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Merged
merged 4 commits into from
Jul 18, 2019
Merged

TYPING: pandas/core/window.py #27391

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246e90e
TYPING: pandas/core/window.py
Jul 15, 2019
85e7f2e
Address comments
Jul 16, 2019
10bd26c
Remove unused import
Jul 16, 2019
0f1faea
Sort imports
Jul 16, 2019
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121 changes: 65 additions & 56 deletions pandas/core/window.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@
from collections import defaultdict
from datetime import timedelta
from textwrap import dedent
from typing import Set
from typing import List, Optional, Set, Union
import warnings

import numpy as np
Expand Down Expand Up @@ -63,19 +63,19 @@ class _Window(PandasObject, SelectionMixin):
"axis",
"on",
"closed",
]
] # type: List[str]
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Was this actually throwing an error? Not opposed to it just surprised Mypy wouldn't infer this already

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Don't think so; just thought to go ahead and type.

exclusions = set() # type: Set[str]

def __init__(
self,
obj,
window=None,
min_periods=None,
center=False,
win_type=None,
axis=0,
on=None,
closed=None,
min_periods: Optional[int] = None,
center: Optional[bool] = False,
win_type: Optional[str] = None,
axis: Union[str, int] = 0,
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Can you put this in pandas._typing as Axis and reference here?

cc @topper-123 as this might conflict with your other PR

on: Optional[str] = None,
closed: Optional[str] = None,
**kwargs
):

Expand All @@ -97,15 +97,15 @@ def _constructor(self):
return Window

@property
def is_datetimelike(self):
def is_datetimelike(self) -> Optional[bool]:
return None

@property
def _on(self):
return None

@property
def is_freq_type(self):
def is_freq_type(self) -> bool:
return self.win_type == "freq"

def validate(self):
Expand All @@ -121,30 +121,20 @@ def validate(self):
]:
raise ValueError("closed must be 'right', 'left', 'both' or " "'neither'")

def _convert_freq(self):
"""
Resample according to the how, return a new object.
"""
obj = self._selected_obj
index = None
return obj, index

def _create_blocks(self):
"""
Split data into blocks & return conformed data.
"""

obj, index = self._convert_freq()
if index is not None:
index = self._on
obj = self._selected_obj

# filter out the on from the object
if self.on is not None:
if obj.ndim == 2:
obj = obj.reindex(columns=obj.columns.difference([self.on]), copy=False)
blocks = obj._to_dict_of_blocks(copy=False).values()

return blocks, obj, index
return blocks, obj

def _gotitem(self, key, ndim, subset=None):
"""
Expand Down Expand Up @@ -186,10 +176,10 @@ def _get_window(self, other=None):
return self.window

@property
def _window_type(self):
def _window_type(self) -> str:
return self.__class__.__name__

def __repr__(self):
def __repr__(self) -> str:
"""
Provide a nice str repr of our rolling object.
"""
Expand All @@ -207,23 +197,21 @@ def __iter__(self):
url = "https://github.com/pandas-dev/pandas/issues/11704"
raise NotImplementedError("See issue #11704 {url}".format(url=url))

def _get_index(self, index=None):
def _get_index(self) -> Optional[np.ndarray]:
"""
Return index as ndarrays.
Return index as an ndarray.

Returns
-------
tuple of (index, index_as_ndarray)
None or ndarray
"""

if self.is_freq_type:
if index is None:
index = self._on
return index, index.asi8
return index, index

def _prep_values(self, values=None, kill_inf=True):
return self._on.asi8
return None

def _prep_values(self, values: Optional[np.ndarray] = None) -> np.ndarray:
"""Convert input to numpy arrays for Cython routines"""
if values is None:
values = getattr(self._selected_obj, "values", self._selected_obj)

Expand All @@ -247,13 +235,14 @@ def _prep_values(self, values=None, kill_inf=True):
"cannot handle this type -> {0}" "".format(values.dtype)
)

if kill_inf:
values = values.copy()
values[np.isinf(values)] = np.NaN
# Always convert inf to nan
values[np.isinf(values)] = np.NaN
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You missed a copy call here. Results in kernc/backtesting.py#14 on write-protected arrays.


return values

def _wrap_result(self, result, block=None, obj=None):
def _wrap_result(
self, result, block=None, obj=None
) -> Union[ABCSeries, ABCDataFrame]:
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Should use FrameOrSeries from pandas._typing

"""
Wrap a single result.
"""
Expand Down Expand Up @@ -281,7 +270,9 @@ def _wrap_result(self, result, block=None, obj=None):
return type(obj)(result, index=index, columns=block.columns)
return result

def _wrap_results(self, results, blocks, obj, exclude=None):
def _wrap_results(
self, results, blocks, obj, exclude=None
) -> Union[ABCSeries, ABCDataFrame]:
"""
Wrap the results.

Expand Down Expand Up @@ -335,7 +326,7 @@ def _wrap_results(self, results, blocks, obj, exclude=None):
return obj.astype("float64")
return concat(final, axis=1).reindex(columns=columns, copy=False)

def _center_window(self, result, window):
def _center_window(self, result, window) -> np.ndarray:
"""
Center the result in the window.
"""
Expand Down Expand Up @@ -724,7 +715,7 @@ def _apply_window(self, mean=True, **kwargs):
window = self._prep_window(**kwargs)
center = self.center

blocks, obj, index = self._create_blocks()
blocks, obj = self._create_blocks()
block_list = list(blocks)

results = []
Expand Down Expand Up @@ -912,9 +903,9 @@ def _apply(
if check_minp is None:
check_minp = _use_window

blocks, obj, index = self._create_blocks()
blocks, obj = self._create_blocks()
block_list = list(blocks)
index, indexi = self._get_index(index=index)
index_as_array = self._get_index()

results = []
exclude = []
Expand Down Expand Up @@ -947,7 +938,7 @@ def func(arg, window, min_periods=None, closed=None):
minp = check_minp(min_periods, window)
# ensure we are only rolling on floats
arg = ensure_float64(arg)
return cfunc(arg, window, minp, indexi, closed, **kwargs)
return cfunc(arg, window, minp, index_as_array, closed, **kwargs)

# calculation function
if center:
Expand Down Expand Up @@ -1027,9 +1018,9 @@ class _Rolling_and_Expanding(_Rolling):

def count(self):

blocks, obj, index = self._create_blocks()
blocks, obj = self._create_blocks()
# Validate the index
self._get_index(index=index)
self._get_index()

window = self._get_window()
window = min(window, len(obj)) if not self.center else window
Expand Down Expand Up @@ -1088,11 +1079,10 @@ def count(self):
def apply(self, func, raw=None, args=(), kwargs={}):
from pandas import Series

# TODO: _level is unused?
_level = kwargs.pop("_level", None) # noqa
kwargs.pop("_level", None)
window = self._get_window()
offset = _offset(window, self.center)
index, indexi = self._get_index()
index_as_array = self._get_index()

# TODO: default is for backward compat
# change to False in the future
Expand All @@ -1113,7 +1103,16 @@ def f(arg, window, min_periods, closed):
if not raw:
arg = Series(arg, index=self.obj.index)
return libwindow.roll_generic(
arg, window, minp, indexi, closed, offset, func, raw, args, kwargs
arg,
window,
minp,
index_as_array,
closed,
offset,
func,
raw,
args,
kwargs,
)

return self._apply(f, func, args=args, kwargs=kwargs, center=False, raw=raw)
Expand Down Expand Up @@ -1285,12 +1284,12 @@ def median(self, **kwargs):
def std(self, ddof=1, *args, **kwargs):
nv.validate_window_func("std", args, kwargs)
window = self._get_window()
index, indexi = self._get_index()
index_as_array = self._get_index()

def f(arg, *args, **kwargs):
minp = _require_min_periods(1)(self.min_periods, window)
return _zsqrt(
libwindow.roll_var(arg, window, minp, indexi, self.closed, ddof)
libwindow.roll_var(arg, window, minp, index_as_array, self.closed, ddof)
)

return self._apply(
Expand Down Expand Up @@ -1474,17 +1473,27 @@ def kurt(self, **kwargs):

def quantile(self, quantile, interpolation="linear", **kwargs):
window = self._get_window()
index, indexi = self._get_index()
index_as_array = self._get_index()

def f(arg, *args, **kwargs):
minp = _use_window(self.min_periods, window)
if quantile == 1.0:
return libwindow.roll_max(arg, window, minp, indexi, self.closed)
return libwindow.roll_max(
arg, window, minp, index_as_array, self.closed
)
elif quantile == 0.0:
return libwindow.roll_min(arg, window, minp, indexi, self.closed)
return libwindow.roll_min(
arg, window, minp, index_as_array, self.closed
)
else:
return libwindow.roll_quantile(
arg, window, minp, indexi, self.closed, quantile, interpolation
arg,
window,
minp,
index_as_array,
self.closed,
quantile,
interpolation,
)

return self._apply(f, "quantile", quantile=quantile, **kwargs)
Expand Down Expand Up @@ -2450,7 +2459,7 @@ def _apply(self, func, **kwargs):
-------
y : same type as input argument
"""
blocks, obj, index = self._create_blocks()
blocks, obj = self._create_blocks()
block_list = list(blocks)

results = []
Expand Down