] = np.nan
assert frame.last_valid_index() is None
assert frame.first_valid_index() is None

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3 changes: 1 addition & 2 deletions pandas/tests/frame/test_to_csv.py
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Expand Up @@ -6,7 +6,6 @@
import csv
import pytest

from numpy import nan
import numpy as np

from pandas.compat import (lmap, range, lrange, StringIO, u)
Expand Down Expand Up @@ -52,7 +51,7 @@ def test_from_csv_deprecation(self):
def test_to_csv_from_csv1(self):

with ensure_clean('__tmp_to_csv_from_csv1__') as path:
self.frame['A'][:5] = nan
self.frame['A'][:5] = np.nan

self.frame.to_csv(path)
self.frame.to_csv(path, columns=['A', 'B'])
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5 changes: 2 additions & 3 deletions pandas/tests/groupby/aggregate/test_cython.py
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Expand Up @@ -9,7 +9,6 @@
import pytest

import numpy as np
from numpy import nan
import pandas as pd

from pandas import (bdate_range, DataFrame, Index, Series, Timestamp,
Expand All @@ -36,11 +35,11 @@
'max',
])
def test_cythonized_aggers(op_name):
data = {'A': [0, 0, 0, 0, 1, 1, 1, 1, 1, 1., nan, nan],
data = {'A': [0, 0, 0, 0, 1, 1, 1, 1, 1, 1., np.nan, np.nan],
'B': ['A', 'B'] * 6,
'C': np.random.randn(12)}
df = DataFrame(data)
df.loc[2:10:2, 'C'] = nan
df.loc[2:10:2, 'C'] = np.nan

op = lambda x: getattr(x, op_name)()

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9 changes: 4 additions & 5 deletions pandas/tests/series/test_operators.py
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Expand Up @@ -5,7 +5,6 @@
import operator

import numpy as np
from numpy import nan
import pytest

import pandas.compat as compat
Expand Down Expand Up @@ -750,12 +749,12 @@ def _check_fill(meth, op, a, b, fill_value=0):
with np.errstate(all='ignore'):
if amask[i]:
if bmask[i]:
exp_values.append(nan)
exp_values.append(np.nan)
continue
exp_values.append(op(fill_value, b[i]))
elif bmask[i]:
if amask[i]:
exp_values.append(nan)
exp_values.append(np.nan)
continue
exp_values.append(op(a[i], fill_value))
else:
Expand All @@ -765,8 +764,8 @@ def _check_fill(meth, op, a, b, fill_value=0):
expected = Series(exp_values, exp_index)
assert_series_equal(result, expected)

a = Series([nan, 1., 2., 3., nan], index=np.arange(5))
b = Series([nan, 1, nan, 3, nan, 4.], index=np.arange(6))
a = Series([np.nan, 1., 2., 3., np.nan], index=np.arange(5))
b = Series([np.nan, 1, np.nan, 3, np.nan, 4.], index=np.arange(6))

result = op(a, b)
exp = equiv_op(a, b)
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