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As noted in https://github.com/pandas-dev/pandas/issues/6581, sounds like we are okay breaking compatibility with `np.compress` | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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Description:
In single object indexer case,
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... | null | 13 | 2019-12-27T20:27:15Z | 2021-08-29T23:11:51Z | null | CONTRIBUTOR | null | xref #19602
#### Code Sample, a copy-pastable example if possible
```python
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.25.3'
In [3]: df = pd.DataFrame({'mixed' : [1, 2, 'abc', 'def'], 'ints': [100, 200, 3
...: 00, 400]})
In [4]: df
Out[4]:
mixed ints
0 1 100
1 2 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30518 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30518/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30518/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30518/events | https://github.com/pandas-dev/pandas/issues/30518 | 542,996,532 | MDU6SXNzdWU1NDI5OTY1MzI= | 30,518 | UTC offset defined through to_datetime function appears reversed | {
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Sorry to intrude, I think there might be a trouble with parsing strings containing timezone data as 'GMT+1'.
Basically, I have a list of timestamps stored as strings:
'''
0 Sat Mar 30 2019 21:00:00 GMT+0100
1 Sat Mar 30 2019 22:00:00 GMT+0100
2 Sat Mar 30 2019 23:00:00 GMT+0100
3 Sun M... | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2019-12-27T22:46:28Z | 2020-01-03T11:58:55Z | 2020-01-03T11:55:36Z | CONTRIBUTOR | null | Hi, this is a quick fix for #15914.
After reading the issue I'm not sure if this is meant to be supported though, please let me know!
I ran into this issue when trying to pass to `read_excel` a binary file downloaded with `requests` so I think it would make sense to support this natively without the user having t... | {
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```python
# The existing implementation is:
def maybe_box_datetimelike(value):
# turn a datetime like into a Timestamp/timedelta as needed
if isinstance(value, (np.datetime64, datetime)):
value = tslibs.Timestamp(value)
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This uses a workaround to dynamically add the pytest.mark.xfail marker within the ... | {
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- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] `maybe_box_datetimelike` avoids unnecessary conversion of `value` to `tslibs.Timestamp` or `tslibs.Timedelta` if `value` is already an instance of `tslibs.Timestamp` ... | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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] | closed | false | null | [] | null | 1 | 2019-12-29T07:15:53Z | 2020-01-03T02:12:53Z | 2020-01-03T02:12:47Z | MEMBER | null | ### I'm not really sure if this is an "issue" or the intended behavior, but it just seems unnatural to me to get this result.
```python
import pandas as pd
df = pd.DataFrame({
'a': [1, 1, 2, 2],
'b': [3, 3, 4, 5],
})
df
a b
0 1 3
1 1 3
2 2 4
3 2 5
```
```python
df1 = df.groupby(... | {
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- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/30536 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30536/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30536/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30536/events | https://github.com/pandas-dev/pandas/issues/30536 | 543,402,724 | MDU6SXNzdWU1NDM0MDI3MjQ= | 30,536 | Named Aggregation : Can't use multiple lambda on the same column | {
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#### Code Sample, a copy-pastable example if possible
Reproduction :
```python
import numpy as np
import pandas as pd
print(pd.__version__) # 0.25.3
animals = pd.DataFrame({'kind': ['cat', 'dog', 'cat', 'dog'],
'height': [9.1, 6.0, 9.5, 34.0... | {
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this doesn’t ultimately matter as we create appropriate conda environments, but should move this forward | {
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... | 1 | 2019-12-29T15:08:25Z | 2021-03-14T16:59:50Z | null | MEMBER | null | This flag disallows usage of generic types that do not specify explicit type parameters. Moreover, built-in collections (such as list and dict) become disallowed as you should use their aliases from the typing module (such as List[int] and Dict[str, str]).
Enabling this would address common pull request review comme... | {
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```python
In [1]: import pandas as pd; pd.__version__
Out[1]: '0.26.0.dev0+1469.ge817ffff3'
In [2]: ts = pd.Timestamp('2020')
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pandas/compat/pickle_compat.py
pandas/_config/config.py
pandas/core/arrays/boolean.py
- [x] Contributes to #29547
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pandas\core\arrays\integer.py:549: error: Argument "copy" to "astype_nansafe" has incompatible type "None"; expected "bool"
pandas\core\arrays\boolean.py:527: error: Argument "copy" to "astype_nansafe" has incompatible type "None"; expected "bool"
``` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30549 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30549/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30549/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30549/events | https://github.com/pandas-dev/pandas/issues/30549 | 543,567,202 | MDU6SXNzdWU1NDM1NjcyMDI= | 30,549 | Re-Opening: Pivot Table Margins aren't correctly showing NaN values despite dummy variables | {
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pandas\core\computation\align.py:26: error: Incompatible types in assignment (expression has type "Tuple[partial[Any], None]", variable has type "Tuple[partial[Any]]")
panda... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30551 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30551/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30551/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30551/events | https://github.com/pandas-dev/pandas/pull/30551 | 543,592,035 | MDExOlB1bGxSZXF1ZXN0MzU3ODU3ODk3 | 30,551 | TYP: check_untyped_defs core.computation.eval | {
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"description": "Memory or execu... | open | false | null | [] | null | 26 | 2019-12-29T22:59:51Z | 2021-10-14T07:57:50Z | null | MEMBER | null | Suppose we have a Categorical with many unused categories:
```
cat = pd.Categorical(range(24), categories=range(10**5))
df = pd.DataFrame({"A": cat, "B": range(24), "C": range(24), "D": 1})
gb = df.groupby(["A", "B", "C"])
>>> gb.size() # memory balloons to 9+ GB before i kill it
```
There are only 24... | {
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- [x] closes #7883
- [x] closes #7820
- [x] closes #8720
- [x] closes #6783
- [x] closes #7072
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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"... | open | false | null | [] | null | 4 | 2019-12-30T08:18:05Z | 2021-07-25T04:31:24Z | null | NONE | null | #### Code Sample
```python
# code 1
def get_pid():
info = pd.read_csv('s3://vision.algo.data/cyz/tmp/test/11.csv', header=None, names=['pid'])
print(f'pid num : {len(info)}')
# code 2
def get_pid():
info = pd.read_csv('s3://vision.algo.data/cyz/tmp/test/11.csv', header=None, names=['pid'], memor... | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2019-12-30T10:55:14Z | 2019-12-30T22:13:49Z | 2019-12-30T22:13:40Z | CONTRIBUTOR | null | - [x] xref #30192
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Output of `python3 scripts/validate_docstrings.py pandas.DataFrame.head`
```bash
################################################################... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30557 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30557/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30557/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30557/events | https://github.com/pandas-dev/pandas/issues/30557 | 543,853,196 | MDU6SXNzdWU1NDM4NTMxOTY= | 30,557 | Should I be able to initialise a Series with dtype PeriodDtype? | {
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```python
import pandas as pd
pd.Series([pd.PeriodIndex(['2000-03'], freq='M')]) # works
pd.Series([pd.PeriodIndex(['2000-03'], freq='M')], dtype=pd.PeriodDtype('M')) # fails ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30558 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30558/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30558/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30558/events | https://github.com/pandas-dev/pandas/pull/30558 | 543,875,074 | MDExOlB1bGxSZXF1ZXN0MzU4MTA3OTQ5 | 30,558 | [TST] Test DataFrame.append with other dtypes | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/30559 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30559/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30559/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30559/events | https://github.com/pandas-dev/pandas/issues/30559 | 543,905,874 | MDU6SXNzdWU1NDM5MDU4NzQ= | 30,559 | BUG: Support win_type parameter with groupby.rolling | {
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... | 4 | 2019-12-30T14:53:57Z | 2020-10-05T01:11:35Z | null | NONE | null | It appears that rolling aggregations on groupby objects do not behave as expected. It looks like the `win_type` parameter is ignored. Here's a minimal example:
#### Code Sample
In this example, a rolling mean is calculated with "uniform" weights and also with "blackman" weights. In each case, the mean is calculat... | {
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- [X] closes #30365
- [X] tests added / passed
- [X] passes `black pandas`
- [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
xref #30366
cc @WillAyd
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Ref work done here: https://github.com/pandas-dev/pandas/pull/29712 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30562/events | https://github.com/pandas-dev/pandas/pull/30562 | 543,984,943 | MDExOlB1bGxSZXF1ZXN0MzU4MTk0ODk2 | 30,562 | ENH: Allow absolute precision in assert_almost_equal (#13357) | {
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Greetings! This is my first pull-request on an open source project, so I hope I did not miss anything at least too obvious... Thank you, in advance :smile:
I do have a few questions:
* Should I add the `versionadded` directive in all docstrings that were changed?
* Which "whatsnew" release notes... | {
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converting to UTC and returning a datetime64[ns] ndarray.
Closes https://github.com/pandas-dev/pandas/issues/6581 (this is the last one). | {
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```python
In [8]: import pandas as pd
...: import numpy as np
...:
...: data = np.arange(1000)
...: index = pd.date_range('2000', periods=len(data))
...: data = dict(zip(index, data))
...: s = pd.Series(data, index=index)
```... | {
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Having return types typed up will be good for the user experience (better piping etc.). | {
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- [ ] tests added / passed
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```python
x = pd.Series([None] * 10)
y = [False] * 3 + [True] * 5 + [False] * 2
x[y] = range(5)
x
# 0 None
# 1 None
# 2 None
# 3 3
# 4 4
# 5 0
# 6 1
# 7 2
# 8 None
# 9 None
```
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This is causing some tests to fail in #28399 and is something that should fixed regardless. Some care is needed in order to ensure that `is_string_dtype` doesn't return `True` once this update has been made.
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- [X] tests added / passed
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This is partially blocking #28399 as tests are failing there due to `kind` being `None`.
cc @TomAugspurger
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PR
```
[ 50.00%] ··· series_methods.SeriesConstructor.time_constructor ok
[ 50.00%] ··· ====== ==========
data
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pandas\core\config_init.py:310: error: Name 'get_ipython' is not defined
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This is extremely ugly, but gets the job done. It's probably worth doing to avoid silently failing, but not sure.
cc @topper-123. | {
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"de... | open | false | null | [] | null | 0 | 2019-12-31T04:30:05Z | 2020-09-22T01:35:38Z | null | CONTRIBUTOR | null | came across this blog / repo which shows nice issue metrics for matplotlib - should be very easy to create one for pandas
https://github.com/LaurenceMolloy/RepoDash
cc @pandas-dev/pandas-core
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@jreback
I just looked back at #30114 and found out that i overlooked to add `ignore_index` to `sort_index`, and this might be the reason this i... | {
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import pandas as pd
import numpy as np
import time
# print(pd.show_versions())
# create the columns and rows of the df
assets = np.array(range(3400))
dates = np.array(range(5000))
df_bool = pd.DataFrame(False, index=dates, columns=assets)
# create the array from the df
a = df_bool.to_numpy()
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Next up will be the pd.read_* functions. | {
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So far just testing how this looks like in the CI. Will open small PRs and get this implementing iteratively if this looks good. | {
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Note that this PR will *NOT* fix the issue for `pivot_table` for now, the reason is that there is already an argument called `dropna` in `pivot_tabl... | {
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Added test in `setup.py` to check if nthreads is positive and on Windows.
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> I have explored the issues like https://github.com/pandas-dev/pandas/issues/10534, https://github.com/pandas-dev/pandas/issues/21379, https://github.com/gte620v/pandas/blob/5cb8243f2dd31cc2155627f29cfc89bbf6d4b84b/pandas/io/tests/test_html.py#L715
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I've been studying the new `string`, `boolean` and `Intxx` dtypes and think it would be worthwhile to add something about the strings that you are allowed to use with extension arrays in specifying the dtypes. It could be an additional column in the dtypes table here:
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https://api.github.com/repos/pandas-dev/pandas/issues/30592 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30592/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30592/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30592/events | https://github.com/pandas-dev/pandas/pull/30592 | 544,295,589 | MDExOlB1bGxSZXF1ZXN0MzU4NDM5OTEw | 30,592 | CLN: remove no-longer-reachable addsub_int_array | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30593 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30593/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30593/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30593/events | https://github.com/pandas-dev/pandas/issues/30593 | 544,299,776 | MDU6SXNzdWU1NDQyOTk3NzY= | 30,593 | Pandas date_range does not work when using periods and adding holiday | {
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````
pd.date_range(start='2020-11-25 10:00',periods=14,
freq=pd.offsets.CustomBusinessHour(start='10:00'))
````
but if I add holidays then it produces more than 14 periods
````
pd.date_range(start='2020-11-25 10:00',periods=14,
freq=pd.offsets.CustomBusin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30594 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30594/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30594/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30594/events | https://github.com/pandas-dev/pandas/pull/30594 | 544,302,975 | MDExOlB1bGxSZXF1ZXN0MzU4NDQ1MzAw | 30,594 | BUG: DTA/TDA/PA add/sub object-dtype | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30595 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30595/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30595/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30595/events | https://github.com/pandas-dev/pandas/pull/30595 | 544,303,199 | MDExOlB1bGxSZXF1ZXN0MzU4NDQ1NDcx | 30,595 | REF: share join methods for DTI/TDI | {
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```
if isinstance(other, cls):
return False
```
In master, TimedeltaIndex uses _is_convertible_to_index which returns True here. The DTI method behavior is unchanged. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30596 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30596/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30596/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30596/events | https://github.com/pandas-dev/pandas/pull/30596 | 544,305,386 | MDExOlB1bGxSZXF1ZXN0MzU4NDQ3MDc2 | 30,596 | REF: move inference/casting out of Index.__new__ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30597 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30597/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30597/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30597/events | https://github.com/pandas-dev/pandas/issues/30597 | 544,305,504 | MDU6SXNzdWU1NDQzMDU1MDQ= | 30,597 | calculate business hours between two time stamp | {
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I have to calculate business hours between two time stamp.
Challenge is Monday and Saturday have different business hours than rest of the weekdays.
Monday starts at 2:30 AM and ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30599 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30599/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30599/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30599/events | https://github.com/pandas-dev/pandas/pull/30599 | 544,312,282 | MDExOlB1bGxSZXF1ZXN0MzU4NDUyMjI4 | 30,599 | REF: share _wrap_joined_index | {
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when it inspects whether or not it should return namedtuples
or plain tuples in it's response.
This PR addresses that bug by correcting the condition
that is used when making the check.
Closes: #28282
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https://api.github.com/repos/pandas-dev/pandas/issues/30608 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30608/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30608/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30608/events | https://github.com/pandas-dev/pandas/pull/30608 | 544,413,958 | MDExOlB1bGxSZXF1ZXN0MzU4NTI4NTY3 | 30,608 | CLN: remove warnings clearing | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30609 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30609/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30609/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30609/events | https://github.com/pandas-dev/pandas/issues/30609 | 544,414,486 | MDU6SXNzdWU1NDQ0MTQ0ODY= | 30,609 | Error on Warnings From C Extensions | {
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] | closed | false | null | [] | null | 13 | 2020-01-02T00:16:52Z | 2020-04-02T18:38:17Z | 2020-04-01T21:51:42Z | MEMBER | null | May differ on other platforms, but currently I see about 19 warnings from C extensions still left. I think we should aim to clean these up and set the `Werror` flag in CI as can help be proactive in identifying bugs from extensions
Here is the list of remaining warnings from a parallel build, so order may not be rel... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30610 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30610/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30610/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30610/events | https://github.com/pandas-dev/pandas/issues/30610 | 544,416,237 | MDU6SXNzdWU1NDQ0MTYyMzc= | 30,610 | DEPR: Remove pandas.datetime | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2020-01-02T00:36:40Z | 2020-09-09T23:04:43Z | 2020-01-02T04:01:44Z | CONTRIBUTOR | null | A follow up issue from #30296 , where it was discussed that pd.datetime should also be deprecated to only allow imports directly from datetime
```
>>> import pandas as pd
>>> pd.datetime
<class 'datetime.datetime'>
``` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30611 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30611/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30611/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30611/events | https://github.com/pandas-dev/pandas/pull/30611 | 544,416,985 | MDExOlB1bGxSZXF1ZXN0MzU4NTMwNjY5 | 30,611 | Improve ASV Environment Creation Performance | {
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Overriding default values documented here:
https://asv.readthedocs.io/en/stable/asv.conf.json.html#build-command-install-command-uninstall-command
I've picked 4 as the value assuming most people running benchmarks will have 2-4 cores. YMMV | {
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https://api.github.com/repos/pandas-dev/pandas/issues/30612 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30612/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30612/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30612/events | https://github.com/pandas-dev/pandas/pull/30612 | 544,423,802 | MDExOlB1bGxSZXF1ZXN0MzU4NTM1NTIw | 30,612 | CLN: replacing str.format with f-strings in several files. #29547 | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2020-01-02T02:00:41Z | 2020-01-03T00:36:54Z | 2020-01-03T00:36:40Z | CONTRIBUTOR | null | - [ ] xref #29547
- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/30613 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/30613/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/30613/comments | https://api.github.com/repos/pandas-dev/pandas/issues/30613/events | https://github.com/pandas-dev/pandas/pull/30613 | 544,432,101 | MDExOlB1bGxSZXF1ZXN0MzU4NTQxNzE1 | 30,613 | TYP: Add TypeVars to NDFrame | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2020-01-02T03:08:10Z | 2020-03-02T22:35:16Z | 2020-01-03T01:05:17Z | CONTRIBUTOR | null | Adding TypeVars to NDFrame methods that don't return optional values. This ensures that e.g. ``(DataFrame|Series).astype`` and ``(DataFrame|Series).copy`` have a known return type, which is nice.
Also adds ``PandasObject._ensure_type``, which is a method used to solve the problem with optional return values, but whe... | {
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