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https://api.github.com/repos/pandas-dev/pandas/issues/39519 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39519/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39519/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39519/events | https://github.com/pandas-dev/pandas/issues/39519 | 798,007,292 | MDU6SXNzdWU3OTgwMDcyOTI= | 39,519 | BUG: Binary operations (__and__, __or__, etc.) do not take parameter `axis` and fail | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39520 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39520/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39520/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39520/events | https://github.com/pandas-dev/pandas/issues/39520 | 798,031,483 | MDU6SXNzdWU3OTgwMzE0ODM= | 39,520 | BUG: AttributeError: type object 'object' has no attribute 'dtype' with numpy 1.20.x and pandas versions 1.0.4 and earlier | {
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pandas 1.0.3
In ipython ,i try initializing df
`
In [1]: import pandas as pd
In [2]: pd.DataFrame([],columns=['a','b','c'])
AttributeErrorTraceback (most recent call last)
<ipython-input-2-ea4921e768b2> in <module>
----> 1 pd.DataFrame([]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39521 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39521/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39521/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39521/events | https://github.com/pandas-dev/pandas/pull/39521 | 798,057,121 | MDExOlB1bGxSZXF1ZXN0NTY0OTM0NjAy | 39,521 | ⬆️ UPGRADE: Autoupdate pre-commit config | {
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<!-- END pr-commits -->
## Base PullRequest
default branch (https://github.com/pandas-dev/pandas/tree/master)
## Command results
<details>
<summary>Details: </summary>
<details>
<summary><em>add path</em></summary>
```Shell
/home/runner/work/_actions/technote-space/create-pr-action/v2/nod... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39522 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39522/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39522/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39522/events | https://github.com/pandas-dev/pandas/issues/39522 | 798,099,282 | MDU6SXNzdWU3OTgwOTkyODI= | 39,522 | BUG: Wrong legend when combining multiple plots on the same axes | {
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... | open | false | null | [] | null | 6 | 2021-02-01T08:22:52Z | 2021-04-09T07:39:37Z | null | NONE | null | The code
```python
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame([{'x': 1, 'a': 1, 'b': 1}, {'x': 2, 'a': 2, 'b': 3}])
ax = plt.gca()
df.plot('x', 'a', yerr=0.1, ax=ax, label='with errors')
df.plot('x', 'b', ax=ax, label='without errors')
```
results in the following image on my pla... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39523 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39523/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39523/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39523/events | https://github.com/pandas-dev/pandas/issues/39523 | 798,208,922 | MDU6SXNzdWU3OTgyMDg5MjI= | 39,523 | CI upgrade pyupgrade | {
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1. in `.pre-commit-config.yaml`, change the `ref` of `pyupgrade` from v2.7.4 to v2.9.0
2. run `pre-commit run pyupgrade --all-files`
3. run `pre-commit run flake8 --all-files` - there will be lots of errors from unused imports, so you should remove them (or you could look into using [autoflake](http... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39524 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39524/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39524/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39524/events | https://github.com/pandas-dev/pandas/pull/39524 | 798,211,223 | MDExOlB1bGxSZXF1ZXN0NTY1MDYzODc4 | 39,524 | STYLE Upgrade no-string-hints | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39525 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39525/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39525/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39525/events | https://github.com/pandas-dev/pandas/issues/39525 | 798,242,810 | MDU6SXNzdWU3OTgyNDI4MTA= | 39,525 | BUG: Groupby and apply fails quietly for str columns | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
The groupby - apply functionality breaks for string columns if within an apply a n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39526 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39526/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39526/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39526/events | https://github.com/pandas-dev/pandas/pull/39526 | 798,274,607 | MDExOlB1bGxSZXF1ZXN0NTY1MTE3MDIx | 39,526 | CI: pin numpy for CI / Checks github action | {
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https://github.com/pandas-dev/pandas/pull/39517/checks?check_run_id=1803471267
xref #39513 and https://github.com/pandas-dev/pandas/pull/38379#discussion_r567753143
conda-forge should pick up 1.19.5 with these changes. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39527 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39527/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39527/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39527/events | https://github.com/pandas-dev/pandas/issues/39527 | 798,313,632 | MDU6SXNzdWU3OTgzMTM2MzI= | 39,527 | DOC: Example for plotting scatterplot matrices is incomplete | {
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https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html#scatter-matrix-plot
#### Documentation problem
In the above-mentioned documentation, the following code is suggested to build/display a scatterplot matrix:
```
df = pd.DataFrame(np.random.randn(1000,... | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample
```python
from openpyxl import load_workbook
from pandas imp... | {
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I would like to be able to use pd.merge to replace or update the columns in the left dataset if non-key columns with the same names are being merged from the right dataset.
#### Describe the solution you'd like
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https://api.github.com/repos/pandas-dev/pandas/issues/39537 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39537/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39537/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39537/events | https://github.com/pandas-dev/pandas/issues/39537 | 798,542,518 | MDU6SXNzdWU3OTg1NDI1MTg= | 39,537 | Error when converting df to json table (utc timezone date time object causes the error) | {
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and there are datetime.now(timezone.utc) objects in the table it causes the following error (Without orient table it works though.):
`---------------------------------------------------------------------------
AttributeError Trace... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39538 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39538/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39538/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39538/events | https://github.com/pandas-dev/pandas/pull/39538 | 798,579,426 | MDExOlB1bGxSZXF1ZXN0NTY1MzcxNDA2 | 39,538 | CI: Upgrade 'pyupgrade' (v2.7.4 --> v2.9.0) | {
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- [ ] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
------
This PR upgrades `pyupgrade` and also includes style/formatting changes required af... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39539 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39539/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39539/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39539/events | https://github.com/pandas-dev/pandas/pull/39539 | 798,613,800 | MDExOlB1bGxSZXF1ZXN0NTY1Mzk5NjQ4 | 39,539 | [ArrayManager] BUG: fix setitem with non-aligned boolean dataframe | {
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This covers setitem with a boolean dataframe (like ``df[df < 0] = 2``), but specifically fixes the case where the dataframe is not aligned (eg `df[df[:-1] < 0] = 2` in the tests).
`DataFrame.fillna` infers object dtype columns getting f... | {
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"followers_url": "https://api.github.com/users/jre... | 2 | 2021-02-01T19:07:44Z | 2021-02-02T12:54:29Z | 2021-02-01T21:06:45Z | CONTRIBUTOR | null | so the confluence of some pyarrow pinning and release of numpy 1.20 are causing pain rn. several PRs have addressed most of these. I think 38_locale is the remaining problem, needs to pin pyarrow.
We need to get to green on master & 1.2.2 before any other PRs.
cc @pandas-dev/pandas-core | {
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- [ ] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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- [ ] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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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.html#code-standards) for how to run them
- [x] whatsnew entry
This is on top of #39486 | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import numpy as np
import... | {
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take the longest. we should just have this run the database tests only. (so add a marker for the appropriate tests / just run the sql tests entirely). | {
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```
2021-02-02T04:33:27.6929603Z =========================== short test summary info ============================
2021-02-02T04:33:27.6930740Z FAILED ../../venv/lib/python3.7/site-packages/pandas/tests/window/test_pairwise.py:... | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import numpy as np
import... | {
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- [ yes] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
Currently I am working on a project about the extension array, while I have som... | {
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Here is the example
```python
import pandas
for tz in [None, "UTC", "CET"]:
index = pandas.date_range("2018", "2019", tz=tz, closed="left", freq='H')... | {
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Hence, I propose to make the doc a bit more accurate.

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```python
data2016.join(expected_runs, how='left', on='STATE')
```
However, it fails with the message:
```
ValueError: You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat
```
Looking... | {
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The code style guide reads
>
> Imports (aim for absolute)
> ==========================
>
> In Python 3, absolute imports are recommended. Using absolute... | {
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"descript... | closed | false | null | [] | null | 2 | 2021-02-02T19:29:40Z | 2021-02-03T02:30:39Z | 2021-02-03T02:30:39Z | NONE | null | Hi everyone, I was using the .drop_duplicates() function to remove duplicate values from the .csv file, but unfortunately, it removed some non-duplicate values from my table. So what would you recommend me to save non-duplicate values while dropping duplicates from the .csv file using drop_duplicates() function?
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https://api.github.com/repos/pandas-dev/pandas/issues/39563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39563/events | https://github.com/pandas-dev/pandas/issues/39563 | 799,640,002 | MDU6SXNzdWU3OTk2NDAwMDI= | 39,563 | ENH: Styler accepts css-strings input args as well as list of (attr,value) pairs | {
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Currently the `styler` has the ability to `set_table_styles` provided they are characterised with a css-selector and list of attribute value pairs, e.g.
```
styler.set_table_styles([{'selector': 'th', 'props': [('color', 'red'), ('font-size', '1em'), ('font-weig... | {
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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.html#code-standards) for how to run them
- [x] whatsnew entry
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regex (in `str.match` for instance) are sometimes complicated and unintuitive. Shell wildcards, although limited, are easy.
If I want to match all SEED channel codes (max 3 characters) for example that end with 'Z' in a column named `cha_code`, I could do:
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"color": "531... | open | false | null | [] | null | 5 | 2021-02-02T21:20:26Z | 2021-09-02T15:09:19Z | null | MEMBER | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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- [x ] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
df = pd.DataFrame({'a': [1,2,3]})
dtype = pd.api.types.CategoricalDtype([1,2])
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AFAICT several of the existing tests are just wrong, xref #39122 cc @jorisvandenbossche
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**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/2... | {
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scikit-learn have made this move (see [issue](https://github.com/scikit-learn/scikit-learn/issues/17595) and [PR](https://github.com/scikit-learn/scikit-learn/pull/19237/files)), and from https://github.... | {
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This actually started as trying to get the tests passing for `tests/frame/indexing`, but while doing that I needed to make decisions on what the behaviour should be for setitem / loc / iloc assignment (so related other ongoing discussions about this).
Very much a draft, but a go... | {
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```python
>>> import pandas as pd
>>> s = pd.Series(pd.cut([1, 2, 3], 2))
>>> s
0 (0.998, 2.0]
1 (0.998, 2.0]
2 (2.0, 3.0]
dtype: category
Categorie... | {
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- [ ] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
### Code Sample
**Bash**
```git
docker build --tag pandas-parfaitg-env .
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https://api.github.com/repos/pandas-dev/pandas/issues/39582 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39582/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39582/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39582/events | https://github.com/pandas-dev/pandas/pull/39582 | 800,574,446 | MDExOlB1bGxSZXF1ZXN0NTY3MDM3NDM0 | 39,582 | BUG: at/iat __setitem__ failing to cast | {
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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.html#code-standards) for how to run them
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/39583 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39583/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39583/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39583/events | https://github.com/pandas-dev/pandas/issues/39583 | 800,692,281 | MDU6SXNzdWU4MDA2OTIyODE= | 39,583 | BUG: Support keywords in pd.Timestamp.isoformat(), ref.#26131 is stale. | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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... | open | false | null | [] | null | 39 | 2021-02-03T22:59:57Z | 2021-03-31T21:18:00Z | null | NONE | null | - [x] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
- [x] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
- See [this question](https://stackoverflow.com/questions/65927344/accessing-dataframe-wit... | {
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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.html#code-standards) for how to run them
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/39587 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39587/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39587/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39587/events | https://github.com/pandas-dev/pandas/pull/39587 | 800,813,494 | MDExOlB1bGxSZXF1ZXN0NTY3MjM5NTc3 | 39,587 | REGR: do not try to infer the excel type from a workbook object | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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For `Series.eq`, In the doc it says "Equivalent to `series == other`" but it seems not true.
Let me show a simple example.
```python
>>> a = pd.Series([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'])
>>> b = pd.Series([1, np.nan, 1, np.nan], index=['a', 'b', 'd', 'e'])
>>> a.eq(b)... | {
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Followup from #39482 - removed tests are duplicates of `test_readers.test_bad_sheetname_raises`
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`ecosystem`, + `user_guide/index.rst + style.ipynb + visualization.rst`
possibly others.
#### Documentation problem and proposed changes.
**High Level**
Scientific data visualization is not just restricted to charting. Tabular data visualization is important and `Styler`... | {
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URL: https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html#optional-dependencies
File in GitHub: https://github.com/pandas-dev/pandas/blob/master/doc/source/getting_started/install.rst
#### Documentation problem
The list of optional dependencies is curren... | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
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---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
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**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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I could set the index as a column, and then hide the remaining index. This is not ideal, because I'd like to keep the pandas dataframe index formatting (i.e. bolding). Currently, it is possible to left align the columns within dataframes, jus... | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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- [ ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
#### Question about pandas
```python
import pandas
df = pandas.DataFrame({"a":... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39610 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39610/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39610/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39610/events | https://github.com/pandas-dev/pandas/issues/39610 | 802,024,686 | MDU6SXNzdWU4MDIwMjQ2ODY= | 39,610 | BUG: Grouping by frequency doesn't preserve order within each group | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import pandas as pd
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- [ ] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28... | {
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This PR implements `concat` for DataFrames using the ArrayManager, and all tests in `pandas/tests/reshape/` already pass.
Summary of the changes:
* In `internals/concat.py`, I added a `concatenate_block_managers` equivalent for Arra... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39613 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39613/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39613/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39613/events | https://github.com/pandas-dev/pandas/issues/39613 | 802,214,573 | MDU6SXNzdWU4MDIyMTQ1NzM= | 39,613 | BUG: Inconsistency between Period.ordinal and Timestamp.fromordinal() | {
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- [x] I have confirmed this bug exists on the latest version of pandas.
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---
#### Code Sample, a copy-pastable example
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- [ ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
#### Question about pandas
I noticed that indexing with a reversed list works b... | {
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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.html#code-standards) for how to run them
- [ ] whatsnew entry
Fixing a bug I introduced in #37355 | {
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``` python
In [16]: import numpy as np
...: import pandas as pd
...:
...: dtype = pd.CategoricalDtype([str(i) for i in range(5)])
...: arr = pd.Categorical.from_codes(np.random.randint(5, size=20), dtype=d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39617 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39617/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39617/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39617/events | https://github.com/pandas-dev/pandas/issues/39617 | 802,430,170 | MDU6SXNzdWU4MDI0MzAxNzA= | 39,617 | BUG: .query() using uint64 column fails with TypeError "dtype could not be cast" | {
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"description": "Arithmetic, Comparison, ... | closed | false | null | [] | null | 4 | 2021-02-05T19:49:07Z | 2021-02-13T19:59:40Z | 2021-02-13T19:46:31Z | NONE | null | #### Code Sample, a copy-pastable example
```python
import pandas as pd
df = pd.DataFrame({'x': [1,2,3]}, dtype='uint64')
df = df.query('x > 1')
print(df)
```
#### Problem description
```
---------------------------------------------------------------------------
TypeError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/39618 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/39618/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/39618/comments | https://api.github.com/repos/pandas-dev/pandas/issues/39618/events | https://github.com/pandas-dev/pandas/pull/39618 | 802,526,235 | MDExOlB1bGxSZXF1ZXN0NTY4NjU0NzUw | 39,618 | REF: simplify BlockManager.quantile | {
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"followers_url": "https://api.github.com/users/j... | 2 | 2021-02-05T22:52:09Z | 2021-02-08T15:05:15Z | 2021-02-08T13:50:34Z | MEMBER | null | Handle the scalar-qs case early on in DataFrame.quantile, hugely simplifies BlockManager.quantile and to a lesser extent Block.quantile | {
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