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} | 5 | "2021-10-21T00:53:22Z" | "2021-10-28T03:34:56Z" | "2021-10-28T03:34:56Z" | CONTRIBUTOR | null | eg.. https://github.com/pandas-dev/pandas/pull/44125/checks?check_run_id=3958010839
traceback is large
maybe something started on numpy side
cc @seberg
cc @pandas-dev/pandas-core
```
pandas/tests/frame/test_reductions.py:570:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = foo bar baz
0 100 -0.699818 -0.060793
1 -0.008426 -0.982277 -0.177994
2 1.633849 0.952529 -0.082802
3 -0.22671 0.524945 2.436406
4 -0.484995 0.845172 -2.276719
axis = 1, skipna = True, level = None, ddof = 1, numeric_only = False
kwargs = {}
@doc(
_num_ddof_doc,
desc="Return sample standard deviation over requested axis."
"\n\nNormalized by N-1 by default. This can be changed using the "
"ddof argument",
name1=name1,
name2=name2,
axis_descr=axis_descr,
notes=_std_notes,
)
def std(
self,
axis=None,
skipna=True,
level=None,
ddof=1,
numeric_only=None,
**kwargs,
):
> return NDFrame.std(self, axis, skipna, level, ddof, numeric_only, **kwargs)
pandas/core/generic.py:10703:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = foo bar baz
0 100 -0.699818 -0.060793
1 -0.008426 -0.982277 -0.177994
2 1.633849 0.952529 -0.082802
3 -0.22671 0.524945 2.436406
4 -0.484995 0.845172 -2.276719
axis = 1, skipna = True, level = None, ddof = 1, numeric_only = False
kwargs = {}
def std(
self, axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs
):
> return self._stat_function_ddof(
"std", nanops.nanstd, axis, skipna, level, ddof, numeric_only, **kwargs
)
pandas/core/generic.py:10396:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = foo bar baz
0 100 -0.699818 -0.060793
1 -0.008426 -0.982277 -0.177994
2 1.633849 0.952529 -0.082802
3 -0.22671 0.524945 2.436406
4 -0.484995 0.845172 -2.276719
name = 'std', func = <function nanstd at 0x10e9e5750>, axis = 1, skipna = True
level = None, ddof = 1, numeric_only = False, kwargs = {}
@final
def _stat_function_ddof(
self,
name: str,
func,
axis=None,
skipna=True,
level=None,
ddof=1,
numeric_only=None,
**kwargs,
):
nv.validate_stat_ddof_func((), kwargs, fname=name)
if axis is None:
axis = self._stat_axis_number
if level is not None:
warnings.warn(
"Using the level keyword in DataFrame and Series aggregations is "
"deprecated and will be removed in a future version. Use groupby "
"instead. df.var(level=1) should use df.groupby(level=1).var().",
FutureWarning,
stacklevel=4,
)
return self._agg_by_level(
name, axis=axis, level=level, skipna=skipna, ddof=ddof
)
> return self._reduce(
func, name, axis=axis, numeric_only=numeric_only, skipna=skipna, ddof=ddof
)
pandas/core/generic.py:10375:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = foo bar baz
0 100 -0.699818 -0.060793
1 -0.008426 -0.982277 -0.177994
2 1.633849 0.952529 -0.082802
3 -0.22671 0.524945 2.436406
4 -0.484995 0.845172 -2.276719
op = <function nanstd at 0x10e9e5750>, name = 'std', axis = 0, skipna = True
numeric_only = False, filter_type = None, kwds = {'ddof': 1}, out_dtype = None
def _reduce(
self,
op,
name: str,
*,
axis: Axis = 0,
skipna: bool = True,
numeric_only: bool | None = None,
filter_type=None,
**kwds,
):
assert filter_type is None or filter_type == "bool", filter_type
out_dtype = "bool" if filter_type == "bool" else None
if numeric_only is None and name in ["mean", "median"]:
own_dtypes = [arr.dtype for arr in self._mgr.arrays]
dtype_is_dt = np.array(
[is_datetime64_any_dtype(dtype) for dtype in own_dtypes],
dtype=bool,
)
if dtype_is_dt.any():
warnings.warn(
"DataFrame.mean and DataFrame.median with numeric_only=None "
"will include datetime64 and datetime64tz columns in a "
"future version.",
FutureWarning,
stacklevel=5,
)
# Non-copy equivalent to
# dt64_cols = self.dtypes.apply(is_datetime64_any_dtype)
# cols = self.columns[~dt64_cols]
# self = self[cols]
predicate = lambda x: not is_datetime64_any_dtype(x.dtype)
mgr = self._mgr._get_data_subset(predicate)
self = type(self)(mgr)
# TODO: Make other agg func handle axis=None properly GH#21597
axis = self._get_axis_number(axis)
labels = self._get_agg_axis(axis)
assert axis in [0, 1]
def func(values: np.ndarray):
# We only use this in the case that operates on self.values
return op(values, axis=axis, skipna=skipna, **kwds)
def blk_func(values, axis=1):
if isinstance(values, ExtensionArray):
if not is_1d_only_ea_obj(values) and not isinstance(
self._mgr, ArrayManager
):
return values._reduce(name, axis=1, skipna=skipna, **kwds)
return values._reduce(name, skipna=skipna, **kwds)
else:
return op(values, axis=axis, skipna=skipna, **kwds)
def _get_data() -> DataFrame:
if filter_type is None:
data = self._get_numeric_data()
else:
# GH#25101, GH#24434
assert filter_type == "bool"
data = self._get_bool_data()
return data
if numeric_only is not None or axis == 0:
# For numeric_only non-None and axis non-None, we know
# which blocks to use and no try/except is needed.
# For numeric_only=None only the case with axis==0 and no object
# dtypes are unambiguous can be handled with BlockManager.reduce
# Case with EAs see GH#35881
df = self
if numeric_only is True:
df = _get_data()
if axis == 1:
df = df.T
axis = 0
ignore_failures = numeric_only is None
# After possibly _get_data and transposing, we are now in the
# simple case where we can use BlockManager.reduce
> res, _ = df._mgr.reduce(blk_func, ignore_failures=ignore_failures)
pandas/core/frame.py:9998:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = BlockManager
Items: RangeIndex(start=0, stop=5, step=1)
Axis 1: Index(['foo', 'bar', 'baz'], dtype='object')
ObjectBlock: slice(0, 5, 1), 5 x 3, dtype: object
func = <function DataFrame._reduce.<locals>.blk_func at 0x1474ce8c0>
ignore_failures = False
def reduce(
self: T, func: Callable, ignore_failures: bool = False
) -> tuple[T, np.ndarray]:
"""
Apply reduction function blockwise, returning a single-row BlockManager.
Parameters
----------
func : reduction function
ignore_failures : bool, default False
Whether to drop blocks where func raises TypeError.
Returns
-------
BlockManager
np.ndarray
Indexer of mgr_locs that are retained.
"""
# If 2D, we assume that we're operating column-wise
assert self.ndim == 2
res_blocks: list[Block] = []
for blk in self.blocks:
> nbs = blk.reduce(func, ignore_failures)
pandas/core/internals/managers.py:1309:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = ObjectBlock: slice(0, 5, 1), 5 x 3, dtype: object
args = (<function DataFrame._reduce.<locals>.blk_func at 0x1474ce8c0>, False)
kwargs = {}
@wraps(meth)
def newfunc(self, *args, **kwargs) -> list[Block]:
if self.ndim == 1 or self.shape[0] == 1:
return meth(self, *args, **kwargs)
else:
# Split and operate column-by-column
> return self.split_and_operate(meth, *args, **kwargs)
pandas/core/internals/blocks.py:137:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = ObjectBlock: slice(0, 5, 1), 5 x 3, dtype: object
func = <function ObjectBlock.reduce at 0x10f2e5510>
args = (<function DataFrame._reduce.<locals>.blk_func at 0x1474ce8c0>, False)
kwargs = {}, res_blocks = []
nb = ObjectBlock: slice(0, 1, 1), 1 x 3, dtype: object
@final
def split_and_operate(self, func, *args, **kwargs) -> list[Block]:
"""
Split the block and apply func column-by-column.
Parameters
----------
func : Block method
*args
**kwargs
Returns
-------
List[Block]
"""
assert self.ndim == 2 and self.shape[0] != 1
res_blocks = []
for nb in self._split():
> rbs = func(nb, *args, **kwargs)
pandas/core/internals/blocks.py:495:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = ObjectBlock: slice(0, 1, 1), 1 x 3, dtype: object
func = <function DataFrame._reduce.<locals>.blk_func at 0x1474ce8c0>
ignore_failures = False
@maybe_split
def reduce(self, func, ignore_failures: bool = False) -> list[Block]:
"""
For object-dtype, we operate column-wise.
"""
assert self.ndim == 2
try:
> res = func(self.values)
pandas/core/internals/blocks.py:1827:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
values = array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object)
axis = 1
def blk_func(values, axis=1):
if isinstance(values, ExtensionArray):
if not is_1d_only_ea_obj(values) and not isinstance(
self._mgr, ArrayManager
):
return values._reduce(name, axis=1, skipna=skipna, **kwds)
return values._reduce(name, skipna=skipna, **kwds)
else:
> return op(values, axis=axis, skipna=skipna, **kwds)
pandas/core/frame.py:9970:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
values = array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object)
axis = 1, skipna = True, kwds = {'ddof': 1}, k = 'ddof', v = 1
@functools.wraps(alt)
def f(
values: np.ndarray,
*,
axis: int | None = None,
skipna: bool = True,
**kwds,
):
if len(self.kwargs) > 0:
for k, v in self.kwargs.items():
if k not in kwds:
kwds[k] = v
if values.size == 0 and kwds.get("min_count") is None:
# We are empty, returning NA for our type
# Only applies for the default `min_count` of None
# since that affects how empty arrays are handled.
# TODO(GH-18976) update all the nanops methods to
# correctly handle empty inputs and remove this check.
# It *may* just be `var`
return _na_for_min_count(values, axis)
if _USE_BOTTLENECK and skipna and _bn_ok_dtype(values.dtype, bn_name):
if kwds.get("mask", None) is None:
# `mask` is not recognised by bottleneck, would raise
# TypeError if called
kwds.pop("mask", None)
result = bn_func(values, axis=axis, **kwds)
# prefer to treat inf/-inf as NA, but must compute the func
# twice :(
if _has_infs(result):
result = alt(values, axis=axis, skipna=skipna, **kwds)
else:
result = alt(values, axis=axis, skipna=skipna, **kwds)
else:
> result = alt(values, axis=axis, skipna=skipna, **kwds)
pandas/core/nanops.py:155:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
values = array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object)
@bottleneck_switch(ddof=1)
def nanstd(values, *, axis=None, skipna=True, ddof=1, mask=None):
"""
Compute the standard deviation along given axis while ignoring NaNs
Parameters
----------
values : ndarray
axis : int, optional
skipna : bool, default True
ddof : int, default 1
Delta Degrees of Freedom. The divisor used in calculations is N - ddof,
where N represents the number of elements.
mask : ndarray[bool], optional
nan-mask if known
Returns
-------
result : float
Unless input is a float array, in which case use the same
precision as the input array.
Examples
--------
>>> import pandas.core.nanops as nanops
>>> s = pd.Series([1, np.nan, 2, 3])
>>> nanops.nanstd(s)
1.0
"""
if values.dtype == "M8[ns]":
values = values.view("m8[ns]")
orig_dtype = values.dtype
values, mask, _, _, _ = _get_values(values, skipna, mask=mask)
> result = np.sqrt(nanvar(values, axis=axis, skipna=skipna, ddof=ddof, mask=mask))
pandas/core/nanops.py:897:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
args = (array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object),)
kwargs = {'axis': 1, 'ddof': 1, 'mask': array([[False, False, False]]), 'skipna': True}
obj_iter = <itertools.chain object at 0x146c93820>
@functools.wraps(f)
def _f(*args, **kwargs):
obj_iter = itertools.chain(args, kwargs.values())
if any(self.check(obj) for obj in obj_iter):
f_name = f.__name__.replace("nan", "")
raise TypeError(
f"reduction operation '{f_name}' not allowed for this dtype"
)
try:
with np.errstate(invalid="ignore"):
> return f(*args, **kwargs)
pandas/core/nanops.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
values = array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object)
axis = 1, skipna = True
kwds = {'ddof': 1, 'mask': array([[False, False, False]])}, k = 'ddof', v = 1
@functools.wraps(alt)
def f(
values: np.ndarray,
*,
axis: int | None = None,
skipna: bool = True,
**kwds,
):
if len(self.kwargs) > 0:
for k, v in self.kwargs.items():
if k not in kwds:
kwds[k] = v
if values.size == 0 and kwds.get("min_count") is None:
# We are empty, returning NA for our type
# Only applies for the default `min_count` of None
# since that affects how empty arrays are handled.
# TODO(GH-18976) update all the nanops methods to
# correctly handle empty inputs and remove this check.
# It *may* just be `var`
return _na_for_min_count(values, axis)
if _USE_BOTTLENECK and skipna and _bn_ok_dtype(values.dtype, bn_name):
if kwds.get("mask", None) is None:
# `mask` is not recognised by bottleneck, would raise
# TypeError if called
kwds.pop("mask", None)
result = bn_func(values, axis=axis, **kwds)
# prefer to treat inf/-inf as NA, but must compute the func
# twice :(
if _has_infs(result):
result = alt(values, axis=axis, skipna=skipna, **kwds)
else:
result = alt(values, axis=axis, skipna=skipna, **kwds)
else:
> result = alt(values, axis=axis, skipna=skipna, **kwds)
pandas/core/nanops.py:155:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
values = array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object)
@disallow("M8", "m8")
@bottleneck_switch(ddof=1)
def nanvar(values, *, axis=None, skipna=True, ddof=1, mask=None):
"""
Compute the variance along given axis while ignoring NaNs
Parameters
----------
values : ndarray
axis : int, optional
skipna : bool, default True
ddof : int, default 1
Delta Degrees of Freedom. The divisor used in calculations is N - ddof,
where N represents the number of elements.
mask : ndarray[bool], optional
nan-mask if known
Returns
-------
result : float
Unless input is a float array, in which case use the same
precision as the input array.
Examples
--------
>>> import pandas.core.nanops as nanops
>>> s = pd.Series([1, np.nan, 2, 3])
>>> nanops.nanvar(s)
1.0
"""
values = extract_array(values, extract_numpy=True)
dtype = values.dtype
mask = _maybe_get_mask(values, skipna, mask)
if is_any_int_dtype(dtype):
values = values.astype("f8")
if mask is not None:
values[mask] = np.nan
if is_float_dtype(values.dtype):
count, d = _get_counts_nanvar(values.shape, mask, axis, ddof, values.dtype)
else:
count, d = _get_counts_nanvar(values.shape, mask, axis, ddof)
if skipna and mask is not None:
values = values.copy()
np.putmask(values, mask, 0)
# xref GH10242
# Compute variance via two-pass algorithm, which is stable against
# cancellation errors and relatively accurate for small numbers of
# observations.
#
# See https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance
> avg = _ensure_numeric(values.sum(axis=axis, dtype=np.float64)) / count
pandas/core/nanops.py:954:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
a = array([['100', -0.6998177032455032, -0.06079253108280515]], dtype=object)
axis = 1, dtype = <class 'numpy.float64'>, out = None, keepdims = False
initial = <no value>, where = True
def _sum(a, axis=None, dtype=None, out=None, keepdims=False,
initial=_NoValue, where=True):
> return umr_sum(a, axis, dtype, out, keepdims, initial, where)
E TypeError: No loop matching the specified signature and casting was found for ufunc add
``` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/44127 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44127/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44127/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44127/events | https://github.com/pandas-dev/pandas/pull/44127 | 1,031,953,243 | PR_kwDOAA0YD84td6ln | 44,127 | Backport PR #44124 on branch 1.3.x (CI: Use Windows and MacOS Numpy Wheels) | {
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- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Since some tests are not running on `windows/moments` (https://github.com/pandas-dev/pandas/issues/37535), moving some lighter ewm tests to `test_ewm.py` | {
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Since some tests are not running on `windows/moments` (https://github.com/pandas-dev/pandas/issues/37535), moving some lighter rolling test to appropriate locations | {
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} | 4 | "2021-10-21T06:31:37Z" | "2021-10-27T12:12:48Z" | "2021-10-27T12:12:44Z" | CONTRIBUTOR | null | Currently, the `pandas.Series` that is used for the example for `pandas.Series.replace` has an index which is identical to its values (i.e. `pandas.Series([0, 1, 2, 3, 4])`). This can be quite confusing at a first glance (as it was for me), as I assumed that `pandas.Series.replace` was using the index of the series (whereas it is actually using the values). Updated the documentation to use `pandas.Series([1, 2, 3, 4, 5])` to remove this ambiguity.
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} | 11 | "2021-10-21T11:22:00Z" | "2021-11-15T13:29:51Z" | null | NONE | null | - [x] closes #44008
- [x] closes #36703
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- [x] closes #22642
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- [x] whatsnew entry
This PR makes `mean()` raise an exception when `sum()` returns a string. Sum performs as expected since it concatenates. However `_ensure_numeric` causes implicit conversion of `str` to a numeric datatype
https://github.com/pandas-dev/pandas/blob/f3f90c33966e3ba334c459ad89d607f820caa1f8/pandas/core/nanops.py#L694
Instead of this, the return value of `sum()` will be checked and if it is a string, an exception will be raised.
This is a breaking change. | {
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] | open | false | null | [] | null | 0 | "2021-10-21T15:49:55Z" | "2021-10-30T23:18:40Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
from pandas import util
df = util.testing.makeMixedDataFrame()
df = df.to_numpy()
df = pd.DataFrame(df)
df.columns = ["A", "B", "C", "D"]
df = df.set_index("B")
df1, df2 = df.iloc[:2], df.iloc[2:]
groupby1 = df1.groupby("B").sum()
groupby2 = df2.groupby("B").sum()
df_conc = pd.concat([groupby1, groupby2], axis=0)
print(f'\nConcatenated dataframe from partial results:\n{df_conc}')
print(f'\nOriginal dataframe:\n{df}')
conc_sum = df_conc.groupby(level=0).sum()
orig_sum = df.groupby(level=0).sum()
print(f'\nConcatenated df groupby.sum: \n{conc_sum}')
print(f'\nOriginal df groupby.sum: \n{orig_sum}')
```
### Issue Description
Script output
```bash
Concatenated dataframe from partial results:
A C
B
0.0 0.0 foo1
1.0 1.0 foo2
0.0 6.0 foo3foo5
1.0 3.0 foo4
Original dataframe:
A C D
B
0.0 0.0 foo1 2009-01-01
1.0 1.0 foo2 2009-01-02
0.0 2.0 foo3 2009-01-05
1.0 3.0 foo4 2009-01-06
0.0 4.0 foo5 2009-01-07
Concatenated df groupby.sum:
A # Column `C` is missed
B
0.0 6.0
1.0 4.0
Original df groupby.sum:
A C
B
0.0 6.0 foo1foo3foo5
1.0 4.0 foo2foo4
```
`groupby.sum` misses columns in case of splitting DataFrame on several parts and applying `groupby.sum` first for each part then for concatenation result of processed parts.
One observation: `groupby.sum` changed `dtypes` of partitions. If align `dtypes` of partitions with `df.dtypes` we can get expected behavior.
### Expected Behavior
Expected results:
```bash
Concatenated df groupby.sum:
A C
B
0.0 6.0 foo1foo3foo5
1.0 4.0 foo2foo4
Original df groupby.sum:
A C
B
0.0 6.0 foo1foo3foo5
1.0 4.0 foo2foo4
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-65-generic
Version : #73-Ubuntu SMP Mon Jan 18 17:25:17 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US
LOCALE : en_US.ISO8859-1
pandas : 1.3.3
numpy : 1.21.0
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.3
setuptools : 52.0.0.post20210125
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : 4.1.2
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.25.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.06.1
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : 0.15.0
pyarrow : 4.0.1
pyxlsb : None
s3fs : 2021.06.1
scipy : 1.7.0
sqlalchemy : 1.4.20
tables : 3.6.1
tabulate : None
xarray : 0.18.2
xlrd : 2.0.1
xlwt : None
numba : None
</details>
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} | 6 | "2021-10-21T16:23:27Z" | "2021-10-24T14:47:02Z" | "2021-10-24T14:47:02Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 2 | "2021-10-21T16:29:28Z" | "2021-10-21T17:47:11Z" | "2021-10-21T17:45:26Z" | CONTRIBUTOR | null | - [x] closes #44116
Looks like GH actions/setup-python seems to have randomly jumped from python 3.9.7 to python 3.10.0
Working:
https://github.com/pandas-dev/pandas/runs/3947277622?check_suite_focus=true#step:3:5
Failing:
https://github.com/pandas-dev/pandas/runs/3960125988?check_suite_focus=true#step:3:5
We can pin to a specific python version as per:
https://github.com/actions/setup-python#usage
Needs backport to 1.3.x also failing there to: https://github.com/pandas-dev/pandas/runs/3959049188?check_suite_focus=true | {
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} | 19 | "2021-10-21T18:00:00Z" | "2021-11-18T14:52:59Z" | null | NONE | null | When downloading the tar ball and executing “py setup.py develop” most of the build succeeds until you ge to the step where it tries to build pandas._libs.indexing, because indexing.c is not in the _libs directory, the build fails with the following error:
Exception: Cython-generated file ‘pandas\_lib/indexing.c’ not found.
Cython is required to compile pandas from a development branch.
Please install Cython or download a release package of pandas.
For the record, there is no official release of Pandas for Python 3.10 on Windows or Macintosh, only Linux.
cython is installed:
py -c “import cython; print(cython.__version__)”
0.29.24
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Needed for #43930
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https://api.github.com/repos/pandas-dev/pandas/issues/44140 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44140/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44140/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44140/events | https://github.com/pandas-dev/pandas/pull/44140 | 1,033,139,483 | PR_kwDOAA0YD84thxi5 | 44,140 | Move moments/test_moments_rolling_apply.py to window/test_apply.py | {
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- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Since some tests are not running on `windows/moments` (https://github.com/pandas-dev/pandas/issues/37535), moving some lighter apply tests to `test_apply.py`
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A part of addressing (#37535), moving some tests under the window directory.
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- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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https://github.com/pandas-dev/pandas/runs/3972068892?check_suite_focus=true
```
mypy --version
mypy 0.910
Performing static analysis using mypy
pandas/core/dtypes/cast.py:913: error: Incompatible types in assignment (expression has type "ndarray[Any, dtype[Any]]", variable has type "NumpyArrayT") [assignment]
pandas/tests/indexes/test_engines.py:65: error: unused "type: ignore" comment
```
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} | 5 | "2021-10-22T13:28:21Z" | "2021-10-22T18:49:38Z" | "2021-10-22T18:49:38Z" | CONTRIBUTOR | null | - [x] closes #44143
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] | open | false | null | [] | null | 0 | "2021-10-22T14:25:24Z" | "2021-10-30T23:20:10Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
pd.set_option("display.precision", 20)
df = pd.DataFrame(data=["0.01234567890123456789", "0.00498124967521367"], columns=["string"])
df["float"] = pd.to_numeric(df["string"])
df.head()
```
### Issue Description
The conversion to string shall at least return a precision of 17 digits after decimal point.
The first number exceeds voluntarily the maximum precision of 17 digits allowed by FLOAT64 representation. The second number has exactly 17 digits
### Expected Behavior
In 1.1.5 version, output:
```
string float
0 0.01234567890123456789 0.01234567890123457017
1 0.00498124967521367 0.00498124967521367066
```
When 1.2.0 version (and further versions) outputs:
```
string float
0 0.01234567890123456789 0.01234567890123450078
1 0.00498124967521367 0.00498124967521360040
```
I think the behaviour fro 1.1.5 should be the right one, keeping a 17 digits precision while converting string to float.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.11.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-693.el7.x86_64
Version : #1 SMP Tue Aug 22 21:09:27 UTC 2017
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.19.5
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3
setuptools : 58.2.0
Cython : 0.29.24
pytest : 6.1.2
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.10.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.25
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.19.0
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.54.1
</details>
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] | open | false | null | [] | null | 1 | "2021-10-22T15:44:14Z" | "2021-11-20T02:02:53Z" | null | NONE | null | ###
- [X] I have checked that the issue still exists on the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation
https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
### Documentation problem
The current documentation for the `MS` offset alias reads as follows: "month start frequency", indicating that it is the complement of `M` (which is "month end frequency").
However, for any date supplied to `pd.date_range(start=[date], ... freq='MS')` other than the first of the month, this offset alias starts from the beginning of the **next** month. See [this](https://stackoverflow.com/questions/34915828/pandas-date-range-to-generate-monthly-data-at-beginning-of-the-month) StackOverflow post (second answer) for a more detailed explanation.
However, in brief:
```
start = "2020-03-08"
end = "2021-03-08"
pd.date_range(start, end, freq='MS')
```
gives
```
DatetimeIndex(['2020-04-01', '2020-05-01', '2020-06-01', '2020-07-01',
'2020-08-01', '2020-09-01', '2020-10-01', '2020-11-01',
'2020-12-01', '2021-01-01', '2021-02-01', '2021-03-01'],
dtype='datetime64[ns]', freq='MS')
```
It should be noted that supplying the first day of the month as the start date keeps the expected behaviour (i.e. the start point of the range is the first of the month supplied).
### Suggested fix for documentation
If the behaviour of the `MS` offset alias is indeed correct (i.e. to start at the beginning of the **next** month), then this should be indicated in the documentation with a note.
For example:
"""
`MS` = month start frequency. Note, for any day other than the first day of the month this will cause the offset to start at the beginning of the next month.
"""
The above explanation correctly encapsulates the current functionality of the `MS` offset, especially within `pd.date_range()`. The current documentation would incorrectly lead a person to believe that the `MS` offset would cause the start date to be the start of the month of the date supplied.
If this behaviour is not correct, and `MS` should be causing the start date to be the start of the month of the date supplied, then a subsequent bug would need to be raised. | {
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} | 7 | "2021-10-22T16:03:41Z" | "2021-11-14T02:13:44Z" | "2021-11-14T02:13:44Z" | NONE | null | ###
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
# pd.show_versions()
df = pd.DataFrame({'X': [1, 2, 3],
'V1': [34, 6, 5],
'V2': [4, 7, 3],
'V3': [ 5, 56, 2]})
df.to_csv('df1.csv',index=False)
## Now read.
df_1 = pd.read_csv('df1.csv',usecols = ['X','V1','V3'],header = 0)
print(df_1)
df_2 = pd.read_csv('df1.csv',usecols = [0,1,3],header = 0,names = ['T','V1','V3'])
print(df_2)
df_3 = pd.read_csv('df1.csv',usecols = ['X','V1','V3'],header = 0,names = ['T','y1','y3'])
print(df_3)
```
### Issue Description
When importing a csv into a dataframe, I want to import certain columns and rename some of them. See example below.
```
import pandas as pd
# pd.show_versions()
df = pd.DataFrame({'X': [1, 2, 3],
'V1': [34, 6, 5],
'V2': [4, 7, 3],
'V3': [ 5, 56, 2]})
df.to_csv('df1.csv',index=False)
## Now read.
df_1 = pd.read_csv('df1.csv',usecols = ['X','V1','V3'],header = 0)
print(df_1)
df_2 = pd.read_csv('df1.csv',usecols = [0,1,3],header = 0,names = ['T','V1','V3'])
print(df_2)
df_3 = pd.read_csv('df1.csv',usecols = ['X','V1','V3'],header = 0,names = ['T','y1','y3'])
print(df_3)
```
When doing this, I get the error message that "ValueError: Usecols do not match columns, columns expected but not found: ['X']"
The code works when I don't use the names option.
The code also works when I supply the column indices to usecols instead of column names in the csv file. This is prone to human error, so I'd like to avoid it.
### Expected Behavior
Expect df_3 to be created with new column names.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3
setuptools : 57.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
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https://api.github.com/repos/pandas-dev/pandas/issues/44152 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44152/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44152/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44152/events | https://github.com/pandas-dev/pandas/issues/44152 | 1,033,980,403 | I_kwDOAA0YD849oUnz | 44,152 | ENH: tm.assert_(is|not)_copy, tm.shares_memory | {
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] | open | false | null | [] | null | 0 | "2021-10-22T22:09:47Z" | "2021-10-30T23:21:21Z" | null | MEMBER | null | There are a number of places in the tests where we check that a result is a copy, is not a copy, is a view, is not a view, etc. We end up with ad-hoc implementations all over the place. It'd be nice to have a something like `assert not tm.shares_memory(series, series.copy())`. This would likely require EA authors to implement parts of it. | {
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] | open | false | null | [] | null | 0 | "2021-10-22T22:26:16Z" | "2021-10-27T02:02:23Z" | null | CONTRIBUTOR | null | Ref: https://github.com/pandas-dev/pandas/issues/41740
https://app.circleci.com/pipelines/github/pandas-dev/pandas/1629/workflows/fdbd00a1-21ba-45fb-8813-c4cfd2a06305/jobs/32470
________________________ TestRename.test_rename_inplace ________________________
[gw1] linux -- Python 3.7.10 /home/circleci/miniconda3/envs/pandas-dev/bin/python
self = <pandas.tests.frame.methods.test_rename.TestRename object at 0xffff47ba8510>
float_frame = A B foo D
a3RR7rMUiG 0.656936 1.215185 0.629301 0.115558
7SCDtsxI3g -1.65....288884 -1.874402
WYIEEfxzV5 0.138755 -0.304313 0.827201 -0.329769
7WsSg25BaJ 0.632135 1.551402 1.333670 -0.128241
def test_rename_inplace(self, float_frame):
float_frame.rename(columns={"C": "foo"})
assert "C" in float_frame
assert "foo" not in float_frame
c_id = id(float_frame["C"])
float_frame = float_frame.copy()
return_value = float_frame.rename(columns={"C": "foo"}, inplace=True)
assert return_value is None
assert "C" not in float_frame
assert "foo" in float_frame
> assert id(float_frame["foo"]) != c_id
E assert 281471885249296 != 281471885249296
E + where 281471885249296 = id(a3RR7rMUiG 0.629301\n7SCDtsxI3g -0.051768\nvptsj7jAlg 0.355503\nB3utB9zDIM 0.047273\nOxQGHHlFri 0.780563\nhyK...3\nw2htgi2mxz 0.198167\n3O7zwMIcBM 1.288884\nWYIEEfxzV5 0.827201\n7WsSg25BaJ 1.333670\nName: foo, dtype: float64)
pandas/tests/frame/methods/test_rename.py:191: AssertionError | {
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] | open | false | null | [] | null | 4 | "2021-10-23T17:24:58Z" | "2021-10-28T03:36:20Z" | null | CONTRIBUTOR | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
pd.Series(["foo", "bar", pd.NA]).astype("str") // ["foo", "bar", "<NA>"]
pd.Series(["foo", "bar", np.NaN]).astype("str") // ["foo", "bar", "nan"]
pd.Series(["foo", "bar", None]).astype("str") // ["foo", "bar", "None"]
```
### Issue Description
NA/null values are converted to their string representation when doing `.astype("str")`, which seems like odd/undesirable behaviour.
### Expected Behavior
```
import pandas as pd
import numpy as np
pd.Series(["foo", "bar", pd.NA]).astype("str") // ["foo", "bar", pd.NA]
pd.Series(["foo", "bar", np.NaN]).astype("str") // ["foo", "bar", np.NaN]
pd.Series(["foo", "bar", None]).astype("str") // ["foo", "bar", None]
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 9b2bb732f09d8e870d806b337b97d3d99fd5b118
python : 3.9.7.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Wed Jun 23 00:26:31 PDT 2021; root:xnu-7195.141.2~5/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.4.0.dev0+952.g9b2bb732f0
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3
setuptools : 58.2.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.23.4
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : None
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : 0.8.9
xarray : None
xlrd : 2.0.1
xlwt : None
numba : None
</details>
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} | 1 | "2021-10-23T17:28:33Z" | "2021-10-23T17:35:34Z" | "2021-10-23T17:35:15Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
series = pd.Series(['bae systems (international) ltd'])
series.str.split('a. s.')
# returns
0 [b, stems (international) ltd]
```
### Issue Description
The .str.split() method of Pandas Series does not split items as expected.
### Expected Behavior
The .str method of Pandas Series does not split items as expected.
`s = "bae systems (international) ltd"`
`s.split('a. s.') `
`# should return `
`['bae systems (international) ltd'] `
### Installed Versions
<details>
pandas 1.3.0
</details>
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} | 5 | "2021-10-23T21:26:39Z" | "2021-11-10T11:25:48Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this issue exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
I am seeing a significantly increased read time for a CSV by pandas when I specify the `index_col`. I do not understand the reason behind it. Can you help me understand why that is happening and if that is actually the expected behaviour? Below is the code I am using:
```
import pandas as pd
#save the CSV to be used
pd.DataFrame({'id':np.arange(100000000),'b':np.random.choice(['a','b','c','d'],size=(100000000,),p=[0.25,0.25,0.25,0.25])}).to_csv('df_sp.csv',index=None)
dfpd = pd.read_csv('df_sp.csv')
#read time - 10.3 seconds
dfpd = pd.read_csv('df_sp.csv',index_col='id')
#read time - 1 minute 38.6 seconds
```
In fact, I am seeing significant improvement if I read the dataset without specifying ```index_col``` and then set the index by ```dfpd = dfpd.set_index('id')```. This takes just 1.6 more seconds. Why does pandas not default to always reading the dataframe with ```index_col``` as a column and then setting it as the index internally with ```set_index(index_col)``` when ```index_col``` is specified?
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-89-generic
Version : #100-Ubuntu SMP Fri Sep 24 14:50:10 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_IN
LOCALE : en_IN.ISO8859-1
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.25.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.09.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.23
tables : None
tabulate : 0.8.9
xarray : 0.19.0
xlrd : 2.0.1
xlwt : None
numba : 0.53.1
</details>
### Prior Performance
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- [X] I have read the [installation guide](https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html#installing-pandas).
### Platform
Windows-10-10.0.19043-SP0
### Installation Method
pip install
### pandas Version
~~1.3.1~~1.3.4(edited by @lithomas1, the logs indicate that the version installed is 1.3.4 not 1.3.1)
### Python Version
3.10
### Installation Logs
I did the following:
- fresh install of python 3.10 from python.org
- Added python executable and scripts directories to path (C:\Users\921479\AppData\Local\Programs\Python\Python310\ and C:\Users\921479\AppData\Local\Programs\Python\Python310\Scripts\)
- Ran a `pip install pandas`
The build dependencies step lagged, and then I got a huge error as follows:
```
Collecting pandas
Using cached pandas-1.3.4.tar.gz (4.7 MB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-c41017tf\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-e81txlwo\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.24,<3' 'oldest-supported-numpy>=0.10'
cwd: None
Complete output (235 lines):
Collecting setuptools>=51.0.0
Using cached setuptools-58.3.0-py3-none-any.whl (946 kB)
Collecting wheel
Using cached wheel-0.37.0-py2.py3-none-any.whl (35 kB)
Collecting Cython<3,>=0.29.24
Using cached Cython-0.29.24-py2.py3-none-any.whl (979 kB)
Collecting oldest-supported-numpy>=0.10
Using cached oldest_supported_numpy-0.10-py3-none-any.whl (3.8 kB)
Collecting numpy==1.21.2
Using cached numpy-1.21.2.zip (10.3 MB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'done'
Building wheels for collected packages: numpy
Building wheel for numpy (pyproject.toml): started
Building wheel for numpy (pyproject.toml): finished with status 'error'
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmp22eoyv9q_in_process.py' build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpvzzhq1ml'
cwd: C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f
Complete output (208 lines):
setup.py:63: RuntimeWarning: NumPy 1.21.2 may not yet support Python 3.10.
warnings.warn(
Running from numpy source directory.
C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f\tools\cythonize.py:69: DeprecationWarning: The distutils package is deprecated and slated for removal in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
from distutils.version import LooseVersion
Processing numpy/random\_bounded_integers.pxd.in
Processing numpy/random\bit_generator.pyx
Processing numpy/random\mtrand.pyx
Processing numpy/random\_bounded_integers.pyx.in
Processing numpy/random\_common.pyx
Processing numpy/random\_generator.pyx
Processing numpy/random\_mt19937.pyx
Processing numpy/random\_pcg64.pyx
Processing numpy/random\_philox.pyx
Processing numpy/random\_sfc64.pyx
Cythonizing sources
blas_opt_info:
blas_mkl_info:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
blis_info:
libraries blis not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelVisualFCompiler
Could not locate executable ifort
Could not locate executable ifl
customize AbsoftFCompiler
Could not locate executable f90
customize CompaqVisualFCompiler
Could not locate executable DF
customize IntelItaniumVisualFCompiler
Could not locate executable efl
customize Gnu95FCompiler
Could not locate executable gfortran
Could not locate executable f95
customize G95FCompiler
Could not locate executable g95
customize IntelEM64VisualFCompiler
customize IntelEM64TFCompiler
Could not locate executable efort
Could not locate executable efc
customize PGroupFlangCompiler
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
NOT AVAILABLE
accelerate_info:
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
libraries tatlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_blas_info:
libraries satlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
libraries ptf77blas,ptcblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_info:
libraries f77blas,cblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f\numpy\distutils\system_info.py:2026: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
if self._calc_info(blas):
blas_info:
libraries blas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f\numpy\distutils\system_info.py:2026: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
if self._calc_info(blas):
blas_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f\numpy\distutils\system_info.py:2026: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
if self._calc_info(blas):
NOT AVAILABLE
non-existing path in 'numpy\\distutils': 'site.cfg'
lapack_opt_info:
lapack_mkl_info:
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_lapack_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_clapack_info:
libraries openblas,lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
flame_info:
libraries flame not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries tatlas,tatlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_threads_info'>
NOT AVAILABLE
atlas_3_10_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries satlas,satlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_info'>
NOT AVAILABLE
atlas_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries ptf77blas,ptcblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_threads_info'>
NOT AVAILABLE
atlas_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries f77blas,cblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_info'>
NOT AVAILABLE
lapack_info:
libraries lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f\numpy\distutils\system_info.py:1858: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
lapack_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-ni6y_7h9\numpy_4aac2ddf32f143248a580c59946b9d1f\numpy\distutils\system_info.py:1858: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
NOT AVAILABLE
numpy_linalg_lapack_lite:
FOUND:
language = c
define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')]
Warning: attempted relative import with no known parent package
C:\Users\921479\AppData\Local\Programs\Python\Python310\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
running bdist_wheel
running build
running config_cc
unifing config_cc, config, build_clib, build_ext, build commands --compiler options
running config_fc
unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options
running build_src
build_src
building py_modules sources
creating build
creating build\src.win-amd64-3.10
creating build\src.win-amd64-3.10\numpy
creating build\src.win-amd64-3.10\numpy\distutils
building library "npymath" sources
error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/
----------------------------------------
ERROR: Failed building wheel for numpy
Failed to build numpy
ERROR: Could not build wheels for numpy, which is required to install pyproject.toml-based projects
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/58/58/b729eda34f78060e14cb430c91d4f7ba3cf1e34797976877a3a1125ea5b2/pandas-1.3.4.tar.gz#sha256=a2aa18d3f0b7d538e21932f637fbfe8518d085238b429e4790a35e1e44a96ffc (from https://pypi.org/simple/pandas/) (requires-python:>=3.7.1). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-c41017tf\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-e81txlwo\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.24,<3' 'oldest-supported-numpy>=0.10' Check the logs for full command output.
Using cached pandas-1.3.3.tar.gz (4.7 MB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-ava6d14u\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-bqyvyk0v\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"''
cwd: None
Complete output (232 lines):
Ignoring numpy: markers 'python_version == "3.7" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.7" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Ignoring numpy: markers 'python_version == "3.9" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Collecting setuptools>=51.0.0
Using cached setuptools-58.3.0-py3-none-any.whl (946 kB)
Collecting wheel
Using cached wheel-0.37.0-py2.py3-none-any.whl (35 kB)
Collecting Cython<3,>=0.29.21
Using cached Cython-0.29.24-py2.py3-none-any.whl (979 kB)
Collecting numpy==1.19.3
Using cached numpy-1.19.3.zip (7.3 MB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'error'
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpl9uv7ugv_in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpciex2_c4'
cwd: C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae
Complete output (204 lines):
setup.py:67: RuntimeWarning: NumPy 1.19.3 may not yet support Python 3.10.
warnings.warn(
Running from numpy source directory.
setup.py:480: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae\tools\cythonize.py:67: DeprecationWarning: The distutils package is deprecated and slated for removal in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
from distutils.version import LooseVersion
Processing numpy/random\_bounded_integers.pxd.in
Processing numpy/random\bit_generator.pyx
Processing numpy/random\mtrand.pyx
Processing numpy/random\_bounded_integers.pyx.in
Processing numpy/random\_common.pyx
Processing numpy/random\_generator.pyx
Processing numpy/random\_mt19937.pyx
Processing numpy/random\_pcg64.pyx
Processing numpy/random\_philox.pyx
Processing numpy/random\_sfc64.pyx
Cythonizing sources
blas_opt_info:
blas_mkl_info:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
blis_info:
libraries blis not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelVisualFCompiler
Could not locate executable ifort
Could not locate executable ifl
customize AbsoftFCompiler
Could not locate executable f90
customize CompaqVisualFCompiler
Could not locate executable DF
customize IntelItaniumVisualFCompiler
Could not locate executable efl
customize Gnu95FCompiler
Could not locate executable gfortran
Could not locate executable f95
customize G95FCompiler
Could not locate executable g95
customize IntelEM64VisualFCompiler
customize IntelEM64TFCompiler
Could not locate executable efort
Could not locate executable efc
customize PGroupFlangCompiler
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
libraries tatlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_blas_info:
libraries satlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
libraries ptf77blas,ptcblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_info:
libraries f77blas,cblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
accelerate_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae\numpy\distutils\system_info.py:1914: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
if self._calc_info(blas):
blas_info:
libraries blas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
if self._calc_info(blas):
blas_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
if self._calc_info(blas):
NOT AVAILABLE
non-existing path in 'numpy\\distutils': 'site.cfg'
lapack_opt_info:
lapack_mkl_info:
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_lapack_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_clapack_info:
libraries openblas,lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
flame_info:
libraries flame not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries tatlas,tatlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_threads_info'>
NOT AVAILABLE
atlas_3_10_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries satlas,satlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_info'>
NOT AVAILABLE
atlas_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries ptf77blas,ptcblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_threads_info'>
NOT AVAILABLE
atlas_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries f77blas,cblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_info'>
NOT AVAILABLE
lapack_info:
libraries lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
lapack_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-tdc7gjhm\numpy_350c6b7af14140aab1fa10dc4459a4ae\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
NOT AVAILABLE
numpy_linalg_lapack_lite:
FOUND:
language = c
define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')]
C:\Users\921479\AppData\Local\Programs\Python\Python310\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
running dist_info
running build_src
build_src
building py_modules sources
creating build
creating build\src.win-amd64-3.10
creating build\src.win-amd64-3.10\numpy
creating build\src.win-amd64-3.10\numpy\distutils
building library "npymath" sources
error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/cb/c0/7b3d69e6ee68bc54c97ba51f8c3c3e43ff1dbc7bd97347cc19a1f944e60a/numpy-1.19.3.zip#sha256=35bf5316af8dc7c7db1ad45bec603e5fb28671beb98ebd1d65e8059efcfd3b72 (from https://pypi.org/simple/numpy/) (requires-python:>=3.6). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpl9uv7ugv_in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpciex2_c4' Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement numpy==1.19.3 (from versions: 1.3.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.6.1, 1.6.2, 1.7.0, 1.7.1, 1.7.2, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1, 1.9.2, 1.9.3, 1.10.0.post2, 1.10.1, 1.10.2, 1.10.4, 1.11.0, 1.11.1, 1.11.2, 1.11.3, 1.12.0, 1.12.1, 1.13.0rc1, 1.13.0rc2, 1.13.0, 1.13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.14.4, 1.14.5, 1.14.6, 1.15.0rc1, 1.15.0rc2, 1.15.0, 1.15.1, 1.15.2, 1.15.3, 1.15.4, 1.16.0rc1, 1.16.0rc2, 1.16.0, 1.16.1, 1.16.2, 1.16.3, 1.16.4, 1.16.5, 1.16.6, 1.17.0rc1, 1.17.0rc2, 1.17.0, 1.17.1, 1.17.2, 1.17.3, 1.17.4, 1.17.5, 1.18.0rc1, 1.18.0, 1.18.1, 1.18.2, 1.18.3, 1.18.4, 1.18.5, 1.19.0rc1, 1.19.0rc2, 1.19.0, 1.19.1, 1.19.2, 1.19.3, 1.19.4, 1.19.5, 1.20.0rc1, 1.20.0rc2, 1.20.0, 1.20.1, 1.20.2, 1.20.3, 1.21.0rc1, 1.21.0rc2, 1.21.0, 1.21.1, 1.21.2, 1.21.3)
ERROR: No matching distribution found for numpy==1.19.3
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/71/65/3ab03ef46613e66880dba5b2c2cb5836938f0219389a11c10cfdc617e836/pandas-1.3.3.tar.gz#sha256=272c8cb14aa9793eada6b1ebe81994616e647b5892a370c7135efb2924b701df (from https://pypi.org/simple/pandas/) (requires-python:>=3.7.1). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-ava6d14u\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-bqyvyk0v\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' Check the logs for full command output.
Using cached pandas-1.3.2.tar.gz (4.7 MB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-6zfx8nxg\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-9tlzccif\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"''
cwd: None
Complete output (232 lines):
Ignoring numpy: markers 'python_version == "3.7" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.7" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Ignoring numpy: markers 'python_version == "3.9" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Collecting setuptools>=51.0.0
Using cached setuptools-58.3.0-py3-none-any.whl (946 kB)
Collecting wheel
Using cached wheel-0.37.0-py2.py3-none-any.whl (35 kB)
Collecting Cython<3,>=0.29.21
Using cached Cython-0.29.24-py2.py3-none-any.whl (979 kB)
Collecting numpy==1.19.3
Using cached numpy-1.19.3.zip (7.3 MB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'error'
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpsh1m6el8_in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpdxif4qbd'
cwd: C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2
Complete output (204 lines):
setup.py:67: RuntimeWarning: NumPy 1.19.3 may not yet support Python 3.10.
warnings.warn(
Running from numpy source directory.
setup.py:480: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2\tools\cythonize.py:67: DeprecationWarning: The distutils package is deprecated and slated for removal in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
from distutils.version import LooseVersion
Processing numpy/random\_bounded_integers.pxd.in
Processing numpy/random\bit_generator.pyx
Processing numpy/random\mtrand.pyx
Processing numpy/random\_bounded_integers.pyx.in
Processing numpy/random\_common.pyx
Processing numpy/random\_generator.pyx
Processing numpy/random\_mt19937.pyx
Processing numpy/random\_pcg64.pyx
Processing numpy/random\_philox.pyx
Processing numpy/random\_sfc64.pyx
Cythonizing sources
blas_opt_info:
blas_mkl_info:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
blis_info:
libraries blis not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelVisualFCompiler
Could not locate executable ifort
Could not locate executable ifl
customize AbsoftFCompiler
Could not locate executable f90
customize CompaqVisualFCompiler
Could not locate executable DF
customize IntelItaniumVisualFCompiler
Could not locate executable efl
customize Gnu95FCompiler
Could not locate executable gfortran
Could not locate executable f95
customize G95FCompiler
Could not locate executable g95
customize IntelEM64VisualFCompiler
customize IntelEM64TFCompiler
Could not locate executable efort
Could not locate executable efc
customize PGroupFlangCompiler
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
libraries tatlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_blas_info:
libraries satlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
libraries ptf77blas,ptcblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_info:
libraries f77blas,cblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
accelerate_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2\numpy\distutils\system_info.py:1914: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
if self._calc_info(blas):
blas_info:
libraries blas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
if self._calc_info(blas):
blas_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
if self._calc_info(blas):
NOT AVAILABLE
non-existing path in 'numpy\\distutils': 'site.cfg'
lapack_opt_info:
lapack_mkl_info:
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_lapack_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_clapack_info:
libraries openblas,lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
flame_info:
libraries flame not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries tatlas,tatlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_threads_info'>
NOT AVAILABLE
atlas_3_10_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries satlas,satlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_info'>
NOT AVAILABLE
atlas_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries ptf77blas,ptcblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_threads_info'>
NOT AVAILABLE
atlas_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries f77blas,cblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_info'>
NOT AVAILABLE
lapack_info:
libraries lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
lapack_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-65y3hff_\numpy_c0e7fa7db25449fd8329899d482227f2\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
NOT AVAILABLE
numpy_linalg_lapack_lite:
FOUND:
language = c
define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')]
C:\Users\921479\AppData\Local\Programs\Python\Python310\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
running dist_info
running build_src
build_src
building py_modules sources
creating build
creating build\src.win-amd64-3.10
creating build\src.win-amd64-3.10\numpy
creating build\src.win-amd64-3.10\numpy\distutils
building library "npymath" sources
error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/cb/c0/7b3d69e6ee68bc54c97ba51f8c3c3e43ff1dbc7bd97347cc19a1f944e60a/numpy-1.19.3.zip#sha256=35bf5316af8dc7c7db1ad45bec603e5fb28671beb98ebd1d65e8059efcfd3b72 (from https://pypi.org/simple/numpy/) (requires-python:>=3.6). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpsh1m6el8_in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpdxif4qbd' Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement numpy==1.19.3 (from versions: 1.3.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.6.1, 1.6.2, 1.7.0, 1.7.1, 1.7.2, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1, 1.9.2, 1.9.3, 1.10.0.post2, 1.10.1, 1.10.2, 1.10.4, 1.11.0, 1.11.1, 1.11.2, 1.11.3, 1.12.0, 1.12.1, 1.13.0rc1, 1.13.0rc2, 1.13.0, 1.13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.14.4, 1.14.5, 1.14.6, 1.15.0rc1, 1.15.0rc2, 1.15.0, 1.15.1, 1.15.2, 1.15.3, 1.15.4, 1.16.0rc1, 1.16.0rc2, 1.16.0, 1.16.1, 1.16.2, 1.16.3, 1.16.4, 1.16.5, 1.16.6, 1.17.0rc1, 1.17.0rc2, 1.17.0, 1.17.1, 1.17.2, 1.17.3, 1.17.4, 1.17.5, 1.18.0rc1, 1.18.0, 1.18.1, 1.18.2, 1.18.3, 1.18.4, 1.18.5, 1.19.0rc1, 1.19.0rc2, 1.19.0, 1.19.1, 1.19.2, 1.19.3, 1.19.4, 1.19.5, 1.20.0rc1, 1.20.0rc2, 1.20.0, 1.20.1, 1.20.2, 1.20.3, 1.21.0rc1, 1.21.0rc2, 1.21.0, 1.21.1, 1.21.2, 1.21.3)
ERROR: No matching distribution found for numpy==1.19.3
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/cf/f7/6c0dd488b5f5f1c0c1a48637df45046334d0be684faaf3536429f14aa9de/pandas-1.3.2.tar.gz#sha256=cbcb84d63867af3411fa063af3de64902665bb5b3d40b25b2059e40603594e87 (from https://pypi.org/simple/pandas/) (requires-python:>=3.7.1). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-6zfx8nxg\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-9tlzccif\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' Check the logs for full command output.
Using cached pandas-1.3.1.tar.gz (4.7 MB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-nu8neo3g\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-1mcvu0sy\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=38.6.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"''
cwd: None
Complete output (232 lines):
Ignoring numpy: markers 'python_version == "3.7" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.7" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Ignoring numpy: markers 'python_version == "3.9" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Collecting setuptools>=38.6.0
Using cached setuptools-58.3.0-py3-none-any.whl (946 kB)
Collecting wheel
Using cached wheel-0.37.0-py2.py3-none-any.whl (35 kB)
Collecting Cython<3,>=0.29.21
Using cached Cython-0.29.24-py2.py3-none-any.whl (979 kB)
Collecting numpy==1.19.3
Using cached numpy-1.19.3.zip (7.3 MB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'error'
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpx1aj0vd6_in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmp8ln0mfh0'
cwd: C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc
Complete output (204 lines):
setup.py:67: RuntimeWarning: NumPy 1.19.3 may not yet support Python 3.10.
warnings.warn(
Running from numpy source directory.
setup.py:480: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc\tools\cythonize.py:67: DeprecationWarning: The distutils package is deprecated and slated for removal in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
from distutils.version import LooseVersion
Processing numpy/random\_bounded_integers.pxd.in
Processing numpy/random\bit_generator.pyx
Processing numpy/random\mtrand.pyx
Processing numpy/random\_bounded_integers.pyx.in
Processing numpy/random\_common.pyx
Processing numpy/random\_generator.pyx
Processing numpy/random\_mt19937.pyx
Processing numpy/random\_pcg64.pyx
Processing numpy/random\_philox.pyx
Processing numpy/random\_sfc64.pyx
Cythonizing sources
blas_opt_info:
blas_mkl_info:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
blis_info:
libraries blis not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelVisualFCompiler
Could not locate executable ifort
Could not locate executable ifl
customize AbsoftFCompiler
Could not locate executable f90
customize CompaqVisualFCompiler
Could not locate executable DF
customize IntelItaniumVisualFCompiler
Could not locate executable efl
customize Gnu95FCompiler
Could not locate executable gfortran
Could not locate executable f95
customize G95FCompiler
Could not locate executable g95
customize IntelEM64VisualFCompiler
customize IntelEM64TFCompiler
Could not locate executable efort
Could not locate executable efc
customize PGroupFlangCompiler
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
libraries tatlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_blas_info:
libraries satlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
libraries ptf77blas,ptcblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_info:
libraries f77blas,cblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
accelerate_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc\numpy\distutils\system_info.py:1914: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
if self._calc_info(blas):
blas_info:
libraries blas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
if self._calc_info(blas):
blas_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
if self._calc_info(blas):
NOT AVAILABLE
non-existing path in 'numpy\\distutils': 'site.cfg'
lapack_opt_info:
lapack_mkl_info:
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_lapack_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_clapack_info:
libraries openblas,lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
flame_info:
libraries flame not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries tatlas,tatlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_threads_info'>
NOT AVAILABLE
atlas_3_10_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries satlas,satlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_info'>
NOT AVAILABLE
atlas_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries ptf77blas,ptcblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_threads_info'>
NOT AVAILABLE
atlas_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries f77blas,cblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_info'>
NOT AVAILABLE
lapack_info:
libraries lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
lapack_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-8nzemtl_\numpy_6fc982daf78f48dda61bd967a8235dbc\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
NOT AVAILABLE
numpy_linalg_lapack_lite:
FOUND:
language = c
define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')]
C:\Users\921479\AppData\Local\Programs\Python\Python310\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
running dist_info
running build_src
build_src
building py_modules sources
creating build
creating build\src.win-amd64-3.10
creating build\src.win-amd64-3.10\numpy
creating build\src.win-amd64-3.10\numpy\distutils
building library "npymath" sources
error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/cb/c0/7b3d69e6ee68bc54c97ba51f8c3c3e43ff1dbc7bd97347cc19a1f944e60a/numpy-1.19.3.zip#sha256=35bf5316af8dc7c7db1ad45bec603e5fb28671beb98ebd1d65e8059efcfd3b72 (from https://pypi.org/simple/numpy/) (requires-python:>=3.6). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpx1aj0vd6_in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmp8ln0mfh0' Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement numpy==1.19.3 (from versions: 1.3.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.6.1, 1.6.2, 1.7.0, 1.7.1, 1.7.2, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1, 1.9.2, 1.9.3, 1.10.0.post2, 1.10.1, 1.10.2, 1.10.4, 1.11.0, 1.11.1, 1.11.2, 1.11.3, 1.12.0, 1.12.1, 1.13.0rc1, 1.13.0rc2, 1.13.0, 1.13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.14.4, 1.14.5, 1.14.6, 1.15.0rc1, 1.15.0rc2, 1.15.0, 1.15.1, 1.15.2, 1.15.3, 1.15.4, 1.16.0rc1, 1.16.0rc2, 1.16.0, 1.16.1, 1.16.2, 1.16.3, 1.16.4, 1.16.5, 1.16.6, 1.17.0rc1, 1.17.0rc2, 1.17.0, 1.17.1, 1.17.2, 1.17.3, 1.17.4, 1.17.5, 1.18.0rc1, 1.18.0, 1.18.1, 1.18.2, 1.18.3, 1.18.4, 1.18.5, 1.19.0rc1, 1.19.0rc2, 1.19.0, 1.19.1, 1.19.2, 1.19.3, 1.19.4, 1.19.5, 1.20.0rc1, 1.20.0rc2, 1.20.0, 1.20.1, 1.20.2, 1.20.3, 1.21.0rc1, 1.21.0rc2, 1.21.0, 1.21.1, 1.21.2, 1.21.3)
ERROR: No matching distribution found for numpy==1.19.3
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/12/01/360d7f444f910ae16496c07e3f003cb8c641b4ca6c033408a4469a904df3/pandas-1.3.1.tar.gz#sha256=341935a594db24f3ff07d1b34d1d231786aa9adfa84b76eab10bf42907c8aed3 (from https://pypi.org/simple/pandas/) (requires-python:>=3.7.1). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-nu8neo3g\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-1mcvu0sy\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=38.6.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' Check the logs for full command output.
Using cached pandas-1.3.0.tar.gz (4.7 MB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-d1g2tmj9\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-xiih8tml\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=38.6.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"''
cwd: None
Complete output (232 lines):
Ignoring numpy: markers 'python_version == "3.7" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.7" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Ignoring numpy: markers 'python_version == "3.9" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Collecting setuptools>=38.6.0
Using cached setuptools-58.3.0-py3-none-any.whl (946 kB)
Collecting wheel
Using cached wheel-0.37.0-py2.py3-none-any.whl (35 kB)
Collecting Cython<3,>=0.29.21
Using cached Cython-0.29.24-py2.py3-none-any.whl (979 kB)
Collecting numpy==1.19.3
Using cached numpy-1.19.3.zip (7.3 MB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'error'
ERROR: Command errored out with exit status 1:
command: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpwf096qa__in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpr_if9ioq'
cwd: C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3
Complete output (204 lines):
setup.py:67: RuntimeWarning: NumPy 1.19.3 may not yet support Python 3.10.
warnings.warn(
Running from numpy source directory.
setup.py:480: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3\tools\cythonize.py:67: DeprecationWarning: The distutils package is deprecated and slated for removal in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
from distutils.version import LooseVersion
Processing numpy/random\_bounded_integers.pxd.in
Processing numpy/random\bit_generator.pyx
Processing numpy/random\mtrand.pyx
Processing numpy/random\_bounded_integers.pyx.in
Processing numpy/random\_common.pyx
Processing numpy/random\_generator.pyx
Processing numpy/random\_mt19937.pyx
Processing numpy/random\_pcg64.pyx
Processing numpy/random\_philox.pyx
Processing numpy/random\_sfc64.pyx
Cythonizing sources
blas_opt_info:
blas_mkl_info:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
blis_info:
libraries blis not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelVisualFCompiler
Could not locate executable ifort
Could not locate executable ifl
customize AbsoftFCompiler
Could not locate executable f90
customize CompaqVisualFCompiler
Could not locate executable DF
customize IntelItaniumVisualFCompiler
Could not locate executable efl
customize Gnu95FCompiler
Could not locate executable gfortran
Could not locate executable f95
customize G95FCompiler
Could not locate executable g95
customize IntelEM64VisualFCompiler
customize IntelEM64TFCompiler
Could not locate executable efort
Could not locate executable efc
customize PGroupFlangCompiler
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
libraries tatlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_blas_info:
libraries satlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
libraries ptf77blas,ptcblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_blas_info:
libraries f77blas,cblas,atlas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
accelerate_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3\numpy\distutils\system_info.py:1914: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
if self._calc_info(blas):
blas_info:
libraries blas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
if self._calc_info(blas):
blas_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
if self._calc_info(blas):
NOT AVAILABLE
non-existing path in 'numpy\\distutils': 'site.cfg'
lapack_opt_info:
lapack_mkl_info:
libraries mkl_rt not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_lapack_info:
libraries openblas not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
openblas_clapack_info:
libraries openblas,lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
flame_info:
libraries flame not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
atlas_3_10_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries tatlas,tatlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries tatlas,tatlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_threads_info'>
NOT AVAILABLE
atlas_3_10_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries satlas,satlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries satlas,satlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_3_10_info'>
NOT AVAILABLE
atlas_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries ptf77blas,ptcblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries ptf77blas,ptcblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_threads_info'>
NOT AVAILABLE
atlas_info:
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\lib
libraries lapack_atlas not found in C:\
libraries f77blas,cblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
libraries f77blas,cblas,atlas not found in C:\Users\921479\AppData\Local\Programs\Python\Python310\libs
<class 'numpy.distutils.system_info.atlas_info'>
NOT AVAILABLE
lapack_info:
libraries lapack not found in ['C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\lib', 'C:\\', 'C:\\Users\\921479\\AppData\\Local\\Programs\\Python\\Python310\\libs']
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
lapack_src_info:
NOT AVAILABLE
C:\Users\921479\AppData\Local\Temp\pip-install-yyjextkg\numpy_6165a234ed6a47fa8baa7cb3918386a3\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
NOT AVAILABLE
numpy_linalg_lapack_lite:
FOUND:
language = c
define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')]
C:\Users\921479\AppData\Local\Programs\Python\Python310\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
running dist_info
running build_src
build_src
building py_modules sources
creating build
creating build\src.win-amd64-3.10
creating build\src.win-amd64-3.10\numpy
creating build\src.win-amd64-3.10\numpy\distutils
building library "npymath" sources
error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/cb/c0/7b3d69e6ee68bc54c97ba51f8c3c3e43ff1dbc7bd97347cc19a1f944e60a/numpy-1.19.3.zip#sha256=35bf5316af8dc7c7db1ad45bec603e5fb28671beb98ebd1d65e8059efcfd3b72 (from https://pypi.org/simple/numpy/) (requires-python:>=3.6). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\tmpwf096qa__in_process.py' prepare_metadata_for_build_wheel 'C:\Users\921479\AppData\Local\Temp\tmpr_if9ioq' Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement numpy==1.19.3 (from versions: 1.3.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.6.1, 1.6.2, 1.7.0, 1.7.1, 1.7.2, 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1, 1.9.2, 1.9.3, 1.10.0.post2, 1.10.1, 1.10.2, 1.10.4, 1.11.0, 1.11.1, 1.11.2, 1.11.3, 1.12.0, 1.12.1, 1.13.0rc1, 1.13.0rc2, 1.13.0, 1.13.1, 1.13.3, 1.14.0rc1, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.14.4, 1.14.5, 1.14.6, 1.15.0rc1, 1.15.0rc2, 1.15.0, 1.15.1, 1.15.2, 1.15.3, 1.15.4, 1.16.0rc1, 1.16.0rc2, 1.16.0, 1.16.1, 1.16.2, 1.16.3, 1.16.4, 1.16.5, 1.16.6, 1.17.0rc1, 1.17.0rc2, 1.17.0, 1.17.1, 1.17.2, 1.17.3, 1.17.4, 1.17.5, 1.18.0rc1, 1.18.0, 1.18.1, 1.18.2, 1.18.3, 1.18.4, 1.18.5, 1.19.0rc1, 1.19.0rc2, 1.19.0, 1.19.1, 1.19.2, 1.19.3, 1.19.4, 1.19.5, 1.20.0rc1, 1.20.0rc2, 1.20.0, 1.20.1, 1.20.2, 1.20.3, 1.21.0rc1, 1.21.0rc2, 1.21.0, 1.21.1, 1.21.2, 1.21.3)
ERROR: No matching distribution found for numpy==1.19.3
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/53/05/bf382e8bc60731906a2e7261648bcea3a6b309ad2b9952010737a1b9413e/pandas-1.3.0.tar.gz#sha256=c554e6c9cf2d5ea1aba5979cc837b3649539ced0e18ece186f055450c86622e2 (from https://pypi.org/simple/pandas/) (requires-python:>=3.7.1). Command errored out with exit status 1: 'C:\Users\921479\AppData\Local\Programs\Python\Python310\python.exe' 'C:\Users\921479\AppData\Local\Temp\pip-standalone-pip-d1g2tmj9\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\921479\AppData\Local\Temp\pip-build-env-xiih8tml\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=38.6.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' Check the logs for full command output.
Using cached pandas-1.2.5.tar.gz (5.5 MB)
Installing build dependencies ... done
Getting requirements to build wheel ... -
``` | {
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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew Added method to ExcelFile class to read all the sheets. This allows the users to access a dictionary of all pd.DataFrames using the .sheets() method and access them more easily. Before, you would need to then call a pd.read_excel(ExcelFile, sheet_name) to access the data in that sheet.
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https://api.github.com/repos/pandas-dev/pandas/issues/44161 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44161/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44161/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44161/events | https://github.com/pandas-dev/pandas/pull/44161 | 1,034,303,814 | PR_kwDOAA0YD84tlbnx | 44,161 | TST: Move remaining ewm tests to window/ | {
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} | 0 | "2021-10-24T02:02:33Z" | "2021-10-24T17:20:46Z" | "2021-10-24T14:42:33Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Since some tests are not running on windows/moments (#37535), moving the remaining tests to test_ewm.py
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} | 2 | "2021-10-24T02:54:36Z" | "2021-11-06T20:51:56Z" | "2021-11-06T20:51:36Z" | NONE | null | ###
- [X] I have checked that the issue still exists on the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.var.html
https://pandas.pydata.org/docs/dev/reference/api/pandas.DataFrame.std.html
### Documentation problem
In all other APIs in DataFrame at least one example is given for better understanding.
I believe, function description is also available in notebooks but not any example.
It's good to have one example for mentioned APIs.
### Suggested fix for documentation
Fix: Use of atleast one example for better undertanding of function.
It's better because function description along with example creates clarity of its use and implimentation. | {
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} | 1 | "2021-10-24T03:03:08Z" | "2021-10-24T17:20:55Z" | "2021-10-24T14:43:41Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Since some tests are not running on windows/moments (#37535), moving the "consistency" expanding tests to `test_expanding.py`
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- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Since some tests are not running on windows/moments (#37535), moving the "consistency" rolling tests to the relevant files.
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} | 1 | "2021-10-24T15:37:53Z" | "2021-10-24T22:07:47Z" | "2021-10-24T22:07:43Z" | CONTRIBUTOR | null | - [ ] closes #18579
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] After discussion in #18579 the current tests were suggested
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} | 3 | "2021-10-24T16:36:46Z" | "2021-11-19T19:09:36Z" | null | CONTRIBUTOR | null | - [x] ~~closes~~ Incremental progress on #28283
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry | {
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Added two examples to the documentation of DataFrame.std function so that users can understand how to use it with different delta degrees of freedom. | {
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pd.ExcelFile lists the sheet names but does not read the book on instantiation. This is not a problem but makes front-end code necessary to access this information longer than it needs to be.
Current way to access a sheet:
file = pd.ExcelFile("./foo.xlsx")
pd.read_excel(file, sheet_name)
#### Describe the solution you'd like
I would like pd.ExcelFile to either have a new method or attribute that reads all sheets as data frames on call or to read all sheets on instantiation and be available as a property.
#### API breaking implications
This would add a new method or attribute to an existing class.
#### Describe alternatives you've considered
Alternatives include putting this functionality on the front-end user to implement. However, since this seems to fit as a core functionality, I request that it is added to the source code.
#### Additional context
Current way to read all sheets:
file = pd.ExcelFile("./foo.xlsx")
dfs = {sheet: pd.read_excel(file, sheet) for sheet in file.sheet_names}
```python
def sheets(self):
return {sheet: read_excel(self._io, sheet) for sheet in self._read.sheet_names}
``` | {
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} | 2 | "2021-10-24T20:47:32Z" | "2021-11-13T19:32:43Z" | "2021-10-24T23:26:35Z" | MEMBER | null | Makes the lists consistent with the governance docs and adds d-fine
cc @MarcoGorelli Would you like to add gousto too? | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Prelim to #43930 | {
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} | 0 | "2021-10-24T22:08:32Z" | "2021-10-25T18:27:41Z" | "2021-10-25T12:33:56Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Since some tests are not running on windows/moments (#37535), moving a "consistency" ewm tests to the `test_ewm.py`. | {
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] | open | false | null | [] | null | 20 | "2021-10-24T23:14:12Z" | "2021-10-28T03:31:28Z" | null | CONTRIBUTOR | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this issue exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
```python3
from timeit import timeit
import pandas as pd
# Create a dummy DataFrame of bools and null values.
df = pd.DataFrame([[True, False, pd.NA] * 200] * 200, dtype = "object")
# This runs very slowly!
print(timeit(lambda: df.astype("boolean").apply(lambda row: row.count(), axis = 1), number = 10)) # 112s
# (As can be easily seen, this is due partly to the `astype` on the entire DataFrame, but mainly to the subsequent `apply` being particularly slow for a boolean-dtype DataFrame).
print(timeit(lambda: df.astype("boolean"), number = 10)) # 3.98s
# This *equivalent* statement runs fast. There seems to be no good reason why the call to `apply` in the previous statement (overall equivalent) must be so slow.
print(timeit(lambda: df.apply(lambda row: row.astype("boolean").count(), axis = 1), number = 10)) # 0.95s
```
There is no problem using the first method in some cases, but it is inconvenient in other situations to cast back and forth between object-dtype and boolean-dtype just to make `apply` efficient.
### Installed Versions
<details>
commit : aced6eedf90f3fdb0e658f33ac89c13fad62b06e
python : 3.9.7.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Wed Jun 23 00:26:31 PDT 2021; root:xnu-7195.141.2~5/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.4.0.dev0+970.gaced6eedf9
numpy : 1.20.2
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.2.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.23.4
sphinx : 4.2.0
blosc : 1.10.6
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : None
pandas_datareader: 0.10.0
bs4 : 4.10.0
bottleneck : None
fsspec : 2021.10.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : 2021.10.1
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : 0.8.9
xarray : 0.19.0
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.54.1
</details>
### Prior Performance
Not applicable.
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} | 15 | "2021-10-24T23:25:55Z" | "2021-11-06T21:30:23Z" | "2021-11-06T21:30:23Z" | CONTRIBUTOR | null | xref https://github.com/pandas-dev/pandas/runs/3990827693?check_suite_focus=true
not sure where this changed recently or a numpy issue. | {
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} | 0 | "2021-10-25T00:38:44Z" | "2021-10-25T17:20:05Z" | "2021-10-25T17:18:56Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 4 | "2021-10-25T02:20:29Z" | "2021-10-31T16:18:48Z" | "2021-10-30T23:52:25Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/44176 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44176/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44176/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44176/events | https://github.com/pandas-dev/pandas/pull/44176 | 1,034,672,003 | PR_kwDOAA0YD84tmiwd | 44,176 | PERF: Improve performance in rolling.mean(engine=numba) | {
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} | 1 | "2021-10-25T04:43:08Z" | "2021-10-29T02:32:13Z" | "2021-10-28T02:07:11Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
This also starts to add a shared aggregation function (sum) that can shared between rolling/groupby/DataFrame when using the numba engine.
```
df = pd.DataFrame(np.ones((10000, 1000)))
roll = df.rolling(10)
roll.sum(engine="numba", engine_kwargs={"nopython": True, "nogil": True, "parallel": True})
%timeit roll.sum(engine="numba", engine_kwargs={"nopython": True, "nogil": True, "parallel": True})
211 ms ± 12.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) <- PR
424 ms ± 9.23 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) <- master
``` | {
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} | 0 | "2021-10-25T11:55:38Z" | "2021-10-25T14:08:51Z" | "2021-10-25T14:04:54Z" | CONTRIBUTOR | null | - [x] closes #43282
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
This PR adds:
- use of yaml anchors for the `flake8` and `yesqa` hooks
- updates to `scripts/sync_flake8_versions.py` since now both `yesqa` and `flake8` hooks have the same additional dependencies declared through a reusable anchor there is no need to check for sync between these two
PD. I am not sure this needs a `whatsnew` entry so I did not add it - unless y'all think there should be one | {
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] | open | false | null | [] | null | 3 | "2021-10-25T13:08:16Z" | "2021-10-30T23:27:37Z" | null | CONTRIBUTOR | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
pd.Series([1.7, 0.5, np.nan]).sum(skipna=None)
```
### Issue Description
In pandas 1.3.4 the example returns `2.2` on nightly it returns `nan`.
This lead to a test failure in xarray (we use pandas to double check a result - so we get a wrong `expected` value & could fix this but I still think this should not change silently).
### Expected Behavior
I think this should still return 2.2 or raise a deprecation warning or an error.
### Installed Versions
pandas was installed from scipy-wheels-nightly:
```bash
python -m pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple --no-deps --pre --upgrade --force-reinstall pandas
```
<details>
INSTALLED VERSIONS
------------------
commit : 9018d327defbe4d397eadc342e489e79bbc14b71
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-38-generic
Version : #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.4.0.dev0+972.g9018d327de
numpy : 1.20.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.2.0
Cython : None
pytest : 6.2.5
hypothesis : 6.24.0
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.10.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : 0.19.1.dev89+gfdabf3be
xlrd : None
xlwt : None
numba : 0.54.1
</details>
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} | 5 | "2021-10-25T13:11:38Z" | "2021-11-01T23:28:19Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
series = pd.Series(range(7))
grouper = pd.Series(list("ABBA"), dtype="category")
series.groupby(grouper)
# Raises ValueError: Length of grouper (4) and axis (7) must be same length
```
### Issue Description
When grouping by a `Series`, the values of the series after alignment determine the groups. In the example, however, pandas does not attempt to align the series and instead unnecessarily wants it to have the same length as the axis of grouping.
### Expected Behavior
I expect `obj.groupby(grouper)`, where `grouper` is a `Series` with a categorical data type, to allow the grouper to have unequal length and to align it, as in the following where the grouper has a non-categorical data type:
```python
series.groupby(grouper.astype(object)).groups
# Returns {'A': [0, 3], 'B': [1, 2]}
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 9b2bb732f09d8e870d806b337b97d3d99fd5b118
python : 3.8.12.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17134
machine : AMD64
processor : Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
pandas : 1.4.0.dev0+952.g9b2bb732f0
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.23.1
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.28.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.10.0
fastparquet : 0.7.1
gcsfs : 2021.10.0
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : 2021.10.0
scipy : 1.7.1
sqlalchemy : 1.4.25
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.1
</details>
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- [X] tests added / passed
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [X] whatsnew entry
While this fix enables grouping by a `Series` that has a categorical data type and length unequal to the axis of grouping, it maintains the requirement (developed in #3017, #9741, and #18525) that the length of a `Categorical` object used for grouping must match that of the axis of grouping. Additionally, this fix checks that requirement consistently with other groupers whose lengths must match—namely `list`, `tuple`, `Index`, and `numpy.ndarray`—and produces the same exception message when the lengths differ. | {
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame([pd.Interval(0,0)])
df.where(df.notnull())
```
### Issue Description
Data replacement using `DataFrame.where` raises `ValueError: Cannot set float NaN to integer-backed IntervalArray`,
when the dataframe instance contains one or multiple columns of `dtype: interval`.
### Expected Behavior
Data replacement and `dtype` conversion as per usual, i.e. in this case no replacement or column `dtype` conversion should be done, and the original `DataFrame` should be returned.
```python
expected = df
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-1160.15.2.el7.x86_64
Version : #1 SMP Thu Jan 21 16:15:07 EST 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 20.0.2
setuptools : 44.0.0
Cython : None
pytest : 6.2.5
hypothesis : None
show more (open the raw output data in a text editor) ...
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame({'a': [1, 2.5, 3, 5.7], 'b': [1.11, -2.7, -5.9, 10]})
def color_cell(cell):
if float(cell) > 0:
return "color: #4472c4"
if float(cell) < 0:
return "color: #ff0000"
df = df.style.applymap(color_cell, subset=["a", "b"])
df = df.format({"a": "{:.2%}"})
df
df = df.format({"b": "{:.2f}"})
df
```
### Issue Description
Multiple `.format` assignments are not applying to every column it gets called.
Prior to version 1.3.x (I've tested in 1.2.3), it had the expected behaviour described below and since I could not find this change in the release notes I am opening this issue.
### Expected Behavior
I would expect that multiple `.format` calls worked the same as calling one `.format` with just one dictionary:
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 11, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
pandas : 1.3.4
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.1
setuptools : 56.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : 2.9.1 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : 7.23.1
pandas_datareader: 0.9.0
bs4 : 4.9.3
bottleneck : None
fsspec : 2021.06.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : 3.0.8
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.3
sqlalchemy : 1.4.22
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 7 | "2021-10-26T02:13:17Z" | "2021-11-04T00:40:54Z" | "2021-11-04T00:40:28Z" | CONTRIBUTOR | null | - [X] closes #43563
- [X] closes #32835
- [X] closes #25549
- [X] xref #37963
- [X] tests added / passed
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [X] whatsnew entry
I've preserved current behavior, in which regex = None. Currently, it handles the pattern as a regex if the length of pattern is not 1. I believe that in the future, this may be worth considering deprecating.
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] | open | false | null | [] | null | 0 | "2021-10-26T03:15:06Z" | "2021-11-01T16:19:13Z" | null | CONTRIBUTOR | null | This somewhat deals with #44172, though that won't be fully resolved until 2D `ExtensionArray`s are supported (per the comments there).
CC @jbrockmendel
- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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} | 0 | "2021-10-26T04:30:18Z" | "2021-10-28T15:10:55Z" | "2021-10-28T12:32:47Z" | MEMBER | null | The goal here is to avoid special-casing in ExtensionBlock.where | {
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] | open | false | null | [] | null | 1 | "2021-10-26T09:17:30Z" | "2021-10-30T23:46:34Z" | null | NONE | null | #### Is your feature request related to a problem?
No.
#### Describe the solution you'd like
I'm using `pd.DataFrame.resample` for stats. There's a piece of data, and I'd like to be able to count the totals by time interval. However, I note that if there is no data or the data is `NaN` in a certain time period, the total value of the time period will be `0`, which is not my expectation because I am **confused** as to whether there is data in this interval.
```shell
>>> import pandas as pd
>>> index = pd.date_range('1/1/2000', periods=5, freq='T')
>>> series = pd.Series(1, index=index)
>>> series.pop('2000-01-01 00:01:00')
>>> series['2000-01-01 00:03:00'] = None
>>> print(series.resample('T').sum())
2000-01-01 00:00:00 1.0
2000-01-01 00:01:00 0.0
2000-01-01 00:02:00 1.0
2000-01-01 00:03:00 0.0
2000-01-01 00:04:00 1.0
Freq: T, dtype: float64
```
Is it possible to exclude time intervals for missing data from the statistical results or to present them as `NaN`? As follows:
exclude :
```shell
2000-01-01 00:00:00 1.0
2000-01-01 00:02:00 1.0
2000-01-01 00:04:00 1.0
Freq: T, dtype: float64
```
or present as `NaN`:
```shell
2000-01-01 00:00:00 1.0
2000-01-01 00:01:00 NaN
2000-01-01 00:02:00 1.0
2000-01-01 00:03:00 NaN
2000-01-01 00:04:00 1.0
Freq: T, dtype: float64
```
#### API breaking implications
This will change how a Resampler behaves when it encounters the sum method. | {
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} | 0 | "2021-10-26T10:25:32Z" | "2021-10-26T12:02:28Z" | "2021-10-26T11:06:16Z" | CONTRIBUTOR | null |
- [x] related to #44177
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
I sent a PR yesterday #44177 which was aimed at adding anchors to the `pre-commit-config.yaml` file
However, somehow I forgot to also update the corresponding test so this PR should remove the references to `yesqa` dependencies checks
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} | 2 | "2021-10-26T11:35:29Z" | "2021-11-01T08:53:40Z" | "2021-10-29T13:17:25Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import numpy as np
import pandas as pd
left = pd.Series([-np.inf, np.nan, -1.0, 0.0, 1.0, 10 / 3, np.inf], dtype=object)
right = pd.Series([None] * len(left))
print(pd.DataFrame(dict(left=left, right=right)))
print(f"{left.equals(right)=}")
print(f"{right.equals(left)=}")
```
### Issue Description
If one constructs a Series `left` containing floating-point data, but declared as dtype `object`, and another Series `right` of the same length, containing only `None`, then `left.equals.right` returns `True`, even though the two series are demonstrably not equal.
Making the comparison the other way round (i.e. `right.equals(right)`) returns `False` as is semantically correct.
Some preliminary testing brings up the following conditions for the bug to occur:
- `left` can consist of any combination of float values - including `+/-inf`, `NaN`, and both integral and fractional floats
- If `left` contains values of any other type, the `.equals` call will correctly return `False` - this includes ints and `None` itself
- The bug seems to occur with DataFrames as well - calling `.to_frame()` on both sides before calling `.equals()` has the same results.
- The bug seems to have been introduced in pandas 1.3.0. I have observed it to occur in 1.3.0 and 1.3.4, and it does not occur on 1.2.5.
- The bug occurs in both WSL and (ARM) macOS environments - I haven't tested on other platforms.
### Expected Behavior
`left.equals(right)` should return `False`.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 4.4.0-19041-Microsoft
Version : #1237-Microsoft Sat Sep 11 14:32:00 PST 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 20.3.4
setuptools : 58.2.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.3.24
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 1 | "2021-10-26T13:18:10Z" | "2021-10-28T01:37:17Z" | "2021-10-28T01:37:15Z" | CONTRIBUTOR | null | Usage of correct parameter ``exclude`` in description of ``exclude``-parameter of ``describe()``-function
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} | 5 | "2021-10-26T16:00:05Z" | "2021-10-26T23:48:20Z" | "2021-10-26T20:26:51Z" | MEMBER | null | - [x] closes #44106
- [ ] tests added / passed
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- [x] whatsnew entry
Using the example in #44106 I time 188.4s on master and 3.9s on this PR. | {
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} | 2 | "2021-10-26T16:06:04Z" | "2021-10-30T23:31:24Z" | "2021-10-30T22:24:35Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
cc @mdurant | {
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} | 3 | "2021-10-26T17:25:27Z" | "2021-10-28T03:39:16Z" | "2021-10-27T09:23:49Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
df = pd.DataFrame({'a':[1,2,3],'b':[1.1,2.2,3.3]})
# copy the df and duplicate a column
df2 = df[['a','b','b']]
# dtypes over the full df will give results
df2.dtypes
#iterating over columns will end in unclear error message
for col in df2.columns:
print(col, df2[col].dtype)
```
### Issue Description
```
df = pd.DataFrame({'a':[1,2,3],'b':[1.1,2.2,3.3]})
df2 = df[['a','b','b']]
df2.dtypes
```
output is
```
a int64
b float64
b float64
dtype: object
```
On iterating over columns to get dtype for each column, you got the error
```
for col in df2.columns:
print(col, df2[col].dtype)
```
here's the output
```
a int64
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-357-ec02ef63fa3c> in <module>()
1 for col in df2.columns:
----> 2 print(col, df2[col].dtype)
/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py in __getattr__(self, name)
5139 if self._info_axis._can_hold_identifiers_and_holds_name(name):
5140 return self[name]
-> 5141 return object.__getattribute__(self, name)
5142
5143 def __setattr__(self, name: str, value) -> None:
AttributeError: 'DataFrame' object has no attribute 'dtype'
```
### Expected Behavior
Error message should state the error root cause or at least some guidance.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : b5958ee1999e9aead1938c0bba2b674378807b3d
python : 3.7.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.104+
Version : #1 SMP Sat Jun 5 09:50:34 PDT 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.5
numpy : 1.19.5
pytz : 2018.9
dateutil : 2.8.2
pip : 21.1.3
setuptools : 57.4.0
Cython : 0.29.24
pytest : 3.6.4
hypothesis : None
sphinx : 1.8.5
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.2.6
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 5.5.0
pandas_datareader: 0.9.0
bs4 : 4.6.3
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.3
odfpy : None
openpyxl : 2.5.9
pandas_gbq : 0.13.3
pyarrow : 3.0.0
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.4.25
tables : 3.4.4
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 1.1.0
xlwt : 1.3.0
numba : 0.51.2
</details>
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} | 9 | "2021-10-26T18:16:19Z" | "2021-10-29T13:17:58Z" | "2021-10-29T13:17:25Z" | MEMBER | null | - [x] closes #44190
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
# Incorrect result and warning with timezone aware df
rng_with_tz = pd.date_range(start='2021-10-01T12:00:00+02:00', end='2021-10-02T12:00:00+02:00', freq='4H')
df_with_tz = pd.DataFrame(data={'A': rng_with_tz, 'B': rng_with_tz + pd.Timedelta(minutes=20)})
df_with_tz.iloc[2, 1] = pd.NaT
print(df_with_tz)
print(df_with_tz.max(axis=1))
# No problem with timezone naive dataframe
rng_tz_naive = pd.date_range(start='2021-10-01T12:00:00', end='2021-10-02T12:00:00', freq='4H')
df_tz_naive = pd.DataFrame(data={'A': rng_tz_naive, 'B': rng_tz_naive + pd.Timedelta(minutes=20)})
df_tz_naive.iloc[2, 1] = pd.NaT
print(df_tz_naive)
print(df_tz_naive.max(axis=1))
# Also no problem on other axis
print(df_with_tz.transpose().max(axis=0))
# And no problem without NaT
df_with_tz.iloc[2, 1] = df_with_tz.iloc[2, 0] + pd.Timedelta(minutes=20)
print(df_with_tz.max(axis=1))
```
### Issue Description
Using the `.max(axis=1)` operation on a dataframe with timezone aware datetime columns that contain at least one NaT
produces an incorrect result (and an obscure warning).
The issue occurs only when all conditions are met. For example there is a workaround by operating on
the other axis via transpose like `df.transpose().max(axis=0)`. Also dataframes with timezone naive columns do not show
the problematic behaviour as do dataframes that do not contain NaTs.
### Expected Behavior
The operation `df_with_tz.max(axis=1)` should return the max along columns thereby ignoring NaTs, similar to the same operation along rows (`axis=0`).
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.14393
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 0, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : de_DE.cp1252
pandas : 1.3.4
numpy : 1.20.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.3.0
Cython : None
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.54.1
</details>
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
mock_data = pd.DataFrame({
'date': ['0', '1', '2', '3'],
'value': [1, 2, 1, 1.5]
})
assert pd.api.types.is_numeric_dtype(mock_data.value) # passes
mock_data_pd_na.loc[2, 'value'] = pd.NA
assert pd.api.types.is_numeric_dtype(mock_data.value) # breaks
```
### Issue Description
Changing one value in a column with an `NA`/`NULL` should not change column's data type. That seems reasonable. Also, it seems the functionality is already there. I am not entirely sure if this is a bug or a feature.
Essentially it is due to the default assignment of a column type, which is `float64` not `pd.Float64Dtype()`. I am not sure if the migration is on the roadmap, but this bug could be an argument in its favor.
### Expected Behavior
```python
mock_data = pd.DataFrame({
'date': ['0', '1', '2', '3'],
'value': [1, 2, 1, 1.5]
})
mock_data.value = mock_data.value.astype(pd.Float64Dtype()) # this should happen by default
mock_data.value.dtype # Float64Dtype()
mock_data.loc[2, 'value'] = pd.NA
assert pd.api.types.is_numeric_dtype(mock_data.value) # still passes
mock_data.value.dtype # Float64Dtype()
```
### Installed Versions
<details>
```
pandas : 1.3.4
```
```
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-34-generic
Version : #36~20.04.1-Ubuntu SMP Fri Aug 27 08:06:32 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.21.2
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.25
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
numba : None
```
</details>
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Added tests to make sure that joining dataframes with multiindices containing dates doesn't break.
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} | 0 | "2021-10-27T04:28:11Z" | "2021-10-27T19:49:25Z" | "2021-10-27T18:24:06Z" | MEMBER | null | - [ ] closes #xxxx
- [x] tests added / passed
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- [x] whatsnew entry
Cast to common dtype instead of object, match IntervalIndex behavior. | {
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} | 1 | "2021-10-27T10:18:03Z" | "2021-10-27T11:53:31Z" | "2021-10-27T11:53:26Z" | CONTRIBUTOR | null | Updated the pyarrow version requirement from 0.17 to 1.0.1 in the "Multithreaded CSV reading" section, to make it in line with #44064.
Docs only, no functional changes.
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As far as I know, the only way to use the new string dtypes, is to set them manually either via the param `dtype` if it's supported or using `astype` otherwise the string will be stored as `object`.
#### Describe the solution you'd like
I'm aware that the string dtype is experimental, but it would be easy for us to play with it in large projects if there's a way to change the default behavior globally which can also be used in the future to set the storage for `StringDtype`.
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Ref: https://github.com/pandas-dev/pandas/issues/44173#issuecomment-952289166
Means we will have 3 more jobs (hopefully can reduce this back..) - but all can run in parallel.
https://github.com/pandas-dev/pandas/runs/4026818833?check_suite_focus=true | {
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} | 2 | "2021-10-27T21:51:28Z" | "2021-10-28T03:07:10Z" | "2021-10-28T03:03:05Z" | MEMBER | null | Equivalent to base class method. | {
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Found in #43744
> pandas/core/ops/mask_ops.py:49: error: Non-overlapping identity check (left operand type: "Union[bool, ndarray[Any, Any]]", right operand type: "NAType") [comparison-overlap]
> pandas/core/ops/mask_ops.py:66: error: Non-overlapping identity check (left operand type: "Union[bool, ndarray[Any, Any]]", right operand type: "NAType") [comparison-overlap]
> pandas/core/ops/mask_ops.py:106: error: Non-overlapping identity check (left operand type: "Union[bool, ndarray[Any, Any]]", right operand type: "NAType") [comparison-overlap]
> pandas/core/ops/mask_ops.py:114: error: Non-overlapping identity check (left operand type: "Union[bool, ndarray[Any, Any]]", right operand type: "NAType") [comparison-overlap]
edit: happens in a few more places as well
> pandas/core/arrays/timedeltas.py:537: error: Non-overlapping identity check (left operand type: "Timedelta", right operand type: "NaTType") [comparison-overlap]
> pandas/core/arrays/timedeltas.py:594: error: Non-overlapping identity check (left operand type: "Timedelta", right operand type: "NaTType") [comparison-overlap]
> pandas/core/arrays/timedeltas.py:637: error: Non-overlapping identity check (left operand type: "Timedelta", right operand type: "NaTType") [comparison-overlap]
> pandas/core/arrays/timedeltas.py:705: error: Non-overlapping identity check (left operand type: "Timedelta", right operand type: "NaTType") [comparison-overlap]
>
> pandas/core/arrays/masked.py:341: error: Non-overlapping identity check (left operand type: "Union[Union[str, int, float, bool], Union[Period, Timestamp, Timedelta, Interval]]", right operand type: "NoDefault") [comparison-overlap]
> pandas/core/arrays/masked.py:349: error: Non-overlapping identity check (left operand type: "Union[Union[str, int, float, bool], Union[Period, Timestamp, Timedelta, Interval]]", right operand type: "NAType") [comparison-overlap] | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/44216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44216/events | https://github.com/pandas-dev/pandas/issues/44216 | 1,038,175,846 | I_kwDOAA0YD8494U5m | 44,216 | BUG: read_sas segfault | {
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] | open | false | null | [] | null | 4 | "2021-10-28T07:29:48Z" | "2021-11-07T12:22:51Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
data = pd.read_sas('testdata4_nocompress.sas7bdat', format='sas7bdat', encoding='big5', chunksize=5000)
for d in data:
print(d)
```
### Issue Description
Hi teams, when I use read_sas to read my SAS dataset, it always occur segmentation fault in for loop
### Expected Behavior
It should print every chunksize with 5,000 rows in for loop.
### Installed Versions
<details>
INSTALLED VERSIONS
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17763
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : zh_TW.UTF-8
LOCALE : Chinese (Traditional)_Taiwan.950
pandas : 1.3.4
numpy : 1.21.0
pytz : 2021.1
dateutil : 2.8.1
pip : 20.2.3
setuptools : 49.2.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/44217 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44217/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44217/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44217/events | https://github.com/pandas-dev/pandas/issues/44217 | 1,038,242,688 | I_kwDOAA0YD8494lOA | 44,217 | BUG: to_sql with sqlalchemy[mysql], if_exists='repalce' raise 'sqlalchemy.exc.NoSuchTableError'; if_exists='fail' raise 'Table already exists' | {
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
class Database:
def __init__(self):
self.save_schema = 'build_dwd'
self.save_table = 'dwd_abtest_report'
self.mysql_dwd_config = {
'drivername': 'mysql+pymysql',
'username': 'xxx',
'password': 'xxx@#$xx',
'host': 'am-xxx.ads.aliyuncs.com',
'port': xxx,
}
self.mysql_engine_url = sqlalchemy.engine.URL.create(**self.mysql_dwd_config)
self.mysql_dwd_engine = sqlalchemy.create_engine(self.mysql_engine_url)
def get_mysql_data(self, sql):
return pandas.read_sql(sql=sql, con=self.mysql_dwd_engine, chunksize=None)
def write_mysql_data(self, df, if_replace=False):
df.to_sql(
con=self.mysql_dwd_engine,
schema=self.save_schema,
name=self.save_table,
if_exists='replace' if if_replace else 'append',
index=False,
index_label='id',
chunksize=10000,
)
```
### Issue Description
BUG: to_sql with sqlalchemy[mysql],
if_exists='repalce' raise 'sqlalchemy.exc.NoSuchTableError';
if_exists='fail' raise 'Table already exists'.
In fact, `if_exists='repalce' ` has error. when I gave schema, but it unknow schema.
### Expected Behavior
if_exists='repalce' should drop table, create table, and insert data.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Mon Aug 31 22:12:52 PDT 2020; root:xnu-6153.141.2~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : zh_CN.UTF-8
pandas : 1.3.2
numpy : 1.20.3
pytz : 2020.1
dateutil : 2.8.1
pip : 21.2.4
setuptools : 50.3.1.post20201107
Cython : 0.29.21
pytest : 6.1.1
hypothesis : None
sphinx : 4.1.2
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.28.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 2021.05.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.23
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.54.0
</details>
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} | 1 | "2021-10-28T10:46:53Z" | "2021-10-28T16:32:58Z" | "2021-10-28T13:17:57Z" | CONTRIBUTOR | null | This PR gives flexibility if we want the series string output to be like the Series repr, but with some adjustments.
So with this PR we we can now do:
```python
>>> params = pd.io.formats.format.get_series_repr_params(ser)
>>> params[my_param] = new_value
>>> ser.to_string(**params)
```
Followup to #43987.
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} | 0 | "2021-10-28T19:34:21Z" | "2021-10-29T16:59:15Z" | "2021-10-29T14:29:42Z" | CONTRIBUTOR | null | Some of the returned values should be booleans. Follow-up to #44218. | {
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] | open | false | null | [] | null | 7 | "2021-10-28T21:07:37Z" | "2021-11-07T18:29:54Z" | null | MEMBER | null | - [x] closes #44196 and #27794
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
This is an attempt at fixing the bug of wrong `min`/`max` aggregation with timezone aware data and at least one `pd.NaT` in the data to aggregate. While I still see quite a lot of weaknesses in my approach I want to elaborate why I did what I did, what the weaknesses of this approach are, how this might be handled better and why I didn't follow that path.
#### Problem description
To fully understand the problem at hand, let's look at three different cases:
```python
import pandas as pd
# CASE 1
# No Problem without NaT
rng_with_tz = pd.date_range(start='2021-10-01T12:00:00+02:00', end='2021-10-02T12:00:00+02:00', freq='4H')
df_with_tz = pd.DataFrame(data={'A': rng_with_tz, 'B': rng_with_tz + pd.Timedelta(minutes=20)})
df_with_tz.max(axis=1)
# No problem with timezone naive dataframe
# CASE 2
rng_tz_naive = pd.date_range(start='2021-10-01T12:00:00', end='2021-10-02T12:00:00', freq='4H')
df_tz_naive = pd.DataFrame(data={'A': rng_tz_naive, 'B': rng_tz_naive + pd.Timedelta(minutes=20)})
df_tz_naive.iloc[2, 1] = pd.NaT
df_tz_naive.max(axis=1)
# Incorrect result and warning with timezone aware df
# CASE 1
rng_with_tz = pd.date_range(start='2021-10-01T12:00:00+02:00', end='2021-10-02T12:00:00+02:00', freq='4H')
df_with_tz = pd.DataFrame(data={'A': rng_with_tz, 'B': rng_with_tz + pd.Timedelta(minutes=20)})
df_with_tz.iloc[2, 1] = pd.NaT
df_with_tz.max(axis=1)
```
When one drills down into the first case no problems arise. The `max` call is handled down to [`pandas/core/nanops.py:reduction`](https://github.com/pandas-dev/pandas/blob/master/pandas/core/nanops.py#L1023) and is running through fine. In the second case one finds that in [`pandas/core/nanops.py:reduction`](https://github.com/pandas-dev/pandas/blob/master/pandas/core/nanops.py#L1023) right after the call to [`pandas/core/nanops.py:_get_values`](https://github.com/pandas-dev/pandas/blob/66ce5de55b4aa6d4ca8bef65318cc9e2381689f6/pandas/core/nanops.py#L257) one realizes that all values are cast to integers, even the `pd.NaT`.
In the third case one can see that the values aren't casted and `pd.NaT` is replaced by `-np.inf` which comes from [this line](https://github.com/pandas-dev/pandas/blob/66ce5de55b4aa6d4ca8bef65318cc9e2381689f6/pandas/core/nanops.py#L1051). This replacement is the reason for our error:
```python
TypeError: '>=' not supported between instances of 'Timestamp' and 'float'
```
when we try to [apply the max from numpy](https://github.com/pandas-dev/pandas/blob/66ce5de55b4aa6d4ca8bef65318cc9e2381689f6/pandas/core/nanops.py#L1042)
which results from comparing `pd.Timestamp`s with `float`s (`np.inf`). This error is caught and all elements are converted into `np.nan`.
The reason behind the error is, that
```python
>>> import pandas as pd
>>> rng_with_tz = pd.date_range(start='2021-10-01T12:00:00+02:00', end='2021-10-02T12:00:00+02:00', freq='4H')
>>> rng_with_tz
DatetimeIndex(['2021-10-01 12:00:00+02:00', '2021-10-01 16:00:00+02:00',
'2021-10-01 20:00:00+02:00', '2021-10-02 00:00:00+02:00',
'2021-10-02 04:00:00+02:00', '2021-10-02 08:00:00+02:00',
'2021-10-02 12:00:00+02:00'],
dtype='datetime64[ns, pytz.FixedOffset(120)]', freq='4H')
>>> rng_with_tz.values.dtype
dtype('<M8[ns]')
>>> rng_with_tz = pd.date_range(start='2021-10-01T12:00:00+02:00', end='2021-10-02T12:00:00+02:00', freq='4H')
>>> df_with_tz = pd.DataFrame(data={'A': rng_with_tz, 'B': rng_with_tz + pd.Timedelta(minutes=20)})
>>> df_with_tz.values.dtype
dtype('O')
```
the `dtype` changes when using timezone aware data, though the `dtype`s of the single series is still `dtype('<M8[ns]')`. This has serious implications: In [`pandas/core/nanops.py:_get_values`](https://github.com/pandas-dev/pandas/blob/66ce5de55b4aa6d4ca8bef65318cc9e2381689f6/pandas/core/nanops.py#L257) the `if` condition in this line (https://github.com/pandas-dev/pandas/blob/66ce5de55b4aa6d4ca8bef65318cc9e2381689f6/pandas/core/nanops.py#L313) is `False` and no cast to happens but still the `pd.NaT` is replaced by `np.inf` which is the reason for the error stated above.
#### Possible improvements on this PR
If we could change the `dtype` of the timezone aware DataFrame with missing values to the `numpy` dtype: `dtype('<M8[ns]')` we should be fine. But I have no idea how we can achieve that, since these are not `pandas` but `numpy` types we are talking about and I didn't really understand how `numpy` determines it`s types.
#### Weaknesses of this PR
The assumption made while catching the exceptions aren't well tested (though all tests are passed) and there might be a better and more generic solution. | {
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