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https://api.github.com/repos/pandas-dev/pandas/issues/28413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28413/events | https://github.com/pandas-dev/pandas/pull/28413 | 492,870,548 | MDExOlB1bGxSZXF1ZXN0MzE2OTU5MDQ1 | 28,413 | REF: prepare Series arith op to be refactored to array op | {
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cc @pandas-dev/pandas-core
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- [ ] passes `black pandas`
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- [x] tests added / passed
- [x] passes `black pandas`
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Infers names in `MultiIndex.from_product` and normalizes handing of `names=None` between `from_arrays` and `from_product` | {
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... | 6 | 2019-09-12T16:53:15Z | 2019-09-14T00:40:11Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
# The first case shows that dicts cause the index argument to be more of a WHERE selector for rows...
>>> pd.Series({"a": 1, "b": 2, "c": 3}, index=["a", "b"])
a 1
b 2
dtype: int64
# But the docs + using a list have an error thrown if th... | {
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- [x] closes #xxxx
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(Will add whatsnew /... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28422/events | https://github.com/pandas-dev/pandas/issues/28422 | 492,977,737 | MDU6SXNzdWU0OTI5Nzc3Mzc= | 28,422 | test_cross_engine_pa_fp fails locally. | {
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"d... | closed | false | null | [] | null | 12 | 2019-09-12T19:05:41Z | 2020-04-23T23:31:18Z | 2020-04-23T23:31:18Z | MEMBER | null | ```
___________________________ test_cross_engine_pa_fp ___________________________
df_cross_compat = a b d e f
0 a 1 4.0 True 2013-01-01
1 b 2 5.0 False 2013-01-02
2 c 3 6.0 True 2013-01-03
pa = 'pyarrow', fp = 'fastparquet'
def test_cross_engine_pa_fp(df_cross_compat,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28423/events | https://github.com/pandas-dev/pandas/issues/28423 | 493,100,112 | MDU6SXNzdWU0OTMxMDAxMTI= | 28,423 | EA: Should IntegerNA support Inf, -Inf? | {
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{... | closed | false | null | [] | null | 16 | 2019-09-13T01:41:20Z | 2019-09-18T01:42:07Z | 2019-09-18T01:42:07Z | MEMBER | null | It uses a boolean mask with 8 bits under the hood, so it wouldn't be too tough to implement. Doing this would make it easier to keep IntegerNA arithmetic in sync with Series arithmetic. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28424/events | https://github.com/pandas-dev/pandas/issues/28424 | 493,105,019 | MDU6SXNzdWU0OTMxMDUwMTk= | 28,424 | ExtensionArray being checked if is instance of collections.abc.Sequence | {
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from pandas.api.extensions import ExtensionDtype,ExtensionArray, ExtensionScalarOpsMixin
class FP:
def __add__(self, other):
return self + other
pass
@pd.api.extensions.register_extension_dtype
class FPType(ExtensionDtype):
name = 'fp'
type = FP
@classmethod
def co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28425/events | https://github.com/pandas-dev/pandas/pull/28425 | 493,118,471 | MDExOlB1bGxSZXF1ZXN0MzE3MTYwMjA0 | 28,425 | Remove SparseSeries and SparseDataFrame | {
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Closes https://github.com/pandas-dev/pandas/issues/28407
Closes https://github.com/pandas-dev/pandas/issues/28025
Closes https://github.com/pandas-dev/pandas/issues/26777
Closes https://github.com/pandas-dev/pandas/issues/26227
~Not https://github.com/pandas-dev/pandas/issues/26123~... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28426/events | https://github.com/pandas-dev/pandas/issues/28426 | 493,363,865 | MDU6SXNzdWU0OTMzNjM4NjU= | 28,426 | Can't use same function twice with named aggregation | {
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```python
import pandas as pd
from functools import partial
quant50 = partial(np.percentile, q=50)
quant70 = partial(np.percentile, q=70)
test = pd.DataFrame({'col1': ['a', 'a', 'b', 'b', 'b'], 'col2': [1,2,3,4,5]})
test.groupby('col1').agg(
quan... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28427/events | https://github.com/pandas-dev/pandas/issues/28427 | 493,385,588 | MDU6SXNzdWU0OTMzODU1ODg= | 28,427 | Resampling and counting empty Series does not have a correct dtype | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2019-09-13T15:24:33Z | 2019-11-19T13:42:59Z | 2019-11-19T13:42:59Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
Short examples:
```python
import pandas as pd
a = pd.Series([], dtype="datetime64[ns]", index=pd.DatetimeIndex([]))
print(a.resample("D").size().dtype) # => actual datetime64[ns], expected int64
```
Longer example:
```python
import pandas as pd
t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28428 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28428/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28428/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28428/events | https://github.com/pandas-dev/pandas/pull/28428 | 493,401,792 | MDExOlB1bGxSZXF1ZXN0MzE3Mzg4NDk1 | 28,428 | BUG: Remove error raise to allow same input function on the same column in named aggregation | {
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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
https://github.com/pandas-dev/pandas/pull/27921#issuecomment-521794197
this was kind of mentioned in the PR27921, and the case used in the iss... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28429/events | https://github.com/pandas-dev/pandas/pull/28429 | 493,404,306 | MDExOlB1bGxSZXF1ZXN0MzE3MzkwNTY1 | 28,429 | BUG: close hdf store on any error | {
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"color": "5319... | closed | false | null | [] | null | 17 | 2019-09-13T16:03:15Z | 2020-02-02T01:03:53Z | 2020-02-02T01:03:53Z | NONE | null | NOTE: I'm opening the PR mainly to open a discussion about the current behaviour. If this is intended, please tell me. If not and you need me to write some tests, I'll do it :)
In `read_hdf`, if the `store.select()` call throws either a
`ValueError`, a `TypeError` or a `KeyError` then the store is closed.
Howeve... | {
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... | open | false | null | [] | null | 0 | 2019-09-13T16:09:35Z | 2020-05-16T20:39:54Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
Code adapted from https://github.com/ToucanToco/peakina/blob/master/peakina/cache.py#L84
```python
try:
metadata = pd.read_hdf(filepath)
except Exception: # catch all, on purpose
metadata = pd.DataFrame(columns=['ke... | {
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"followers_url": "https://api.github.com/users/wesm... | 9 | 2019-09-13T16:20:35Z | 2019-09-23T14:29:13Z | 2019-09-23T12:55:02Z | MEMBER | null | Following #28413, #28396, and #28395, these are all pretty straightforward refactors.
`arithmetic_op`, `comparison_op`, and `logical_op` are going to become the ops that we call `Block`-wise. Hopefully also `PandasArray` will use them directly.
Other follow-ups I have in mind:
- Move `should_extension_dispatch`... | {
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So I'm using this to clean up the sdist logic a bit, and exclude a few test data files that have snuck int... | {
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```python
In [1]: import pandas as pd
In [2]: s = pd.Series([4,5,6])
...: s1 = pd.Series([3,6, 5])
...: s2 = pd.Series([8,8,8])
...: s.between(s1, s2)
Out[2]:
0 True
1 False
2 True
dtype: bool
```
#### Problem description
Th... | {
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Also closes GH24897, GH24212, and GH17257
- [x] closes #28220, #24897, #24212, and #17257
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
Probably requires a bit more cleanu... | {
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"... | closed | false | null | [] | null | 0 | 2019-09-13T20:56:55Z | 2019-09-15T17:30:27Z | 2019-09-15T17:30:22Z | MEMBER | null | This shaves about 3.5-4% off of our import time.
If we want to continue down this path, we can do the same thing for `eval` and `reshape.api` pretty easily. Probably more than that, but I haven't looked that far.
FWIW: a full run of `asv` (on one commit, not `continuous`) imports pandas just over 5000 times, so ... | {
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- [x] passes `black pandas`
- [x] tests added / passed
- [x] whatsnew entry
This raises an error when attempting to cast a `Categorical` or `CategoricalIndex` containing `nans` to an integer dtype. Also had to remove the casting within `get_indexer_non_unique` since this won't always be possi... | {
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```python
import numpy as np
import pandas as pd
from concurrent.futures import ThreadPoolExecutor
fs = HadoopFileSystem(...)
table = fs.read_parquet(index_path, use_threads=True)
dataset_index = table.to_pandas(categories=['key'])
# dataset_index.loc[... | {
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- [ ] passes `black pandas`
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- [x] tests added / passed
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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```python
>>> import pandas as pd
>>>
>>> pd.__version__
'0.25.0+350.g330bedeb7'
>>>
>>> df = pd.DataFrame({'A': range(1, 6)})
>>>
>>> df.eval('A/2')
0 0.5
1 1.0
2 1.5
3 2.0
4 2.5
dtype: float64
>>>
>>> df.eval('A/2', truediv = Fals... | {
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- [x] tests added / passed (no new tests added, test_dtypes.py, passes locally)
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` (passed locally)
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I was able to ... | {
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```python
from pandas import Categorical
Categorical(['2015-01-01']).astype('datetime64[ns]') # works
Categorical(['2015-01-01']).astype('datetime64[ns, MET]') # fails
```
This is because the `astype` method returns
```
np.array(self, dtype=dt... | {
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- Unknown parameters {kwargs, args}
- Parameter "func" type should use "str" instead of "string"
- Parameter "*args" description should start with a capital letter
- Parameter "**kwargs" description should start with a capital letter
- pandas.core.common.pipe : Unknown parameters {kwargs, args} in #27976
... | {
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when the test intentionally raises an exception, the entire transaction,
including the table creation, gets rolled back, so there is no table
to query. Wrapping the table CREATE statement in its own transaction
avoids the issue.
- [x] clos... | {
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] | open | false | null | [] | null | 9 | 2019-09-14T21:36:53Z | 2019-09-22T15:18:22Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df1 = pd.DataFrame(data=np.random.rand(100,1))
df2 = pd.DataFrame(data=np.random.rand(100,1))
a = plt.subplot()
df1.plot(ax=a,style='.')
df2.plot(ax=a,style='.')
```
####... | {
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```python
import pandas as pd
df = pd.DataFrame({'date': ['2019-01-01', '2019-02-01', '2018-01-01', '2018-02-01']})
df["date"] = pd.to_datetime(df["date"])
pd.crosstab(df["date"].dt.month, df["date"].dt.year)
```
#### Problem description
This gives my a `2x2` table with the years 2018 and 2... | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2019-09-16T09:08:55Z | 2019-09-20T14:38:51Z | 2019-09-20T14:32:33Z | CONTRIBUTOR | null | - [x] part of #26792
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] annotate all rendering methods of `pandas.core.frame.DataFrame`
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"d... | open | false | null | [] | null | 1 | 2019-09-16T09:10:17Z | 2020-05-22T03:36:28Z | null | CONTRIBUTOR | null | follow up https://github.com/pandas-dev/pandas/pull/28176#pullrequestreview-286089893
Right now, `astype(str)` converts `np.nan` into string.
```
In [3]: pd.Series(['foo', np.nan]).astype(str)
Out[3]:
0 foo
1 nan
dtype: object
```
After merging #28176, `astype(str)` will preserve `np.nan`.
Revie... | {
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```python
import pandas
from pandas.io.json import build_table_schema
df = pandas.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]})
build_table_schema(df)
```
produces
```
{'fields': [{'name': 'index', 'type': 'integer'},
{'name': 'col1', 'type': '... | {
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read into a Series[sparse] / DataFrame[sparse]. https://github.com/pandas-dev/pandas/pull/28425
cc @jreback @jorisvandenbossche.
I've just done the minimal amount to get this working. It may shed some light on how we can design an API for dis... | {
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- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/28458 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28458/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28458/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28458/events | https://github.com/pandas-dev/pandas/issues/28458 | 494,093,723 | MDU6SXNzdWU0OTQwOTM3MjM= | 28,458 | pd.read_csv does not allow passing valid delimiters when using sep=None | {
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] | open | false | null | [] | null | 4 | 2019-09-16T14:40:07Z | 2020-12-13T16:41:13Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
Using a sample file of:
```
email
test@gmail.com
test2@yahoo.com
test3@microsoft.com
```
```python
import pandas as pd
pd.read_csv('email.txt', sep=None)
Out[24]:
e ail
test@g ail.co NaN
test2@yahoo.co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28459 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28459/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28459/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28459/events | https://github.com/pandas-dev/pandas/pull/28459 | 494,102,360 | MDExOlB1bGxSZXF1ZXN0MzE3OTIxOTk1 | 28,459 | BUG: fix size()/count() when resamping empty series (#28427) | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/28460 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28460/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28460/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28460/events | https://github.com/pandas-dev/pandas/issues/28460 | 494,103,365 | MDU6SXNzdWU0OTQxMDMzNjU= | 28,460 | PerformanceWarning: misleading warning for all columns | {
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... | 1 | 2019-09-16T14:56:07Z | 2020-05-03T20:34:01Z | null | NONE | null | #### Code Sample
```python
import pandas as pd
df = pd.DataFrame({'string': ['a', 'b'], 'number': [1.0, 2.0], 'mix': ['a', 2.0]})
df.to_hdf('foo.h5', 'data')
```
#### Problem description
The problem is related to the feature added in #3622. The warning for types that cannot be saved as c-types applies for ... | {
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] | closed | false | null | [] | null | 9 | 2019-09-16T15:01:11Z | 2019-10-24T05:27:43Z | 2019-10-23T22:59:45Z | CONTRIBUTOR | null | Both `DataFrame.pct_change` and `Series.pct_change` should have default behavior that matches the "obvious" implementation:
```python
lag = series.shift(1)
change = (series - lag) / lag
```
Unfortunately, the default behavior is set to `fill_method='pad'` which surprises many people (#6389). We should start a ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28462 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28462/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28462/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28462/events | https://github.com/pandas-dev/pandas/issues/28462 | 494,114,424 | MDU6SXNzdWU0OTQxMTQ0MjQ= | 28,462 | Survey on Pull Request Prioritization | {
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We are an international group of researchers investigating Pull Requests management activities. We implemented an automated approach, named CARTESIAN, for prioritizing Pull Requests (PRs) received by an open-source project according to the likelihood of acceptance/response. We would lik... | {
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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
The Test code is inspired from a similar tests in
`RaiseError`: https://github.com/pandas-dev/pandas/blob/master/pandas/tests/arrays/categorical/te... | {
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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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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `black pandas`
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"description": "np.nan, ... | closed | false | null | [] | null | 5 | 2019-09-16T17:56:07Z | 2020-10-12T21:56:48Z | 2020-10-12T21:56:48Z | MEMBER | null | Based on tests.series.test_operators `test_logical_ops_df_compat`
```
# GH#1134
s1 = pd.Series([True, False, True], index=list("ABC"))
s2 = pd.Series([True, True, False], index=list("ABD"))
exp_ser = pd.Series([True, False, False, False], index=list("ABCD"))
res_ser = s1 & s2
tm.assert_series_equal(res_ser, ... | {
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```python
animals = pd.DataFrame({'kind': ['cat', 'dog', 'cat', 'dog'],
'height': [9.1, 6.0, 9.5, 34.0],
'weight': [7.9, 7.5, 9.9, 198.0]})
# Yields an error
animals.groupby('kind').agg(mean_height=('... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28468 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28468/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28468/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28468/events | https://github.com/pandas-dev/pandas/issues/28468 | 494,240,661 | MDU6SXNzdWU0OTQyNDA2NjE= | 28,468 | DataFrame.min/max with axis=1, datetime64[ns, tz] types and NaT values returns NaNs | {
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] | closed | false | null | [] | null | 1 | 2019-09-16T19:45:07Z | 2020-03-09T20:07:38Z | 2019-09-16T21:20:31Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
s1 = pd.Series([pd.Timestamp('2017-01-01T10', tz='UTC'), pd.Timestamp('2017-01-01T11', tz='UTC')])
s2 = pd.Series([pd.Timestamp('2017-01-01T12', tz='UTC'), pd.NaT])
df = pd.DataFrame(dict(s1=s1, s2=s2))
df.min(axis=1)
```
produces:
```
0 ... | {
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... | 4 | 2019-09-16T20:22:27Z | 2019-10-07T15:01:02Z | 2019-10-07T15:01:02Z | CONTRIBUTOR | null | The length of `formatters` should match the number of columns
Both of these should error with a nice message.
```python
In [2]: df = pd.DataFrame(columns=['a', 'b', 'c'])
In [3]: df.to_html(formatters=['{}'.format])
In [4]: df.to_html(formatters=['{}'.format] * 5)
```
Currntly `In [4]` succeeds, sile... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28470 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28470/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28470/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28470/events | https://github.com/pandas-dev/pandas/pull/28470 | 494,289,164 | MDExOlB1bGxSZXF1ZXN0MzE4MDczMTYz | 28,470 | POC: deprecation with strict removal version | {
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Decorator that just registers the deprecation in a dict that we can check and test-time. | {
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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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"id": ... | open | false | null | [] | null | 3 | 2019-09-16T21:55:16Z | 2020-05-18T11:12:58Z | null | NONE | null | Slightly related to #28380
Currently an issue in Dask https://github.com/dask/dask/issues/5294 for implementing Named Aggregation (introduced in pandas 0.25.0) is open. To implement this it needs to use `_normalize_keyword_aggregation` and `_is_multi_agg_with_relabel`.
Making it public would be useful for frame... | {
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... | 7 | 2019-09-16T22:00:22Z | 2020-04-02T23:02:40Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
def test_idxmin(self):
df = pd.DataFrame({'accountid': ['12345'], 'createddate': [pd.Timestamp(2019, 1, 1)]})
min = df.groupby('accountid')[['createddate']].idxmin(axis=1)
print(min)
df2 = pd.DataFrame({'accoun... | {
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] | closed | false | null | [] | null | 39 | 2019-09-17T01:32:07Z | 2020-11-22T05:14:08Z | 2020-11-22T05:14:07Z | NONE | null | - [x] closes #22529
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
**Problem:** Currently if you give two Series with the same name to pd.crosstab it will ignore one of the columns. By minimally modifying a current ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28475 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28475/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28475/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28475/events | https://github.com/pandas-dev/pandas/pull/28475 | 494,358,581 | MDExOlB1bGxSZXF1ZXN0MzE4MTI3MTg0 | 28,475 | BUG: Raise when casting infinity to int | {
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- [x] passes `black pandas`
- [x] whatsnew entry
Raises a `ValueError` when attempting to cast a `Float64Index` with infinite values to a (non-`ExtensionArray`) integer dtype. Currently this returns a garbage value:
```
idx ... | {
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```python
import numpy as np
import pandas as pd
X = np.array([[0, 1, 0], [4, 0, 0]])
X = pd.DataFrame(X).astype(pd.SparseDtype(float, fill_value=0.0))
X
X.sparse
np.sqrt(X).sparse
```
#### Problem description
The data shouldn't be coerced to dense. H... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28477 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28477/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28477/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28477/events | https://github.com/pandas-dev/pandas/issues/28477 | 494,379,133 | MDU6SXNzdWU0OTQzNzkxMzM= | 28,477 | BUG: DataFrame[SparseArray] coerces to dense with .T | {
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"gists... | [] | closed | false | null | [] | null | 1 | 2019-09-17T03:22:02Z | 2019-09-17T18:10:36Z | 2019-09-17T18:10:36Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
```python
import numpy as np
import pandas as pd
X = np.array([[0, 1, 0], [4, 0, 0]])
X = pd.DataFrame(X).astype(pd.SparseDtype(float, fill_value=0.0))
X.dtypes
X.T.dtypes
```
#### Problem description
Given the entire dataframe is sparse, it should pro... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28479 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28479/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28479/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28479/events | https://github.com/pandas-dev/pandas/issues/28479 | 494,402,947 | MDU6SXNzdWU0OTQ0MDI5NDc= | 28,479 | value_counts() crashes if groupby object contains empty groups | {
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The following example illustrates the problem:
```
import pandas as pd
df = pd.... | {
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] | open | false | null | [] | null | 1 | 2019-09-17T05:41:23Z | 2020-02-25T21:09:46Z | null | CONTRIBUTOR | null | A consistent naming convention should be used for type aliases.
Maybe CamelCase as the stdlib typing module is in Camel Case, but suggestions are welcome.
Inconsistent names could be found in `pandas.io.formatters.formatter`, `formatters_type` and `float_format_type`. Look for other similar names too and fix them a... | {
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`combine_first` returns weird results in case there exist unmatched columns between two timestamp dataframes. this issue probably relates to #24357 (not retaining dtypes)
```python
import pandas as pd
x = pd.DataFrame([pd.NaT,pd.NaT],columns=['a']).T
y = pd.DataFrame([[pd.NaT,pd.NaT],pd... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28483 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28483/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28483/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28483/events | https://github.com/pandas-dev/pandas/issues/28483 | 494,614,069 | MDU6SXNzdWU0OTQ2MTQwNjk= | 28,483 | Unexpected results on groupby([]).sum() | {
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```python
# n = df1.groupby(['Year', 'State', 'Regulator', 'Industry','Product', 'Count']).sum() # <-- this produces the error
```
#### Problem description
[Hi, I think there's a problem dropping/excluding data points with groupby.sum function. I've performed the following code (see abov... | {
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] | closed | false | null | [] | null | 3 | 2019-09-17T15:44:47Z | 2021-02-05T20:40:32Z | 2021-02-05T20:40:32Z | NONE | null | Matplotlib has a nice formatter class named matplotlib.dates.ConciseDateFormatter, which is a candidate to become Matplotlib's default date formatter in future versions (as of MPL 3.1.1, see
[Matplotlib documentation](https://matplotlib.org/gallery/ticks_and_spines/date_concise_formatter.html)).
It would be nice i... | {
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```python
import pandas.io.sql
# current state
table_name = 'my_new_table'
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"description": "Sparse Data Type",
"id": 49182326,
"name": "Sparse",
"node_id": "MDU6TGFiZWw0OTE4MjMyNg==",
"url": "https://api.github.com/repos/pandas-dev/pandas/labels/Sparse"
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... | 5 | 2019-09-17T20:07:23Z | 2021-09-12T17:40:59Z | null | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
from scipy import sparse
X_sp = sparse.coo_matrix((2**30, 2**10))
X_pd = pd.DataFrame.sparse.from_spmatrix(X_sp)
X_sp.sum(axis=1)
X_sp.sum(axis=0)
X_pd.sum(axis=1)
X_pd.sum(axis=0)
```
#### Problem description
The new ... | {
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"followers_url": "https://api.github.com/users/j... | 14 | 2019-09-17T20:42:48Z | 2020-09-22T13:41:53Z | 2020-09-22T13:41:25Z | CONTRIBUTOR | null | We should be able to test astype to our own type
```diff
diff --git a/pandas/tests/extension/base/casting.py b/pandas/tests/extension/base/casting.py
index 7146443bf8..b33ab93031 100644
--- a/pandas/tests/extension/base/casting.py
+++ b/pandas/tests/extension/base/casting.py
@@ -1,3 +1,5 @@
+import pytest
+
... | {
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Validate that we use
```python
class Foo:
"""
Doc.
"""
pass
```
instead of:
```python
class Bar:
"""
Doc.
"""
pass
```
(note the blank line between `class Bar:` and the docstring. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28490/events | https://github.com/pandas-dev/pandas/issues/28490 | 494,948,765 | MDU6SXNzdWU0OTQ5NDg3NjU= | 28,490 | pd.read_parquet can't handle an S3 directory | {
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*pyarrow* can load parquet files directly from S3. So can Dask. *pandas* seems to not be able to. This would be really cool and since you use *pyarrow* underneath it should be easy.
For example in *pyarrow*, even with push-down filters:
```python
stocks_close_ds = ParquetDataset(
'data/v4.parq... | {
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might provide some inspiration about Interval API that we might want to include / emulate
cc @jschendel | {
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- [x] passes `black pandas`
- [x] whatsnew entry
Fixes a bug in `astype_nansafe` where `NaT` was ignored when casting a datetime or timedelta to `int`. I put the test in `pandas/tests/dtypes/test_common.py` since I couldn't find another place where `astype_nansafe` was tested. Also add... | {
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- no issue opened
- [ ] tests added / passed
- no, only docs modified
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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```python
import pandas as pd
# pandas 0.25
sample_data = pd.Series([1, 2])
result = sample_data.sample(frac=0.2)
result.empty
```
#### Problem description
When I sample with a fraction I always expect a result, returning an empty series is unexpected... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28496 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28496/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28496/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28496/events | https://github.com/pandas-dev/pandas/issues/28496 | 495,092,182 | MDU6SXNzdWU0OTUwOTIxODI= | 28,496 | Reindexing overlapping IntervalIndex throws KeyError | {
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```python
import pandas as pd
df = pd.DataFrame({"start": ["2017-01-01 13:09:01", "2017-01-01 13:09:04", "2017-01-01 13:09:12"],
"end": ["2017-01-01 13:09:05", "2017-01-01 13:09:09", "2017-01-01 13:09:14"],
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] | closed | false | null | [] | null | 1 | 2019-09-18T14:09:07Z | 2019-09-19T14:00:03Z | 2019-09-19T14:00:03Z | MEMBER | null | After this is merged, https://dev.pandas.io will have the new website, and the dev docs will be in https://dev.pandas.io/docs
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https://api.github.com/repos/pandas-dev/pandas/issues/28498 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28498/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28498/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28498/events | https://github.com/pandas-dev/pandas/pull/28498 | 495,257,644 | MDExOlB1bGxSZXF1ZXN0MzE4ODM4NTcz | 28,498 | TST: added a test case for special character in file name | {
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- [x] closes #26074
- [x] 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/28499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28499/events | https://github.com/pandas-dev/pandas/pull/28499 | 495,266,401 | MDExOlB1bGxSZXF1ZXN0MzE4ODQ1Nzg0 | 28,499 | WEB: Adding governance document to the website | {
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] | closed | false | null | [] | null | 6 | 2019-09-18T14:33:27Z | 2019-11-14T16:53:46Z | 2019-11-14T16:53:46Z | MEMBER | null | This adds the governance document to the new website.
The rest of the information in the governance repo should already be in the website, so we shouldn't need that repo anymore.
Advantages I see on having this in the website:
- Users can see the governance information from the website, with the same look and fe... | {
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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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```python
In [13]: pd.read_json("[null]", dtype=True)
Out[13]:
0
0 NaN
In [14]: pd.read_json("[null]", dtype=False)
Out[14]:
0
0 None
```
I think the second above is an issue - should probably return `np.nan` instead of `None` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28502/events | https://github.com/pandas-dev/pandas/pull/28502 | 495,305,381 | MDExOlB1bGxSZXF1ZXN0MzE4ODc3NzI1 | 28,502 | Cleaned up JSON test with ambiguous DTA usage | {
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I created a new test specific to the handling of DTA with `dtype=X` to provide a more logical separation of concerns | {
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] | closed | false | null | [] | null | 6 | 2019-09-18T17:14:51Z | 2019-09-18T22:15:18Z | 2019-09-18T22:14:37Z | NONE | null | I am migrating my `SparseDataFrame`s to `DataFrames` with sparse columns. I can no longer transpose this DataFrame and have it stay sparse. The behavior I was expecting was to have a fully sparse DataFrame maintain sparsity when transposed.
```python
>>> arrs = scipy.sparse.coo_matrix(np.random.randint(2,size=(1000... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28505 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28505/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28505/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28505/events | https://github.com/pandas-dev/pandas/pull/28505 | 495,361,155 | MDExOlB1bGxSZXF1ZXN0MzE4OTIzMTY1 | 28,505 | BUG/CLN: DatetimeTZDtype.construct_from_string Exception | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2019-09-18T17:33:49Z | 2019-09-20T14:25:15Z | 2019-09-20T12:34:28Z | MEMBER | null | The bug part of this is that "dateutil/something_invalid" fails to raise on master because dateutil.tz.gettz("something_invalid") returns None instead of raising. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28506 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28506/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28506/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28506/events | https://github.com/pandas-dev/pandas/issues/28506 | 495,398,002 | MDU6SXNzdWU0OTUzOTgwMDI= | 28,506 | TST: DataFrame operations with ExtensionArrays | {
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```
In [4]: df1 = pd.DataFrame({'a': DecimalArray(make_data()[:5]), 'b': DecimalArray(make_data()[:5])})
In [5]: df1
Out[5]:
a ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28507 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28507/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28507/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28507/events | https://github.com/pandas-dev/pandas/issues/28507 | 495,402,718 | MDU6SXNzdWU0OTU0MDI3MTg= | 28,507 | COMPAT: tzawareness check behavior is different from stdlib | {
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"followers_url": "https://api.github.com/users/j... | 2 | 2019-09-18T19:05:05Z | 2020-10-04T04:47:47Z | 2020-10-04T04:47:47Z | MEMBER | null | `Timestamp` comparisons raise TypeError in some cases where `datetime`s do not:
```
ts = pd.Timestamp.now()
ts2 = ts.tz_localize("UTC")
dt = ts.to_pydatetime()
dt2 = ts2.to_pydatetime()
>>> ts == ts2 # <-- TypeError
>>> dt == dt2
False
```
The datetime comparison _will_ raise for inequalities, just no... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28508 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28508/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28508/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28508/events | https://github.com/pandas-dev/pandas/pull/28508 | 495,408,737 | MDExOlB1bGxSZXF1ZXN0MzE4OTYyMDkz | 28,508 | BUG: fix array_equivalent with mismatched tzawareness | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2019-09-18T19:18:34Z | 2019-09-20T14:15:56Z | 2019-09-20T12:38:23Z | MEMBER | null | Some of this can be simplified if we change the behavior discussed in #28507. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28509 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28509/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28509/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28509/events | https://github.com/pandas-dev/pandas/pull/28509 | 495,414,708 | MDExOlB1bGxSZXF1ZXN0MzE4OTY2OTE3 | 28,509 | [WIP, ENH] Adds cumulative methods to ea | {
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"c... | closed | false | null | [] | null | 63 | 2019-09-18T19:32:41Z | 2021-10-04T00:13:12Z | 2021-10-04T00:13:12Z | CONTRIBUTOR | null | - [x] closes #28385
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
Problem specific
- [X] Add abstract tests similar to pandas/tests/extension/base/reduce.py
- [X] Add TestFixtures for Accumulations
- [x] Imple... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28510/events | https://github.com/pandas-dev/pandas/pull/28510 | 495,453,355 | MDExOlB1bGxSZXF1ZXN0MzE4OTk4ODg5 | 28,510 | Re-implemented parametrization of test_frame_from_json_to_json | {
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"d... | closed | false | null | [] | null | 2 | 2019-09-18T21:02:02Z | 2019-09-20T18:06:29Z | 2019-09-20T17:53:30Z | MEMBER | null | This piece was broken off of #27838 as it made the diff much larger, so hopefully easier to digest on its own.
As is, parametrization here has brought up a lot of rough edges which are responsible for some of the complexity. These are noted with TODOs and summarized as follows (save Py35 issues, which aren't worth a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28511 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28511/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28511/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28511/events | https://github.com/pandas-dev/pandas/pull/28511 | 495,455,151 | MDExOlB1bGxSZXF1ZXN0MzE5MDAwMzkw | 28,511 | Pick and choose numpy version based on Python 2 or 3. | {
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- [ ] tests added / passed
- [ ] passes `black pandas` (not applicable, `black setup.py` changes too many quotes, polluting the diff).
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
cc @jorisvandenbossche | {
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https://api.github.com/repos/pandas-dev/pandas/issues/28512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/28512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/28512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/28512/events | https://github.com/pandas-dev/pandas/issues/28512 | 495,481,523 | MDU6SXNzdWU0OTU0ODE1MjM= | 28,512 | DEPR: Deprecate numpy argument in read_json | {
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"followers_url": "https://api.github.com/users/wesm... | 6 | 2019-09-18T22:18:24Z | 2020-01-09T03:25:48Z | 2020-01-09T03:25:48Z | MEMBER | null | I've never really been clear on the purpose of the `numpy` argument in to_json. Some digging brought me here https://github.com/pandas-dev/pandas/pull/3876#issuecomment-19390383 where it is explained that this maintains some kind of sequence to elements. To illustrate the only difference I could find
```python
>>> ... | {
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