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} | 2 | "2021-03-24T21:07:12Z" | "2021-03-29T14:46:12Z" | "2021-03-29T14:42:30Z" | MEMBER | null | We'll be able to cache more aggressively following each of #35417, #40574, and #40263 | {
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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
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Will follow up by looking into #37506 so that the `skipna=False` case can also be handled correctly. | {
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I spent quite a bit of time trying to figure out what this message means:
`*** ValueError: cannot reindex from a duplicate axis`
#### Describe the solution you'd like
It would have been much easier for me to figure out what I was doing wrong with the message:
`*** ValueError: cannot reindex from an index with duplicate values`
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https://api.github.com/repos/pandas-dev/pandas/issues/40624 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40624/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40624/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40624/events | https://github.com/pandas-dev/pandas/issues/40624 | 840,479,252 | MDU6SXNzdWU4NDA0NzkyNTI= | 40,624 | BUG: Arithmetic operations on 0 length ExtensionArrays aren't tested | {
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} | 1 | "2021-03-25T01:41:01Z" | "2021-07-01T21:41:36Z" | null | NONE | null | pint-pandas includes the arithmetic tests, but had an issue opened for performing addition on a 0 length PintArray. I don't think this is tested in the EA tests.
```
import pint_pandas
import numpy as np
import pint
import pandas as pd
PA_= pint_pandas.PintArray
PT_ = pint_pandas.PintType
ureg=pint.get_application_registry()
data = PA_.from_1darray_quantity(
np.arange(start=1.0, stop=101.0) * ureg.nm
)
s = pd.Series(data)
s.loc[[]] + (1 * ureg.meter) # Untested
``` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/40625 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40625/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40625/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40625/events | https://github.com/pandas-dev/pandas/pull/40625 | 840,532,139 | MDExOlB1bGxSZXF1ZXN0NjAwNDA1MzQz | 40,625 | REF: SingleBlockManager dont subclass BlockManager | {
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} | 1 | "2021-03-25T03:54:12Z" | "2021-04-08T20:57:12Z" | "2021-04-08T20:16:27Z" | MEMBER | null | Instead, most of BlockManager becomes _BlockManager which is subclassed by SingleBlockManager and BlockManager, the latter holding only the 2d-specific BM methods.
Motivation: putting BlockManager constructor in cython gives a much bigger gain if we can define `__cinit__`, and we can't do that with the two subclasses having mismatched `__init__` signatures. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/40626 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40626/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40626/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40626/events | https://github.com/pandas-dev/pandas/issues/40626 | 840,554,057 | MDU6SXNzdWU4NDA1NTQwNTc= | 40,626 | BUG: I got empty Dataframe with index from the summation of empty Dataframe with MultiIndex | {
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] | closed | false | null | [] | null | 1 | "2021-03-25T04:49:03Z" | "2021-03-25T20:25:07Z" | "2021-03-25T20:24:20Z" | NONE | null | I'm not sure that the current behavior is right, so I would like to ask.
When I have a non-empty Dataframe I can use `sum(level=['Project', 'Task''])` to get the MultiIndex Dataframe as my expectation. But when I try to sum the empty Dataframe, I got Index Dataframe instead of MultiIndex Dataframe and It has no index name and column name in there.
Is this the correct behavior or this is a bug. If this is the correct one, do you have any suggestions for me to handle this?
Thank you in advance.
## Code Sample
```python
pd.__version__
# non-empty data
data = pd.DataFrame([(1,1,1,1,1,1),(2,2,2,2,2,2)],columns=('Project', 'Task', 'Increasing Length', 'Start Period', 'Period', 'Value'))
data.set_index(['Project', 'Task', 'Increasing Length', 'Start Period', 'Period'], inplace=True)
sum_data = data.sum(level=['Project', 'Task'])
print(sum_data)
# empty data
empty_data = pd.DataFrame([],columns=('Project', 'Task', 'Increasing Length', 'Start Period', 'Period', 'Value'))
empty_data.set_index(['Project', 'Task', 'Increasing Length', 'Start Period', 'Period'], inplace=True)
# sum of empty data
sum_empty_data = empty_data.sum(level=['Project', 'Task'])
print(sum_empty_data)
# my expectation
expected_sum_empty_data = pd.DataFrame([],columns=('Project', 'Task', 'Value'))
expected_sum_empty_data.set_index(['Project', 'Task'], inplace=True)
print(expected_sum_empty_data)
```
## Expected Output
## Installed Version
python : 3.8.8
pandas : 1.2.3
numpy : 1.20.1
OS: Ubuntu 20.04.1 LTS (docker)
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https://api.github.com/repos/pandas-dev/pandas/issues/40627 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40627/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40627/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40627/events | https://github.com/pandas-dev/pandas/pull/40627 | 840,565,780 | MDExOlB1bGxSZXF1ZXN0NjAwNDMzNzQx | 40,627 | ENH: Addition of input arguments for boundaries to add more consistency between methods | {
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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/40628 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40628/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40628/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40628/events | https://github.com/pandas-dev/pandas/pull/40628 | 840,584,176 | MDExOlB1bGxSZXF1ZXN0NjAwNDQ5NjU0 | 40,628 | ENH: New boundary inputs | {
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- [x] tests added / passed
- [x] closes #40245
- [x] whatsnew entry
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- [X] closes #22144
- [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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] | open | false | null | [] | null | 2 | "2021-03-25T09:15:45Z" | "2021-07-26T20:19:27Z" | null | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version 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/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
import pandas as pd
from scipy.stats import norm
series = pd.Series([2.0, -2.5, pd.NA], dtype=pd.Float64Dtype())
norm.pdf(series)
Traceback (most recent call last):
File "<input>", line 1, in <module>
File "C:\Users\XXX\AppData\Local\pypoetry\Cache\virtualenvs\XXX-w19Rd76b-py3.9\lib\site-packages\scipy\stats\_distn_infrastructure.py", line 1837, in pdf
cond1 = self._support_mask(x, *args) & (scale > 0)
File "C:\Users\XXX\AppData\Local\pypoetry\Cache\virtualenvs\XXX-w19Rd76b-py3.9\lib\site-packages\scipy\stats\_distn_infrastructure.py", line 964, in _support_mask
return (a <= x) & (x <= b)
File "pandas\_libs\missing.pyx", line 360, in pandas._libs.missing.NAType.__bool__
TypeError: boolean value of NA is ambiguous
```
#### Problem description
My issue is about that pandas does not convert a pd.Series with dtype=pd.Float64Dtype() correctly to a numpy array when I try to use the scipy.stats.norm function. Therefore it cannot handle empty values (pd.NA) and the series needs to be cast right now as a float dtype to properly work which is not ideal. It probably has to do with the fact that the method series.to_numpy is called which does not work well with pd.Float64Dtype.
See also [https://github.com/scipy/scipy/issues/13729]
#### Expected Output
array([0.05399097, 0.0175283 , nan])
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 79 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.2
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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---
#### Code Sample, a copy-pastable example
```python
# Your code here
import pandas as pd
pd.read_excel('2a/07AAUFG6881H1ZP_012021_R2A.xlsx',sheet_name='B2B',skiprows=6, engine='openpyxl').shape
Ouput- (24, 24)
```
#### Problem description
There are no empty rows, no change in data has occurred. Somehow, only 24 rows are being read since today. There are 4 more files where same thing is happening
#### Expected Output
Actual shape of data - (92,24)
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python : 3.7.8.final.0
python-bits : 64
OS : Darwin
OS-release : 20.3.0
Version : Darwin Kernel Version 20.3.0: Thu Jan 21 00:07:06 PST 2021; root:xnu-7195.81.3~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.1.2
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.6.0.post20200917
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.20.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : None
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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
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} | 2 | "2021-03-25T16:53:49Z" | "2021-04-03T06:09:46Z" | "2021-04-02T21:37:23Z" | CONTRIBUTOR | null | Added a note to the enhancements section detailing some different upgrades to `Styler` for 1.3.0
If this is not standard or unnecessary just close this PR - I'm only including it in case it is helpful (it is not for self-publication), so I am completely indifferent!
Hopefully there will be one or two more items to add before the end of May.
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] | null | 1 | "2021-03-25T17:07:44Z" | "2021-04-19T23:17:36Z" | null | MEMBER | null | Problem is here:
https://github.com/pandas-dev/pandas/blob/acacff35b1fe87875e2fddccbbadbc1c6834d156/pandas/core/arrays/numpy_.py#L358-L364
Since `na_value` is handled after the dtype conversion, calls like
```
arr = pd.array([pd.NA, 1], dtype="string")
arr.to_numpy(na_value=True, dtype=bool)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/40639 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40639/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40639/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40639/events | https://github.com/pandas-dev/pandas/pull/40639 | 841,254,483 | MDExOlB1bGxSZXF1ZXN0NjAxMDE0MDc1 | 40,639 | DOC array_algos/take method format update | {
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] | null | 1 | "2021-03-25T21:32:13Z" | "2021-04-04T17:14:58Z" | "2021-04-04T17:14:58Z" | CONTRIBUTOR | null | If you could also make `contributing_environment.rst` which includes _both_ Docker instructions as well as non-Docker, and remove `env_outside_docker`, that'd be great, else it can be a follow-up PR
_Originally posted by @MarcoGorelli in https://github.com/pandas-dev/pandas/issues/40130#issuecomment-803026178_ | {
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} | 4 | "2021-03-25T22:08:41Z" | "2021-03-27T07:14:53Z" | "2021-03-26T13:08:09Z" | CONTRIBUTOR | null | The following tests moved from `style/test_style.py` to their own module `style/test_format.py`.
def test_display_format(styler):
def test_format_dict(styler):
def test_format_string(styler): [added new]
def test_format_callable(styler): [added new]
def test_format_with_na_rep():
def test_format_non_numeric_na():
def test_format_clear(styler):
def test_format_escape():
def test_format_escape_na_rep():
def test_format_escape_floats(styler):
def test_format_raises(styler, formatter):
def test_format_with_precision():
def test_format_subset():
The new module does not use `class` setup structure.
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https://api.github.com/repos/pandas-dev/pandas/issues/40644 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40644/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40644/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40644/events | https://github.com/pandas-dev/pandas/pull/40644 | 841,802,153 | MDExOlB1bGxSZXF1ZXN0NjAxNDgyNDEz | 40,644 | DOC: Change user guide style notebook to reST | {
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The downside is, that the downloadable notebook is not as pretty as before (because it contains raw cells with reST code).
Is this something worth the effort?
- [ ] closes #40645
- [ ] 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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} | 3 | "2021-03-26T10:29:27Z" | "2021-03-29T15:55:19Z" | "2021-03-29T15:55:19Z" | CONTRIBUTOR | null | #### Location of the documentation
https://pandas.pydata.org/pandas-docs/stable/user_guide/style.html
#### Documentation problem
The page lacks links to the referenced objects (`DataFrame`, `Series`, ... but most importantly `Styler`).
#### Suggested fix for documentation
Links should be included. This could either be done using [raw reST cells](https://nbsphinx.readthedocs.io/en/0.8.2/raw-cells.html#reST) (which looks not as nice in the downloadable notebook) or by inserting relative links into the markdown code (which breaks easily).
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] | closed | false | null | [] | null | 1 | "2021-03-26T11:01:34Z" | "2021-03-26T23:36:10Z" | "2021-03-26T23:36:10Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version 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/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
import pandas as pd
def test_mask_dataframe():
df = pd.DataFrame(
{
"A": [1, 2, pd.NA],
"B": [4, 5, 6]
}, dtype=pd.Int64Dtype()
)
expected = pd.Series([4, 0, pd.NA], dtype=pd.Int64Dtype(), name="C")
df["C"] = df["B"].mask(df["A"] == 2, 0)
pd.testing.assert_series_equal(expected, df["C"])
E AssertionError: ExtensionArray NA mask are different
E
E ExtensionArray NA mask values are different (33.33333 %)
E [index]: [0, 1, 2]
E [left]: [False, False, True]
E [right]: [False, False, False]
```
Actual output:
```
pd.Series([4, 0, 0], dtype=pd.Int64Dtype(), name="C")
```
#### Problem description
When performing the .mask method on a dataframe, it is expected that a value will be replaced by another value (in this case 0) when the condition result is True. However, when the condition result is pd.NA, it is now also being handled like it is True which is incorrect behaviour. I guess that the same problem happens when using the dataframe.where() method since .mask and .where are linked. It also happens for pd.Float64Dtype().
#### Expected Output
expected = pd.Series([4, 0, pd.NA], dtype=pd.Int64Dtype(), name="C")
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.2
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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} | 3 | "2021-03-26T11:14:24Z" | "2021-05-02T17:16:02Z" | null | NONE | null | #### feature request and related problem
If a table does not exist pd.to_sql is unconditionnally creating it. There are situations, where this is not acceptable.
There are application strategies where this has to be avoided. Eg. in case failed name matching the ISERT might have to fail and signal, that programcode has to be adapted. Such condition arise because of possible changes in the DB model - the outside of python's data environment.
requested option feature for pd.to_sql:
If the table expected by python is not there, it should not be created but the attempted INSERT should fail.
Presently a a certain amount of boilerplate is needed to do such fail-safe handling.
```python
tableName = '...'
schemaName = '...'
dbEngine = ....
# dataframe df is holding the data for target table named in [tableName]
# currently quote some boilerplate is needed to fail safe, if database table does not exist to avoid creating one
if tableExists(tableName):
df.to_sql(tableName, schema=schemaName, con=dbEngine, index=True, if_exists='append')**
print(f"INSERT-I-done ")
else
print(f"INSERT-I-failed: table with expected name [{schemaName}].[{tableName}] does not yet or nomore exist")
```
This missing feature leads to another level of encapsulation in a wrapper class. It would be better to integrate this as a option directly to PANDAS.
#### Describe the proposed solution
Integrate this checking of the outside DB environment into Dataframe.to_sql
Suggested new parameter:
if_not_exists{‘fail’, ‘create’}, default 'fail'
#### API breaking implications
Dataframe.to_sql fails if the table specified by name does not exist in the schema. This should be the default, thus avoiding that dead phantom tables are created, resulting in dead ends off the track of the DB model, once the nomenklatura of the DB model has moved on. Coevolutive and agile development of applications python code and the datamodel and its naming thus should be supported, by failsafe handling of naming assumptions.
present processing still is possible with parameter if_no_exist='create'
Possible the default 'create' might be preferred, as thus it does not break existing code, even though in a greenfield approach I consider 'fail' to be the better choice.
#### Describe alternatives you've considered
Handling outside of Pandas is possible, as shown above. Anyway this results in widespread boilder-plate code and violates the idea of code centralisation and functional encapsulation.
#### Additional context
...
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} | 3 | "2021-03-26T17:49:29Z" | "2021-04-23T17:23:05Z" | "2021-04-23T00:07:08Z" | CONTRIBUTOR | null | - [x] closes #40442
- [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
Prior to this fix, a blank data row after a MultiIndex header was a interpreted as containing a blank index name, but that only works if the user has specified an index column. If index_col is None all subsequent rows should be treated as data, even if the first one is empty. | {
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] | closed | false | null | [] | null | 3 | "2021-03-26T18:24:52Z" | "2021-03-29T15:48:06Z" | "2021-03-29T15:47:58Z" | MEMBER | null | Updates some CSS to better align buttons on the main documentation page. Seems to be an improvement when built locally (I'm using Ubuntu Firefox) but likely worth checking on other platforms / browsers.
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} | 15 | "2021-03-27T00:28:20Z" | "2021-04-21T12:57:52Z" | "2021-04-21T12:39:20Z" | MEMBER | null | Potential first step towards #37493
ASV's (on `N = 5_000_000` instead of `N = 1_000_000` on the added benchmark to get more stable results):
<details>
```
before after ratio
[3a973b6d] [2fa80ad0]
<master> <perf/masked_cummin/max>
- 297±10ms 241±9ms 0.81 groupby.CumminMax.time_frame_transform('Float64', 'cummax')
- 284±6ms 240±7ms 0.85 groupby.CumminMax.time_frame_transform('Float64', 'cummin')
- 761±60ms 393±4ms 0.52 groupby.CumminMax.time_frame_transform('Int64', 'cummax')
- 753±50ms 390±3ms 0.52 groupby.CumminMax.time_frame_transform('Int64', 'cummin')
481±20ms 474±10ms 0.99 groupby.CumminMax.time_frame_transform('float64', 'cummax')
461±10ms 459±10ms 1.00 groupby.CumminMax.time_frame_transform('float64', 'cummin')
706±40ms 732±50ms 1.04 groupby.CumminMax.time_frame_transform('int64', 'cummax')
730±20ms 674±20ms 0.92 groupby.CumminMax.time_frame_transform('int64', 'cummin')
- 685±30ms 214±5ms 0.31 groupby.CumminMax.time_frame_transform_many_nulls('Float64', 'cummax')
- 698±20ms 225±4ms 0.32 groupby.CumminMax.time_frame_transform_many_nulls('Float64', 'cummin')
- 811±50ms 204±6ms 0.25 groupby.CumminMax.time_frame_transform_many_nulls('Int64', 'cummax')
- 804±50ms 207±6ms 0.26 groupby.CumminMax.time_frame_transform_many_nulls('Int64', 'cummin')
444±20ms 447±4ms 1.01 groupby.CumminMax.time_frame_transform_many_nulls('float64', 'cummax')
447±20ms 459±20ms 1.03 groupby.CumminMax.time_frame_transform_many_nulls('float64', 'cummin')
1.41±0.1s 1.33±0.01s 0.94 groupby.CumminMax.time_frame_transform_many_nulls('int64', 'cummax')
1.41±0.09s 1.33±0s 0.94 groupby.CumminMax.time_frame_transform_many_nulls('int64', 'cummin')
```
</details>
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] | open | false | null | [] | null | 4 | "2021-03-27T02:31:40Z" | "2021-10-24T15:54:33Z" | null | NONE | null | I already searched for a while for discussions of nested structures in Pandas, but I couldn't find anything corresponding.
#### Is your feature request related to a problem?
Currently, there is no way to work with arbitrary nested data types in Pandas.
In Spark and PyArrow, one can have StructTypes. In NumPy, we have Compound types.
However, when we try something like this:
```python
df = pd.DataFrame({'pos':[1,2,3], "val": ["a","b", "c"]})
struct = df.to_records(index=False).view(type=np.ndarray, dtype=list(df.dtypes.items()))
pd.Series(struct)
```
Then we only get an error:
```python
ValueError: Cannot construct a Series from an ndarray with compound dtype. Use DataFrame instead.
```
This would be useful for a number of use cases:
- Direct mapping between PySpark and Pandas nested columns
- Easy creation of custom data types; type checking of nested columns
- Efficient serialization with Arrow
#### Describe the solution you'd like
My wish would be to have a generic Pandas StructDType that:
- can be composed of any other Pandas DType
- allows conversion to PyArrow StructType back and forth
- can be written to Parquet
A perfect example is the `IntervalDType`/`IntervalArray` that is already implemented in Pandas:
https://github.com/pandas-dev/pandas/blob/2198f51911dd5a5a0cc1c12c3f083b86c96bd33b/pandas/core/arrays/interval.py#L146
In my opinion, its implementation is a special case of a Struct dtype.
It also supports conversion to and from PyArrow (see https://github.com/pandas-dev/pandas/commit/2198f51911dd5a5a0cc1c12c3f083b86c96bd33b).
Therefore, by generalizing the IntervalDType to use any number of subtypes, we would have the StructDType implementation ready.
#### API breaking implications
`to_csv()`, etc. could have difficulties with storing nested data.
That's maybe a followup problem to solve.
#### Describe alternatives you've considered
One can try to construct the Series as a list of tuples.
However, this has two drawbacks:
- No type checking
- `to_parquet()` fails
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} | 22 | "2021-03-27T06:47:28Z" | "2021-10-07T00:37:01Z" | "2021-10-07T00:36:48Z" | CONTRIBUTOR | null | - [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
Introduces IntpHashMap. Instead of making it from the scratch, we map the functionality either to Int32HashMap or Int64HashMap depending on the plattform. This has the advantage, that the resulting so/pyd-files don't get bigger.
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"color": "5319e7",
"default": false,
"description": "to_sql, read_sql, read_sql_query",
"id": 47232590,
"name": "IO SQL",
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] | closed | false | null | [] | null | 6 | "2021-03-27T07:04:55Z" | "2021-09-08T02:26:22Z" | "2021-09-08T02:26:22Z" | NONE | null | [`pandas.read_sql`](https://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.read_sql.html#pandas.read_sql), [`pandas.read_sql_query`](https://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.read_sql_query.html#pandas.read_sql_query), [`pandas.read_sql_table`](https://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.read_sql_table.html#pandas.read_sql_table), [`DataFrame.to_sql`](https://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.DataFrame.to_sql.html#pandas.DataFrame.to_sql), and [`Series.to_sql`](https://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.Series.to_sql.html#pandas.Series.to_sql) can now accept an [`AsyncEngine`](https://docs.sqlalchemy.org/en/latest/orm/extensions/asyncio.html#sqlalchemy.ext.asyncio.AsyncEngine) or an [`AsyncConnection`](https://docs.sqlalchemy.org/en/latest/orm/extensions/asyncio.html#sqlalchemy.ext.asyncio.AsyncConnection) as a valid argument to `con`.
Example Usage:
```py
import asyncio
from sqlalchemy.ext.asyncio import create_async_engine
engine = create_async_engine('postgresql+asyncpg://anakin:skywalker@localhost/test')
async def sql_operations():
# Accessing a table with the AsyncEngine
umbara = await pd.read_sql('umbara', engine)
# Can alternatively be written as: await pd.read_sql_table('umbara', engine)
# Using an SQL query with the AsyncConnection
async with engine.connect() as conn:
seasons = await pd.read_sql_query('SELECT season6, season5, season7 FROM clonewars', conn)
favs = pd.DataFrame({
'FirstName': ['Mace', 'Obi-Wan', 'Ahsoka'],
'LastName': ['Windu', 'Kenobi', 'Tano']
})
# Writing data with the AsyncEngine
await favs.to_sql('jedi', engine)
asyncio.run(sql_operations())
```
# Check list
- [x] tests added / passed (found a way to do this efficiently and relatively easily, will be pushing soon!)
- [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
# Issue with unit tests
So unfortunately, as far as I can tell, creating unit tests will require that all the current unit tests for the SQL functions/methods will need to be rewritten, since every time the SQL functions/methods are invoked they need to be awaited. One kind of unique idea I have is to read the source code of the existing test functions and add the word `await` whenever one of the SQL functions/methods is called and the use `exec` function to create the new `asyncio` version of the function. Or perhaps there is a better approach I am not familiar with to avoid having to completely rewrite the unit tests for these new use cases. I'm open to any ideas!
Thank you for considering my proposal! ♥ | {
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] | closed | false | null | [] | null | 2 | "2021-03-27T12:18:52Z" | "2021-03-27T16:00:56Z" | "2021-03-27T16:00:56Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
pd.api.types.is_datetime64_dtype("M") # True
pd.api.types.is_timedelta64_dtype("m") # True
```
#### Problem description
The function `pd.api.types.is_datetime64_dtype` returns `True` for the string `"M"`. The function `pd.api.types.is_timedelta64_dtype` returns `True` for the string `"m"`. Is this behavior intentional?
#### Expected Output
`False`.
#### Output of ``pd.show_versions()``
<details>
```
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.3.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : AMD64 Family 23 Model 96 Stepping 1, AuthenticAMD
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Belgium.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : 0.29.22
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.22.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.7
fastparquet : None
gcsfs : None
matplotlib : 3.4.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.53.1
```
</details>
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} | 12 | "2021-03-27T14:23:24Z" | "2021-04-25T16:26:19Z" | "2021-04-25T11:57:19Z" | MEMBER | null | According to https://docs.pytest.org/en/stable/customize.html, using `setup.cfg`as pytest config file is not recommended. So moved everything to `pyproject.toml`
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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 restores behavior to before the regression, but I think also deprecating this behavior while patching might be reasonable. Since categoricals represent all missing values the same way, this allows unintuitive behavior like
```
ser = pd.Series([None, "b"]).astype('category')
ser = ser.replace({np.nan: 'c'})
print(ser)
```
replacing the missing value even though `None` and `np.nan` are different missing values. Forcing usage of the more explicit `fillna` seems more reasonable in this case. | {
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} | 3 | "2021-03-27T18:01:02Z" | "2021-04-01T08:36:18Z" | "2021-04-01T07:15:12Z" | MEMBER | null | - [x] closes #39904
- [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
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} | 1 | "2021-03-27T21:20:45Z" | "2021-03-29T15:51:23Z" | "2021-03-29T14:21:48Z" | MEMBER | null | - [x] closes #32859
- [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
ASV's look unaffected:
<details>
```
before after ratio
[029907c9] [b45f9193]
<master> <bug/rank_datetimelike>
6.90±0.2ms 6.76±0.6ms 0.98 frame_methods.Rank.time_rank('float')
2.63±0.3ms 2.39±0.2ms ~0.91 frame_methods.Rank.time_rank('int')
45.7±1ms 45.3±1ms 0.99 frame_methods.Rank.time_rank('object')
2.47±0.2ms 2.22±0.1ms ~0.90 frame_methods.Rank.time_rank('uint')
10.8±0.09ms 10.8±0.8ms 1.01 series_methods.Rank.time_rank('float')
8.10±0.2ms 8.26±0.3ms 1.02 series_methods.Rank.time_rank('int')
51.3±2ms 51.2±1ms 1.00 series_methods.Rank.time_rank('object')
8.76±0.6ms 8.30±0.2ms 0.95 series_methods.Rank.time_rank('uint')
```
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} | 0 | "2021-03-28T02:46:41Z" | "2021-04-08T22:15:42Z" | "2021-04-08T22:15:42Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, Minimal
The data:
```python
>>> d = pd.DataFrame(
{ "a": [pd.Timedelta(hours=6),pd.Timedelta(hours=7)]
, "b": [12.1,13.3]
})
>>> d
a b
0 0 days 06:00:00 12.1
1 0 days 07:00:00 13.3
>>> d.dtypes
a timedelta64[ns]
b float64
dtype: object
```
The operation with unexpected results:
```python
>>> d.sum(level=0)
b
0 12.1
1 13.3
```
The expected results:
```python
>>> d.sum(level=0)
a b
0 0 days 06:00:00 12.1
1 0 days 07:00:00 13.3
```
#### Code Sample, Real-World
There's no point to summing a level without a multi-index. This example is more serious.
```python
>>> d = pd.DataFrame(
{ "a": [1,1]
, "b": [2,2]
, "c": [4,5]
, "d": [pd.Timedelta(hours=6),pd.Timedelta(hours=7)]
, "e": [12.1,13.3]
})
>>> d = d.set_index(["a","b","c"])
>>> d
d e
a b c
1 2 4 0 days 06:00:00 12.1
5 0 days 07:00:00 13.3
>>> d.dtypes
d timedelta64[ns]
e float64
dtype: object
```
Unexpected results:
```python
>>> d.sum(level=["a","b"])
e
a b
1 2 25.4
```
Expected results:
```python
>>> d.sum(level=["a","b"])
d e
a b
1 2 0 days 13:00:00 25.4
```
#### Problem description
If it can be summed without the `level` argument it should be summed with the `level` argument. At the very least, raise an error rather than dropping the column.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.8.final.0
python-bits : 64
OS : CYGWIN_NT-10.0-19041
OS-release : 3.1.7-340.x86_64
Version : 2020-08-22 17:48 UTC
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 41.2.0
Cython : 0.29.22
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 3 | "2021-03-28T04:13:22Z" | "2021-10-03T14:12:55Z" | "2021-10-03T14:12:55Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
bins = range(0,20,3)
labels = (
# OK:
[ [i for i in bins[:-1]]
, [(i,) for i in bins[:-1]]
, [(i,)*2 for i in bins[:-1]]
, [(i,)*3 for i in bins[:-1]]
, [pd.Timestamp(i) for i in bins[:-1]]
# Not OK:
, [(pd.Timestamp(i),) for i in bins[:-1]]
, [(pd.Timestamp(i),)*2 for i in bins[:-1]]
, [(pd.Timestamp(i),)*3 for i in bins[:-1]]
# OK:
, [(pd.Timestamp(i),i) for i in bins[:-1]]
, [(pd.Timestamp(i),i,i) for i in bins[:-1]]
, [(i,pd.Timestamp(i)) for i in bins[:-1]]
, [(i,i,pd.Timestamp(i)) for i in bins[:-1]]
, [(*(pd.Timestamp(i),)*5,i) for i in bins[:-1]]
, [(*(pd.Timestamp(i),)*5,i,i) for i in bins[:-1]]
, [(i,*(pd.Timestamp(i),)*5) for i in bins[:-1]]
, [(i,i,*(pd.Timestamp(i),)*5) for i in bins[:-1]]
, [(pd.Timestamp(i),i)*2 for i in bins[:-1]]
, [(pd.Timestamp(i),i)*3 for i in bins[:-1]]
])
for label in labels:
try:
pd.cut(range(20), bins, labels=label)
except ValueError:
print("Error:", label, "", sep="\n")
```
#### Traceback
```python
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-2112-25ff621c28d2> in <module>
----> 1 pd.cut(range(20), bins, labels=labels[5])
.../lib/python3.8/site-packages/pandas/core/reshape/tile.py in cut(x, bins, right, labels, retbins, precision, include_lowest, duplicates, ordered)
271 raise ValueError("bins must increase monotonically.")
272
--> 273 fac, bins = _bins_to_cuts(
274 x,
275 bins,
.../lib/python3.8/site-packages/pandas/core/reshape/tile.py in _bins_to_cuts(x, bins, right, labels, precision, include_lowest, dtype, duplicates, ordered)
434 )
435 if not is_categorical_dtype(labels):
--> 436 labels = Categorical(
437 labels,
438 categories=labels if len(set(labels)) == len(labels) else None,
.../lib/python3.8/site-packages/pandas/core/arrays/categorical.py in __init__(self, values, categories, ordered, dtype, fastpath)
366
367 else:
--> 368 codes = _get_codes_for_values(values, dtype.categories)
369
370 if null_mask.any():
.../lib/python3.8/site-packages/pandas/core/arrays/categorical.py in _get_codes_for_values(values, categories)
2524 t = hash_klass(len(cats))
2525 t.map_locations(cats)
-> 2526 return coerce_indexer_dtype(t.lookup(vals), cats)
2527
2528
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.lookup()
ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
```
#### Problem description
Say you are trying to cut a DataFrame:
```python
b = pd.cut(...)
r = d.groupby(b).sum()
```
How do you build the resulting index? Using either the default intervals provided by the cut function or some temporary identifying labels, build the index using lookups on the input dataframe. Merging runs the risk of dropping columns even with `how="left"` and `validate="1:1"`. Concatenation has the same problems assuming the indices are matched. There is no simple way to lookup the value of a matching column given the value of another column (afaik) in the same row. The straightforward approach is to convert the dataframe to a dictionary for lookups and that's tedious.
Or you can just build the index from the input dataframe and pass it to the cut function via the `labels` keyword. And that's **why** the current behaviour is a problem and why it should be fixed.
```python
r.index = pd.MultiIndex.from_tuples(r.index, names=...)
```
#### Aside
As an aside, the documentation for the `labels` parameter is lacking:
```python
labels: array or False, default None
```
It can't accept numpy arrays. It can't accept MultiIndex. It can't accept DataFrame. It can't accept Series, or lists of Series. It can't accept lists of lists. That should be noted. And per my convincing argument above, the list of acceptable types should be expanded.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.8.final.0
python-bits : 64
OS : CYGWIN_NT-10.0-19041
OS-release : 3.1.7-340.x86_64
Version : 2020-08-22 17:48 UTC
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 41.2.0
Cython : 0.29.22
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 8 | "2021-03-28T06:17:23Z" | "2021-04-12T14:27:29Z" | "2021-04-12T14:27:29Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
# works
foo = np.array([1,2,3,4]).reshape(2,2)
bar = np.zeros_like(foo)
np.add(foo, 1, out=bar)
print(bar)
# doesn't work. bar remains an array of zeros
foo = np.array([1,2,3,4]).reshape(2,2)
df = pd.DataFrame(foo)
bar = np.zeros_like(df)
np.add(df, 1, out=bar)
print(bar)
```
#### Problem description
Many numpy functions accept an `out` parameter as a way of storing the result. In the current pandas version (1.2.3), when the numpy function takes in a DataFrame as input, it no longer stores the result to the `out` array.
In pandas 1.0.1 (and earlier, on my other machine), the behavior works as expected. (see Expected Output). I am using numpy==1.19 for both machines.
Curiously, note that this problem is not seen for `pd.Series`. The below code works fine:
```python
foo = np.array([1,2,3,4])
series = pd.Series(foo)
bar = np.zeros_like(series)
np.add(series, 1, out=bar)
print(bar)
```
One workaround is to instead use `np.add(df.values, 1, out=bar)` but I am using several packages that require the older behavior.
#### Expected Output
```python
>>> print(bar)
[[2 3]
[4 5]]
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.7.4.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-1062.1.1.el7.x86_64
Version : #1 SMP Fri Sep 13 22:55:44 UTC 2019
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.2.3
numpy : 1.19.5
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 41.4.0
Cython : 0.29.21
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.11.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.8.2
fastparquet : None
gcsfs : None
matplotlib : 3.1.3
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.13.0
pyxlsb : None
s3fs : 0.5.1
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : 0.8.7
xarray : None
xlrd : 1.2.0
xlwt : None
numba : 0.49.1
</details>
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- [x] I have confirmed this bug exists on the latest version of pandas.
---
#### Code Sample, a copy-pastable example
```python
import pandas as pd
df = pd.DataFrame(columns=['a', 'b'], index=range(6))
# Slicings that work
df[::2] = 1
df['a'][::2] = 'a'
df[1::2] = 2
df['a'][1::2] = 'c'
# Slicing that does not work
df[['a','b']][1::2] = 'aha'
```
#### Problem description
The last slicing does not work (Dataframe is not modified), and no error message is issued.
I could check that it works with `pd.IndexSlice`.
At least an error message should be raised.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.8.0-48-generic
Version : #54~20.04.1-Ubuntu SMP Sat Mar 20 13:40:25 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : fr_FR.UTF-8
LOCALE : fr_FR.UTF-8
pandas : 1.2.3
numpy : 1.18.5
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : 0.29.22
pytest : 6.2.2
hypothesis : None
sphinx : 3.5.3
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 0.8.7
fastparquet : 0.5.0
gcsfs : None
matplotlib : 3.3.4
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 2.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : 1.3.23
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.51.2
</details>
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- [ x ] tests added / passed
- [ x ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ x ] whatsnew entry updated in docs
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] | closed | false | null | [] | null | 2 | "2021-03-28T18:12:52Z" | "2021-03-28T21:47:52Z" | "2021-03-28T21:47:52Z" | CONTRIBUTOR | null | #### Location of the documentation
Trivial typo fix of `min_periods` from `min_peridos` in the Overview of the [Windowing](https://pandas.pydata.org/docs/user_guide/window.html) User Guide section.
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Fixes Issue #40666 | {
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} | 2 | "2021-03-28T18:49:43Z" | "2021-03-29T14:39:59Z" | "2021-03-29T13:09:14Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] 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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] | open | false | null | [] | null | 2 | "2021-03-28T19:34:29Z" | "2021-03-30T01:25:59Z" | null | NONE | null | In `DataFrame._reduce` are there reasons not to have `try/except` clauses around this conversion?
https://github.com/pandas-dev/pandas/blob/029907c9d69a0260401b78a016a6c4515d8f1c40/pandas/core/frame.py#L9581-L9584
Like you have here:
https://github.com/pandas-dev/pandas/blob/029907c9d69a0260401b78a016a6c4515d8f1c40/pandas/core/frame.py#L9609-L9613
Because then you have issues like this, which are very common in `groupby` (I mean empty DataFrames are common):
``` python
pd.DataFrame(columns=["Duration"], dtype="timedelta64[ns]").sum(skipna=False)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-2442-dd5151a2feed> in <module>
----> 1 pd.DataFrame(columns=["Duration"], dtype="timedelta64[ns]").sum(skipna=False)
.../lib/python3.8/site-packages/pandas/core/generic.py in sum(self, axis, skipna, level, numeric_only, min_count, **kwargs)
11069 **kwargs,
11070 ):
> 11071 return NDFrame.sum(
11072 self, axis, skipna, level, numeric_only, min_count, **kwargs
11073 )
.../lib/python3.8/site-packages/pandas/core/generic.py in sum(self, axis, skipna, level, numeric_only, min_count, **kwargs)
10789 **kwargs,
10790 ):
> 10791 return self._min_count_stat_function(
10792 "sum", nanops.nansum, axis, skipna, level, numeric_only, min_count, **kwargs
10793 )
.../lib/python3.8/site-packages/pandas/core/generic.py in _min_count_stat_function(self, name, func, axis, skipna, level, numeric_only, min_count, **kwargs)
10771 name, axis=axis, level=level, skipna=skipna, min_count=min_count
10772 )
> 10773 return self._reduce(
10774 func,
10775 name=name,
.../lib/python3.8/site-packages/pandas/core/frame.py in _reduce(self, op, name, axis, skipna, numeric_only, filter_type, **kwds)
8855 # Even if we are object dtype, follow numpy and return
8856 # float64, see test_apply_funcs_over_empty
-> 8857 out = out.astype(np.float64)
8858 return out
8859
.../lib/python3.8/site-packages/pandas/core/generic.py in astype(self, dtype, copy, errors)
5875 else:
5876 # else, only a single dtype is given
-> 5877 new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
5878 return self._constructor(new_data).__finalize__(self, method="astype")
5879
.../lib/python3.8/site-packages/pandas/core/internals/managers.py in astype(self, dtype, copy, errors)
629 self, dtype, copy: bool = False, errors: str = "raise"
630 ) -> "BlockManager":
--> 631 return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
632
633 def convert(
.../lib/python3.8/site-packages/pandas/core/internals/managers.py in apply(self, f, align_keys, ignore_failures, **kwargs)
425 applied = b.apply(f, **kwargs)
426 else:
--> 427 applied = getattr(b, f)(**kwargs)
428 except (TypeError, NotImplementedError):
429 if not ignore_failures:
.../lib/python3.8/site-packages/pandas/core/internals/blocks.py in astype(self, dtype, copy, errors)
671 vals1d = values.ravel()
672 try:
--> 673 values = astype_nansafe(vals1d, dtype, copy=True)
674 except (ValueError, TypeError):
675 # e.g. astype_nansafe can fail on object-dtype of strings
.../lib/python3.8/site-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy, skipna)
1061 return arr.astype(TD64NS_DTYPE, copy=copy)
1062
-> 1063 raise TypeError(f"cannot astype a timedelta from [{arr.dtype}] to [{dtype}]")
1064
1065 elif np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer):
TypeError: cannot astype a timedelta from [timedelta64[ns]] to [float64]
```
And I don't think one should depend on the the undocumented behavior of a negative `min_count` to bypass that coercion while guaranteeing the same output as if `min_count` were 0.
https://github.com/pandas-dev/pandas/blob/029907c9d69a0260401b78a016a6c4515d8f1c40/pandas/core/frame.py#L9560
Especially with code like:
https://github.com/pandas-dev/pandas/blob/029907c9d69a0260401b78a016a6c4515d8f1c40/pandas/core/nanops.py#L1435
This stackoverflow question, [Sum Empty DataFrame without Converting to Incompatible Type](https://stackoverflow.com/q/66845001/2626865) goes into more detail. | {
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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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] | open | false | null | [] | null | 8 | "2021-03-29T00:45:06Z" | "2021-04-02T21:13:09Z" | null | NONE | null | - [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the latest version of pandas.
- present in v1.2.3
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import pandas as pd
import numpy as np
df = pd.DataFrame({
'A' : np.random.normal(10, 12, size=(100, ))
})
# function to cyclically group with a frequency of 4
def grouper(index):
return index % 4
store = {}
# debuging apply function to store the dataframe chunks created by the grouper
# also contains print statements to identify the error
def addstore(df):
key = df.index.min()
if len(store.keys()) > 0:
firstkey = list(store.keys())[0]
print(f'{key:19d} {firstkey:19d} {store[firstkey].index.min():19d} {firstkey == store[firstkey].index.min()!s:6s}')
else:
print('New key', key)
print(f'{"New Key":19s} {"First Key":19s} {"Stored Index":19s} {"Valid":19s}')
# attempting to copy dataframe
store[key] = pd.DataFrame(df).copy(deep=True)
df.groupby(grouper).apply(addstore)
```
A more detailed example with integer and datetime indices can be found here: https://gist.github.com/dakenblack/41595c831def6d06e289f87d015aca5e
#### Problem description
Between calls of the apply function (getstore) the copied dataframe changes. If a copy is created, the copy should be independant of the original dataframe.
#### Found Output
```
New key 0
New Key First Key Stored Index Valid
1 0 1 False
2 0 2 False
3 0 3 False
```
#### Expected Output
```
New key 0
New Key First Key Stored Index Valid
1 0 0 True
2 0 0 True
3 0 0 True
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.7.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.21343
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.2.3
numpy : 1.18.5
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.2.0.post20200714
Cython : 0.29.21
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.3.3
lxml.etree : 4.5.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.20.0
pandas_datareader: None
bs4 : 4.8.0
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : None
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : 1.3.13
tables : None
tabulate : 0.8.9
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : None
</details>
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] | open | false | null | [] | null | 2 | "2021-03-29T04:32:52Z" | "2021-04-16T20:00:15Z" | null | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version 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/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
df = pd.DataFrame([1.], columns=[0])
pd.read_json(df.to_json(orient="table"), orient="table")
```
#### Problem description
The returned DataFrame will be all `NaN` without exception or warning.
If the value is int as well (e.g., `df = pd.DataFrame([1], columns=[0])`, a `ValueError` is raised instead. The error message was not clear ("Cannot convert non-finite values (NA or inf) to integer"), but it's still better than returning a DataFrame with wrong values.
`NaN` is set during the call of `pd.read_json`.
#### Expected Output
Based on https://github.com/pandas-dev/pandas/issues/19129, it looks like numeric column names are not allowed in the first place. I think an exception is needed rather than setting `NaN`, which makes the debugging difficult.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : 9d598a5e1eee26df95b3910e3f2934890d062caa
python : 3.7.9.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : None.None
pandas : 1.2.1
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : 0.29.22
pytest : 6.2.2
hypothesis : None
sphinx : 3.5.2
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : 4.6.2
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.20.0
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.3.2
fsspec : 0.8.3
fastparquet : None
gcsfs : None
matplotlib : 3.3.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.6
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : 0.4.2
scipy : 1.6.1
sqlalchemy : 1.3.23
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.2
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.52.0
</details>
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] | closed | false | null | [] | null | 0 | "2021-03-29T08:33:36Z" | "2021-10-23T12:20:07Z" | "2021-10-23T12:19:57Z" | CONTRIBUTOR | null | ### PR Tracking
- [x] copy mechanics (#42187)
- [x] clear mechanics (#42271)
- [x] export mechanics (#43318)
- [x] use mechanics (#43318)
# Post
The 4 methods attached to Styler have weakly defined purposes and implementation. Some recent PRs have sought to address this
[#40664 and #39975] but none go all the way.
So lets define a purpose:
- `export` and `use` are designed to work together to transfer all **non-data dependent** styles from one Styler to another.
- `copy` aims to recreate a new Styler object which contains the same data and styles as the original.
- `clear` only operates on a single instance and seeks to set it to a default state.
How does this work in practice with the different Styler attributes:
### Non-Ambiguous Attributes
#### Fully Data Dependent: should be copied but *not* exported.
- **Tooltips**
- **set_td_classes** and **cell_context**
- **hidden_columns**, **hidden_rows**
- **format** (the format method maps formatting functions to the data internally)
#### Non-Data Dependent: should be copied *and* exported
- **hide_index_**, **hide_columns_**:
- **hidden_header** (future development)
- **table_attributes**
### Ambiguous Attributes
- **apply** and **applymap** and **_todo**: should be copied **and** exported. The user must deal with data dependency, since they have optionally introduced it.
The `apply` and `applymap` methods operate by default in a non-data dependent way and optionally become data dependent when the `subset` argument is used or if the functions given are somehow data dependent themselves.
- **table_styles**: should be copied **and** exported. The user must deal with data dependency.
Table styles provide a generic non-data dependent way of adding styles. It can also be data dependent when the CSS selectors target specific rows or colums that might depend on the data. For consistency we include in export and make the user deal with data dependency. (Since Tooltips add table styles dynamically at render time this will not be exported.)
- **uuid**: is ~~not copied~~ **copied and not exported**
~~The uuid is an attribute designed specifically to avoid CSS clashes. It is preferable to have 2 objects with different uuids, and potentially erroneous for them to have the same, therefore we avoid **copying** or **exporting** the uuid.~~
**edit 14-august-2021**: In order to use `to_html` with args without impacting the `styler` we must be able to fully copy a `styler` including uuid: see #43034. Therefore this is copied.
- **caption**: is copied and **not** exported.
A caption is usually data-dependent, although not necessarily hence not exported.
### Clearing
Some attributes can be provided at class instantiation, so "clearing" a Styler could be seen as reseting to these values. In order to do this, the instantiation variables need to be saved, which is unnecessary overhead. Another interpretation is that the Styler instantiation is rarely called specifically with args, and these can be seen as syntactic sugar for, instead calling a default Styler and then immediately applying the relevant modifiers.
Weighing these arguments it seems best to `clear` a Styler back to its default instantiation without any applied arguments.
The most thorough and future proof clearing method might be to re-instantiate a new object, with default inputs:
```
def clear(self):
return Styler(self.data)
````
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] | open | false | null | [] | null | 5 | "2021-03-29T10:10:41Z" | "2021-08-19T03:06:04Z" | null | NONE | null | #### Is your feature request related to a problem?
_I wish I could use pandas to_ drop NaN values using a threshold that is a fraction of the total column/row, not an absolute number. See detailed example below.
#### Describe the solution you'd like
**thresh** : int or float, optional
Where int, requires that many non-NA values and where float, require that fraction of non-NA values.
#### API breaking implications
Only needs to extend it to accept floats as well as ints.
#### Describe alternatives you've considered
None. IMHO this solution is too simple and effective to consider other options.
#### Additional context
##### Example
```python
import numpy as np
import pandas as pd
import missingno as msno
X = pd.DataFrame(
{
'ones': np.ones(50),
'rand': np.random.normal(size=50),
'linear': np.linspace(1, 50),
}
)
y = 3 * np.sin(X.linear) + X.ones + X.rand
y = y.rename('sin_target')
X.loc[4:10, 'ones'] = np.nan
X.loc[4:20, 'rand'] = np.nan
X.loc[40:45, ['linear', 'ones', 'rand']] = np.nan
y.loc[23:25] = np.nan
Xy = pd.concat([X, y], axis=1)
msno.matrix(Xy)
```
```python
Xy_t = Xy.dropna(thresh=0.7 * len(Xy), axis=1)
# Proposed: Xy_t = Xy.dropna(thresh=0.7, axis=1)
msno.matrix(Xy_t)
```
```python
Xy_t = Xy.dropna(thresh=0.4 * Xy.shape[1], axis=1)
# Proposed: Xy_t = Xy.dropna(thresh=0.4, axis=1)
msno.matrix(Xy_t)
```
It should be obviously that this is very useful in cases where the df axis size is liable to change, and where using piped functionality (saves the extra line of code calculating `thresh_int = 0.4 * Xy.shape[1]`). | {
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} | 1 | "2021-03-29T12:13:47Z" | "2021-04-01T12:35:05Z" | "2021-03-29T13:52:08Z" | MEMBER | null | #35259 added dtype parameterisation to existing tests in pandas/tests/arrays/string_/test_string.py and xfailed for ArrowStringArray where needed.
test_astype_float and test_fillna_args were later added in #37974 and #37987 respectively.
This PR doesn't fix (although will be looking at the all the xfailed tests in this module shortly, https://github.com/pandas-dev/pandas/issues/35169#issuecomment-727217462) just xfails to reduce the diff (slightly) for #39908 | {
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} | 1 | "2021-03-29T12:32:30Z" | "2021-04-09T11:58:42Z" | "2021-03-29T13:50:04Z" | MEMBER | null | follow-up to #35259, xref https://github.com/pandas-dev/pandas/issues/35169#issuecomment-727217462 | {
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} | 4 | "2021-03-29T13:56:47Z" | "2021-04-01T14:45:00Z" | "2021-04-01T13:35:41Z" | MEMBER | null | aim to reduce diff to address https://github.com/pandas-dev/pandas/pull/39908#discussion_r585573328, but good to do as follow-up to #35259 anyway.
This also includes a change to inference, which could be broken off if not wanted as part of a TST PR.
more tests to change once fixture in play and also some parameterisation to add for the str accessor testing (which could be a precursor with xfails for ArrowStringArray or combined with PR that adds the accessor.. will open a draft shortly for discussion) | {
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} | 19 | "2021-03-29T16:18:42Z" | "2021-08-19T21:53:25Z" | null | CONTRIBUTOR | null | #### Location of the documentation
https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
#### Potential Cheat Sheet Improvements
Per discussion at https://github.com/pandas-dev/pandas/pull/39806#pullrequestreview-590105681 , add a third page to the cheat sheet:
- More visualization examples that use pandas plotting (no dependence on third party libraries)
- List of frequently used options shown here: https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html#frequently-used-options
- I/O: A whole section showing a variety of popular IO usage (CSV, Excel, SQL, HTML), and also output file formats (feather, parquet, HDF)
- An Apply Functions section
- The new Extension Types (String, Integer, Float) and how pd.NA works
- Anything else that could fill up the space (if needed)
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} | 0 | "2021-03-29T17:09:02Z" | "2021-03-31T14:17:13Z" | "2021-03-31T12:57:39Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] 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
only real perf impact is one case where we currently do a complex->object->complex cast that this removes
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} | 4 | "2021-03-29T21:47:13Z" | "2021-09-04T14:33:26Z" | "2021-09-04T14:33:26Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version 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/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```py
# Your code here
from sqlalchemy import create_engine, Table, Column, Integer, String
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
import pandas as pd
import sqlalchemy as sa
BaseModel = declarative_base()
class Test(BaseModel):
__tablename__ = "test"
id = Column(Integer, primary_key=True)
foo = Column(String(50))
engine = create_engine("sqlite:///")
BaseModel.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
df = pd.DataFrame({"id": [0, 1], "foo": ["hello", "world"]})
df.to_sql("test", con=engine, index=False, if_exists="replace")
session.commit()
foo = session.query(Test.id, Test.foo)
df = pd.DataFrame(foo)
session.close()
print(df)
assert list(df.columns) == ["id", "foo"]
```
#### Problem description
Coping from https://github.com/sqlalchemy/sqlalchemy/issues/6154.
In sqlalchemy 1.4 `Query` returns `Row` objects that are no longer subclass of tuple, so they don't pass the `is_named_tuple` check, as mentioned by Mike here https://github.com/sqlalchemy/sqlalchemy/issues/6154#issuecomment-809441845
#### Expected Output
The colums are named `0,1` instead of `'id', 'foo'`
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.21337
machine : AMD64
processor : Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 1.2.3
numpy : 1.19.2
pytz : 2019.3
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : None
pytest : 6.2.1
hypothesis : None
sphinx : 3.5.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : 0.9.3
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : 2.10.3
IPython : 7.14.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 1.4.4 (actually master)
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.52.0
</details>
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} | 1 | "2021-03-29T21:55:04Z" | "2021-04-09T20:08:50Z" | "2021-04-08T22:15:43Z" | MEMBER | null | - [x] closes #40660
- [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
stumbled accross this one | {
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} | 3 | "2021-03-29T22:15:16Z" | "2021-06-08T16:29:49Z" | "2021-03-30T13:17:57Z" | MEMBER | null | - [x] closes #40397
- [x] tests added / passed
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This will also un-block making a .pyi for lib.pyx | {
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] | open | false | null | [] | null | 2 | "2021-03-29T23:49:33Z" | "2021-04-03T23:26:41Z" | null | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
# Your code here
import pandas as pd
from decimal import Decimal
# from pandas.tests.extension.decimal import DecimalArray
df = pd.DataFrame({
'idx': [0, 1],
'x': [Decimal('8.68'), Decimal('42.23')],
'y': [Decimal('7.11'), Decimal('79.61')],
# 'x': DecimalArray([Decimal('8.68'), Decimal('42.23')]),
# 'y': DecimalArray([Decimal('7.11'), Decimal('79.61')]),
})
print(df.groupby("idx", sort=True).agg('idxmin'))
# Empty DataFrame
# Columns: []
# Index: [0, 1]
```
#### Problem description
When a column contains `Decimal` objects, the `idxmin` and `idxmax` aggregations return empty output.
#### Expected Output
The expected output is
```
x y
idx
0 0 0
1 1 1
```
If I uncomment the commented lines in the above example (i.e. place the `Decimal` objects inside a `DecimalArray`), it works, but AFAICT that isn't really part of the intended public pandas API. Moreover, the issue is not exclusively due to singleton groups: I can also reproduce it using the following DataFrame:
```
df = pd.DataFrame({
'idx': [0, 1, 0, 1],
'x': [Decimal('8.68'), Decimal('42.23'), Decimal('8.69'), Decimal('42.24')],
'y': [Decimal('7.11'), Decimal('79.61'), Decimal('7.12'), Decimal('79.62')],
})
```
I don't think this is related to #39098 because this only occurs for `idxmin` or `idxmax`, not aggregations like `sum`. That is the only obviously related issue I could find.
#### Output of ``pd.show_versions()``
<details>
I've tested on two separate systems.
**Docker Ubuntu container (running on a host Ubuntu machine)**
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.7.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-76-generic
Version : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : 0.29.22
pytest : 6.2.2
hypothesis : 6.3.4
sphinx : 3.5.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.7
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.1
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.53.0
**conda Python on a Mac**
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.2.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Tue Jan 12 22:13:05 PST 2021; root:xnu-6153.141.16~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.6.0.post20210108
Cython : 0.29.22
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 2 | "2021-03-29T23:52:06Z" | "2021-08-27T02:40:03Z" | null | NONE | null | #### Is your feature request related to a problem?
As of SQLAlchemy 1.4, there is a new syntax available that will become the only syntax in version 2.0+. Pandas uses SQLAlchemy for performing SQL IO, particularly in ``DataFrame.to_sql`` and ``pd.read_sql`` (via ``pd.read_sql_query`` and ``pd.read_sql_table``). This usage is not compatible with the new SQLAlchemy syntax.
#### Describe the solution you'd like
Upgrade Pandas SQLAlchemy code to be compatible with the new 1.4+/2.0+ syntax. [An official guide for how to do so in a test-driven fashion is available here.](https://docs.sqlalchemy.org/en/14/changelog/migration_20.html) Note that at least the following 2.0+ incompatibility warnings are issued (though this list is by no means exhaustive):
```
.../pandas/io/sql.py:1313: RemovedIn20Warning: The MetaData.bind argument is deprecated and will be removed in SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: http://sqlalche.me/e/b8d9)
meta = MetaData(self.connectable, schema=schema)
.../pandas/io/sql.py:1103: RemovedIn20Warning: The MetaData.bind argument is deprecated and will be removed in SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: http://sqlalche.me/e/b8d9)
meta = MetaData(self.pd_sql, schema=schema)
.../sqlalchemy/sql/schema.py:939: RemovedIn20Warning: The ``bind`` argument for schema methods that invoke SQL against an engine or connection will be required in SQLAlchemy 2.0. (Background on SQLAlchemy 2.0 at: http://sqlalche
.me/e/b8d9)
bind = _bind_or_error(self)
.../pandas/io/sql.py:1612: RemovedIn20Warning: The Connection.connect() method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. (Background on SQLAlchemy 2.0 at: http://sqlalche.me/e/b8d9)
with self.connectable.connect() as conn:
```
#### API breaking implications
The upgrade to the 2.0+ syntax is not backwards compatible, and even the upgrade to 1.4 may require some changes (though it is primarily an incremental step from 1.3). Since the range of SQLA features used by Pandas is limited, there should be little difficulty in supporting both >=2.0 (and hence also ~=1.4) and <=1.3.
#### Describe alternatives you've considered
The alternative is to pin ``sqlalchemy<=2.0``, or to stop using the Pandas SQL IO functions.
#### Additional context
[The guide linked above](https://docs.sqlalchemy.org/en/14/changelog/migration_20.html) shows how to discover SQLA compatibility issues, and then how to tweak the test suite to ensure that no issues are later introduced. Note that many of these upgrades are simple fixes (using ``connection.execute`` instead of ``engine.execute``, not binding an ``Engine`` into a ``MetaData`` instance, not calling ``Connection.connect``, etc.) and that most are backwards-compatible with recent versions of SQLA. | {
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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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} | 2 | "2021-03-30T03:35:08Z" | "2021-03-31T01:04:25Z" | "2021-03-31T01:01:49Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] 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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] | open | false | null | [] | null | 4 | "2021-03-30T07:58:34Z" | "2021-03-31T11:31:52Z" | null | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version 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
import numpy as np
frame = pd.DataFrame( np.arange(9).reshape( (3, 3) ), index=['a', 'c', 'd'], columns=['Caladan', 'Corrin', 'Ix'] )
"""
Caladan Corrin Ix
a 0 1 2
c 3 4 5
d 6 7 8
"""
frame.reindex(index=['a','b','c','d'],columns=["Caladan","CZ","Ix"],method="ffill")
"""
comment: this is OK
Caladan CZ Ix
a 0 NaN 2
b 0 NaN 2
c 3 NaN 5
d 6 NaN 8
"""
frame.reindex(index=['a','b','c','d'],columns=["Caladan","DZ","Ix"],method="ffill")
"""
comment: OK this is weird...
Caladan DZ Ix
a 0 1 2
b 0 1 2
c 3 4 5
d 6 7 8
"""
frame.reindex(index=['a','b','c','d'],columns=["Caladan","TZ","Ix"],method="ffill")
"""
comment: wat?
Caladan TZ Ix
a 0 2 2
b 0 2 2
c 3 5 5
d 6 8 8
"""
```
#### Problem description
`DataFrame.reindex`, when changing columns labeling, if column name is unknown it should not fill that column, even though it does. Besides, it has different behaviors depending on the new column name, which is even stranger.
#### Expected Output
New column not filled; same behavior when varying the name of new column/s.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : 7d32926db8f7541c356066dcadabf854487738de
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.72-microsoft-standard-WSL2
Version : #1 SMP Wed Oct 28 23:40:43 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.13.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 1 | "2021-03-30T08:25:53Z" | "2021-03-30T15:28:44Z" | "2021-03-30T13:57:33Z" | CONTRIBUTOR | null | small fixes to the previous doc edits:
1 spell correction.
1 uncomment and add an extra cell for clarity.
2 move creation of internal classes to relevant section.
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] | closed | false | null | [] | null | 7 | "2021-03-30T12:53:20Z" | "2021-08-19T03:35:16Z" | "2021-08-19T03:35:16Z" | NONE | null | **Problem**
It is well-documented that the default data frame is not the most size efficient. To do that we have to manually convert each column to their respectively smallest datatype possible.
This will involve the conversion of categorical and downsizing of integers & floats as stated in pandas [documentation](https://pandas.pydata.org/pandas-docs/stable/user_guide/scale.html#use-efficient-datatypes).
**Solution**
I am wondering if it makes sense to create a new function to automatically convert/scale down all the columns in a dataframe to its most efficient. Something as simple as below.
```python
import pandas as pd
df_optimzied = pd.optimize(df)
```
I will be willing to implement this feature as a pull request if it is something the maintainers value. At least, I feel it is something our team will use frequently. | {
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} | 0 | "2021-03-30T16:14:38Z" | "2021-03-31T01:08:56Z" | "2021-03-31T01:05:50Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] 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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- [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/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
The code I'm using is the following:
#### Code Sample, a copy-pastable example
```python
DeathURL = 'https://www.dshs.texas.gov/coronavirus/TexasCOVID19DailyCountyFatalityCountData.xlsx'
TxDeath = pd.read_excel(DeathURL, engine='openpyxl', sheet_name='Fatalities by County')
TxDeath.shape
```
The output is:
```
/Users/rgrasmus/anaconda3/lib/python3.7/site-packages/openpyxl/styles/stylesheet.py:221: UserWarning: Workbook contains no default style, apply openpyxl's default
warn("Workbook contains no default style, apply openpyxl's default")
(0,1)
```
#### Problem description
I am trying to read an online excel .xlsx file that is updated daily via Pandas (version 1.0.5) with openpyxl engine (version 3.0.7). Before updating Pandas and xlrd recently, the file loaded appropriately. Currently, it is raising a warning that openpyxl is applying a default stylesheet and the Dataframe that loads is only the first cell of the worksheet instead of the whole worksheet.
#### Expected Output
I am expecting Pandas to load a ~388x259 worksheet.
I have tested openpyxl directly and it seems to load the entire worksheet:
```python
import openpyxl
import requests
DeathURL = 'https://www.dshs.texas.gov/coronavirus/TexasCOVID19DailyCountyFatalityCountData.xlsx'
resp=requests.get(DeathURL)
output = open('test.xlsx', 'wb')
output.write(resp.content)
output.close()
TxD = openpyxl.load_workbook('test.xlsx')
TxDSheet = TxD.active
print(TxDSheet.max_column)
print(TxDSheet.max_row)
```
Output from the above:
```
388
259
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.7.final.0
python-bits : 64
OS : Darwin
OS-release : 20.3.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.0.5
numpy : 1.18.5
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : 0.29.22
pytest : 6.2.2
hypothesis : None
sphinx : 3.5.3
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fastparquet : None
gcsfs : None
lxml.etree : 4.6.3
matplotlib : 3.3.4
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 6.2.2
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : 1.3.23
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
xlsxwriter : 1.3.7
numba : 0.53.1
</details>
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#### Code Sample, a copy-pastable example
```python
In [1]: import pandas as pd
In [2]: pdf = pd.DataFrame({'a' : [2, 2, 1, 1, 6], 'b' : [2, 2, 1, 1, 3]})
In [3]: pdf.groupby('a').agg(['sum'])
Out[3]:
b
sum
a
1 2
2 4
6 3
In [4]: pdf.groupby('a').agg(['cumsum'])
Out[4]:
b
cumsum
0 2
1 4
2 1
3 2
4 3
In [5]: pdf.groupby('a').agg(['cumsum', 'sum'])
Out[5]:
b
cumsum sum
0 2.0 NaN
1 4.0 2.0
2 1.0 4.0
3 2.0 NaN
4 3.0 NaN
6 NaN 3.0
```
#### Problem description
When both scan aggregrations (cumsum, cummin, cummax, cumcount) and any of reduction aggregartions (sum, min, max, prod, ...), are passed to `groupby.agg` , output value mapping to index in the result is wrong.
scan aggregations produce index as RangeIndex (0 to N-1).
reduction aggregations usually map to grouped keys. In the given example, it maps to values of keys in resulting index.
#### Expected Output
Common method to align the output should be decided and implemented.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.7.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-137-generic
Version : #141-Ubuntu SMP Fri Feb 19 13:46:27 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.19.2
pytz : 2020.4
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.6.0.post20201009
Cython : 0.29.22
pytest : 6.2.2
hypothesis : 6.8.1
sphinx : 3.5.3
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.21.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : 0.8.7
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.1
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.52.0
</details>
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"title": "1.3",
"updated_at": "2021-08-25T20:34:06Z",
"url": "https://api.github.com/repos/pandas-dev/pandas/milestones/80"
} | 4 | "2021-03-31T06:28:03Z" | "2021-04-05T17:26:16Z" | "2021-04-05T16:22:13Z" | MEMBER | null | - [x] closes #38523
- [x] closes #38787
- [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
Essentially https://github.com/pandas-dev/pandas/pull/38737 but targeted for 1.3 as it appears that the current behavior is largely unexpected | {
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https://api.github.com/repos/pandas-dev/pandas/issues/40702 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40702/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40702/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40702/events | https://github.com/pandas-dev/pandas/issues/40702 | 846,035,711 | MDU6SXNzdWU4NDYwMzU3MTE= | 40,702 | ENH: Having rolling accepts pd.IntervalIndex on a sorted datetime column | {
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] | closed | false | null | [] | null | 1 | "2021-03-31T06:57:23Z" | "2021-05-01T09:13:12Z" | "2021-04-30T21:30:27Z" | NONE | null | #### Describe the solution you'd like
It is currently possible to define custom window rolling as explained in [documentation](https://pandas.pydata.org/pandas-docs/stable/user_guide/window.html#custom-window-rolling).
It is required to subclass `BaseIndexer` and define ones' own `get_window_bounds`.
In case windows' bounds are defined by timestamps, pandas already provide a nice API to define them as `pd.IntervalIndex`.
Requested feature is to have rolling accepting `pd.IntervalIndex` in `window` parameter, that would be used in combination with `on` parameter to define the datetime-like column (already the case apparently)
#### API breaking implications
`window` parameter accepts `pd.IntervalIndex`
#### Additional context
This operation could be managed by use of `pd.IntervalIndex` and `pd.cut` but this combination does not take advantage that:
- intervals are sorted and non overlapping
- datetime-like column is sorted
which allows then to go through the DataFrame only once, managing each intervals one after the other.
I think that rolling naturally does. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/40703 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40703/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40703/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40703/events | https://github.com/pandas-dev/pandas/pull/40703 | 846,304,013 | MDExOlB1bGxSZXF1ZXN0NjA1NDA5NTE2 | 40,703 | CLN: add property to check if NDFrame uses ArrayManager | {
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cc @jbrockmendel | {
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https://api.github.com/repos/pandas-dev/pandas/issues/40704 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40704/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40704/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40704/events | https://github.com/pandas-dev/pandas/issues/40704 | 846,696,277 | MDU6SXNzdWU4NDY2OTYyNzc= | 40,704 | BUG: Divide zero by zero returns NaN in a Float64 dtype column which cannot be handled by fillna | {
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] | closed | false | null | [] | null | 2 | "2021-03-31T13:44:13Z" | "2021-03-31T15:18:20Z" | "2021-03-31T15:18:20Z" | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version 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/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
series1 = pd.Series([0.], dtype=pd.Float64Dtype())
series2 = pd.Series([0.], dtype=pd.Float64Dtype())
series1/series2
0 NaN
dtype: Float64
(series1/series2).fillna(0)
0 NaN
dtype: Float64
```
#### Problem description
When dividing a pd.Float64Dtype series by another of the same type, and if there is a zero by zero division taking place, then pandas returns a NaN value for that particular case. If I want to replace this NaN value with something else, I cannot do that.
I can only get it to work if I do:
```python
(series1/series2).astype(float).astype(pd.Float64Dtype()).fillna(0)
0 0.0
dtype: Float64
```
#### Expected Output
```python
(series1/series2).fillna(0)
0 0.0
dtype: Float64
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.3
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/40705 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40705/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40705/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40705/events | https://github.com/pandas-dev/pandas/issues/40705 | 846,805,072 | MDU6SXNzdWU4NDY4MDUwNzI= | 40,705 | BUG: Incorrect timedelta with tz_localize and nonexistent times | {
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] | open | false | null | [] | null | 1 | "2021-03-31T14:48:26Z" | "2021-04-13T15:37:12Z" | null | NONE | null | - [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
s = pd.Series(range(2),
index=pd.DatetimeIndex(['2021-03-28 01:30:00',
'2021-03-28 02:30:00']))
s.tz_localize('Europe/London', nonexistent=pd.Timedelta('1H'))
```
```python
2021-03-28 03:30:00+01:00 0
2021-03-28 02:30:00+01:00 1
dtype: int64
```
#### Problem description
Using Timedelta with the `nonexistent` flag with `tz_localize` is adding 2 hours instead of 1 hour for nonexistent times in 'Europe/London' tz. DST started on 2021-03-28 when 59:59 > 02:00 so '2021-03-28 01:30:00' is nonexistent. When I run almost the same code from the docs with 'Europe/Warsaw' the bug does not occur:
```python
s = pd.Series(range(2),
index=pd.DatetimeIndex(['2021-03-28 02:30:00',
'2021-03-28 03:30:00']))
s.tz_localize('Europe/Warsaw', nonexistent=pd.Timedelta('1H'))
```
```python
2021-03-28 03:30:00+02:00 0
2021-03-28 03:30:00+02:00 1
dtype: int64
```
#### Expected Output
```python
2021-03-28 02:30:00+01:00 0
2021-03-28 02:30:00+01:00 1
dtype: int64
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 1.2.3
numpy : 1.19.5
pytz : 2020.5
dateutil : 2.8.1
pip : 20.3.3
setuptools : 51.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.6
pandas_gbq : None
pyarrow : 2.0.0
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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- [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
I was installing the development environment and it was failing due to:
> /home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
This also happens in the Docker container under some conditions (creating a new env).
Steps followed:
```bash
mamba env create -f environment.yml
conda activate pandas-dev
python setup.py build_ext -j 4 # <-- ERROR HERE
python -m pip install -e . --no-build-isolation --no-use-pep517
```
Adding a `extra_link_args.append("-L/usr/lib/x86_64-linux-gnu/")` fixed the issue on Ubuntu 20.04.
<details>
<summary>Logs</summary>
```
❯ python setup.py build_ext -j 4 (pandas-dev)
Compiling pandas/_libs/algos.pyx because it changed.
Compiling pandas/_libs/groupby.pyx because it changed.
Compiling pandas/_libs/hashing.pyx because it changed.
Compiling pandas/_libs/hashtable.pyx because it changed.
Compiling pandas/_libs/index.pyx because it changed.
Compiling pandas/_libs/indexing.pyx because it changed.
Compiling pandas/_libs/internals.pyx because it changed.
Compiling pandas/_libs/interval.pyx because it changed.
Compiling pandas/_libs/join.pyx because it changed.
Compiling pandas/_libs/lib.pyx because it changed.
Compiling pandas/_libs/missing.pyx because it changed.
Compiling pandas/_libs/parsers.pyx because it changed.
Compiling pandas/_libs/reduction.pyx because it changed.
Compiling pandas/_libs/ops.pyx because it changed.
Compiling pandas/_libs/ops_dispatch.pyx because it changed.
Compiling pandas/_libs/properties.pyx because it changed.
Compiling pandas/_libs/reshape.pyx because it changed.
Compiling pandas/_libs/sparse.pyx because it changed.
Compiling pandas/_libs/tslib.pyx because it changed.
Compiling pandas/_libs/tslibs/base.pyx because it changed.
Compiling pandas/_libs/tslibs/ccalendar.pyx because it changed.
Compiling pandas/_libs/tslibs/dtypes.pyx because it changed.
Compiling pandas/_libs/tslibs/conversion.pyx because it changed.
Compiling pandas/_libs/tslibs/fields.pyx because it changed.
Compiling pandas/_libs/tslibs/nattype.pyx because it changed.
Compiling pandas/_libs/tslibs/np_datetime.pyx because it changed.
Compiling pandas/_libs/tslibs/offsets.pyx because it changed.
Compiling pandas/_libs/tslibs/parsing.pyx because it changed.
Compiling pandas/_libs/tslibs/period.pyx because it changed.
Compiling pandas/_libs/tslibs/strptime.pyx because it changed.
Compiling pandas/_libs/tslibs/timedeltas.pyx because it changed.
Compiling pandas/_libs/tslibs/timestamps.pyx because it changed.
Compiling pandas/_libs/tslibs/timezones.pyx because it changed.
Compiling pandas/_libs/tslibs/tzconversion.pyx because it changed.
Compiling pandas/_libs/tslibs/vectorized.pyx because it changed.
Compiling pandas/_libs/testing.pyx because it changed.
Compiling pandas/_libs/window/aggregations.pyx because it changed.
Compiling pandas/_libs/window/indexers.pyx because it changed.
Compiling pandas/_libs/writers.pyx because it changed.
Compiling pandas/io/sas/sas.pyx because it changed.
[ 1/40] Cythonizing pandas/_libs/algos.pyx
[ 2/40] Cythonizing pandas/_libs/groupby.pyx
[ 4/40] Cythonizing pandas/_libs/hashtable.pyx
[ 3/40] Cythonizing pandas/_libs/hashing.pyx
[ 5/40] Cythonizing pandas/_libs/index.pyx
[ 6/40] Cythonizing pandas/_libs/indexing.pyx
[ 7/40] Cythonizing pandas/_libs/internals.pyx
[ 8/40] Cythonizing pandas/_libs/interval.pyx
[ 9/40] Cythonizing pandas/_libs/join.pyx
[10/40] Cythonizing pandas/_libs/lib.pyx
[11/40] Cythonizing pandas/_libs/missing.pyx
[12/40] Cythonizing pandas/_libs/ops.pyx
[13/40] Cythonizing pandas/_libs/ops_dispatch.pyx
[14/40] Cythonizing pandas/_libs/parsers.pyx
[15/40] Cythonizing pandas/_libs/properties.pyx
[16/40] Cythonizing pandas/_libs/reduction.pyx
[17/40] Cythonizing pandas/_libs/reshape.pyx
[18/40] Cythonizing pandas/_libs/sparse.pyx
[19/40] Cythonizing pandas/_libs/testing.pyx
[20/40] Cythonizing pandas/_libs/tslib.pyx
[21/40] Cythonizing pandas/_libs/tslibs/base.pyx
[22/40] Cythonizing pandas/_libs/tslibs/ccalendar.pyx
[23/40] Cythonizing pandas/_libs/tslibs/conversion.pyx
[24/40] Cythonizing pandas/_libs/tslibs/dtypes.pyx
[25/40] Cythonizing pandas/_libs/tslibs/fields.pyx
[26/40] Cythonizing pandas/_libs/tslibs/nattype.pyx
[27/40] Cythonizing pandas/_libs/tslibs/np_datetime.pyx
[28/40] Cythonizing pandas/_libs/tslibs/offsets.pyx
[29/40] Cythonizing pandas/_libs/tslibs/parsing.pyx
[30/40] Cythonizing pandas/_libs/tslibs/period.pyx
[31/40] Cythonizing pandas/_libs/tslibs/strptime.pyx
[32/40] Cythonizing pandas/_libs/tslibs/timedeltas.pyx
[33/40] Cythonizing pandas/_libs/tslibs/timestamps.pyx
[34/40] Cythonizing pandas/_libs/tslibs/timezones.pyx
[35/40] Cythonizing pandas/_libs/tslibs/tzconversion.pyx
[36/40] Cythonizing pandas/_libs/tslibs/vectorized.pyx
[37/40] Cythonizing pandas/_libs/window/aggregations.pyx
[38/40] Cythonizing pandas/_libs/window/indexers.pyx
[39/40] Cythonizing pandas/_libs/writers.pyx
[40/40] Cythonizing pandas/io/sas/sas.pyx
running build_ext
building 'pandas._libs.algos' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/algos.c -o build/temp.linux-x86_64-3.8/pandas/_libs/algos.o
building 'pandas._libs.groupby' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/groupby.c -o build/temp.linux-x86_64-3.8/pandas/_libs/groupby.o
building 'pandas._libs.hashtable' extension
building 'pandas._libs.hashing' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/hashing.c -o build/temp.linux-x86_64-3.8/pandas/_libs/hashing.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/hashtable.c -o build/temp.linux-x86_64-3.8/pandas/_libs/hashtable.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/hashing.o -o build/lib.linux-x86_64-3.8/pandas/_libs/hashing.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.index' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I./pandas/_libs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/index.c -o build/temp.linux-x86_64-3.8/pandas/_libs/index.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/index.o -o build/lib.linux-x86_64-3.8/pandas/_libs/index.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.indexing' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/indexing.c -o build/temp.linux-x86_64-3.8/pandas/_libs/indexing.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/indexing.o -o build/lib.linux-x86_64-3.8/pandas/_libs/indexing.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.internals' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/internals.c -o build/temp.linux-x86_64-3.8/pandas/_libs/internals.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/internals.o -o build/lib.linux-x86_64-3.8/pandas/_libs/internals.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.interval' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/interval.c -o build/temp.linux-x86_64-3.8/pandas/_libs/interval.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/groupby.o -o build/lib.linux-x86_64-3.8/pandas/_libs/groupby.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.join' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/join.c -o build/temp.linux-x86_64-3.8/pandas/_libs/join.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/hashtable.o -o build/lib.linux-x86_64-3.8/pandas/_libs/hashtable.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.lib' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs -I./pandas/_libs/tslibs -I./pandas/_libs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/lib.c -o build/temp.linux-x86_64-3.8/pandas/_libs/lib.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs -I./pandas/_libs/tslibs -I./pandas/_libs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/src/parser/tokenizer.c -o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/tokenizer.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/lib.o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/tokenizer.o -o build/lib.linux-x86_64-3.8/pandas/_libs/lib.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.missing' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/missing.c -o build/temp.linux-x86_64-3.8/pandas/_libs/missing.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/missing.o -o build/lib.linux-x86_64-3.8/pandas/_libs/missing.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.parsers' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -Ipandas/_libs/src/klib -Ipandas/_libs/src -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/parsers.c -o build/temp.linux-x86_64-3.8/pandas/_libs/parsers.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/algos.o -o build/lib.linux-x86_64-3.8/pandas/_libs/algos.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.reduction' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/reduction.c -o build/temp.linux-x86_64-3.8/pandas/_libs/reduction.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/reduction.o -o build/lib.linux-x86_64-3.8/pandas/_libs/reduction.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.ops' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/ops.c -o build/temp.linux-x86_64-3.8/pandas/_libs/ops.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/interval.o -o build/lib.linux-x86_64-3.8/pandas/_libs/interval.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.ops_dispatch' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/ops_dispatch.c -o build/temp.linux-x86_64-3.8/pandas/_libs/ops_dispatch.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/ops_dispatch.o -o build/lib.linux-x86_64-3.8/pandas/_libs/ops_dispatch.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.properties' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/properties.c -o build/temp.linux-x86_64-3.8/pandas/_libs/properties.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/properties.o -o build/lib.linux-x86_64-3.8/pandas/_libs/properties.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.reshape' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/reshape.c -o build/temp.linux-x86_64-3.8/pandas/_libs/reshape.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -Ipandas/_libs/src/klib -Ipandas/_libs/src -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/src/parser/tokenizer.c -o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/tokenizer.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/ops.o -o build/lib.linux-x86_64-3.8/pandas/_libs/ops.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.sparse' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/sparse.c -o build/temp.linux-x86_64-3.8/pandas/_libs/sparse.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -Ipandas/_libs/src/klib -Ipandas/_libs/src -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/src/parser/io.c -o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/io.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/parsers.o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/tokenizer.o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/io.o -o build/lib.linux-x86_64-3.8/pandas/_libs/parsers.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslib' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslib.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslib.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/reshape.o -o build/lib.linux-x86_64-3.8/pandas/_libs/reshape.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.base' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/base.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/base.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/base.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/base.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.ccalendar' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/ccalendar.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/ccalendar.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/ccalendar.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/ccalendar.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.dtypes' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/dtypes.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/dtypes.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslib.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslib.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.conversion' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/conversion.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/conversion.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/dtypes.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/dtypes.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.fields' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/fields.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/fields.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/src/datetime/np_datetime.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/conversion.o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/conversion.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.nattype' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/nattype.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/nattype.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/fields.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/fields.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.np_datetime' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/np_datetime.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/np_datetime.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/src/datetime/np_datetime.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/src/datetime/np_datetime_strings.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime_strings.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/np_datetime.o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime.o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime_strings.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/np_datetime.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.offsets' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/offsets.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/offsets.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/nattype.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/nattype.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.parsing' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/parsing.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/parsing.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -Ipandas/_libs/src/klib -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/src/parser/tokenizer.c -o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/tokenizer.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/parsing.o build/temp.linux-x86_64-3.8/pandas/_libs/src/parser/tokenizer.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/parsing.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.period' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/period.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/period.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/sparse.o -o build/lib.linux-x86_64-3.8/pandas/_libs/sparse.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.strptime' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/strptime.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/strptime.o
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/tslibs -I./pandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/src/datetime/np_datetime.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/period.o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/src/datetime/np_datetime.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/period.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.timedeltas' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/timedeltas.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/timedeltas.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/offsets.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/offsets.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.timestamps' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/timestamps.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/timestamps.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/strptime.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/strptime.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.timezones' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/timezones.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/timezones.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/timedeltas.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/timedeltas.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.tzconversion' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/tzconversion.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/tzconversion.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/timezones.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/timezones.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.tslibs.vectorized' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs/tslibs -Ipandas/_libs/tslibs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/tslibs/vectorized.c -o build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/vectorized.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/timestamps.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/timestamps.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.testing' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/testing.c -o build/temp.linux-x86_64-3.8/pandas/_libs/testing.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/vectorized.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/vectorized.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.window.aggregations' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -Ipandas/_libs/window -I./pandas/_libs -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/window/aggregations.cpp -o build/temp.linux-x86_64-3.8/pandas/_libs/window/aggregations.o
cc1plus: warning: command line option '-Wstrict-prototypes' is valid for C/ObjC but not for C++
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/testing.o -o build/lib.linux-x86_64-3.8/pandas/_libs/testing.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.window.indexers' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/window/indexers.c -o build/temp.linux-x86_64-3.8/pandas/_libs/window/indexers.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/tslibs/tzconversion.o -o build/lib.linux-x86_64-3.8/pandas/_libs/tslibs/tzconversion.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas._libs.writers' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/_libs/writers.c -o build/temp.linux-x86_64-3.8/pandas/_libs/writers.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/window/indexers.o -o build/lib.linux-x86_64-3.8/pandas/_libs/window/indexers.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
building 'pandas.io.sas._sas' extension
gcc -pthread -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DNPY_NO_DEPRECATED_API=0 -I/home/cristian/miniforge3/envs/pandas-dev/lib/python3.8/site-packages/numpy/core/include -I/home/cristian/miniforge3/envs/pandas-dev/include/python3.8 -c pandas/io/sas/sas.c -o build/temp.linux-x86_64-3.8/pandas/io/sas/sas.o
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/writers.o -o build/lib.linux-x86_64-3.8/pandas/_libs/writers.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
g++ -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/window/aggregations.o -o build/lib.linux-x86_64-3.8/pandas/_libs/window/aggregations.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/io/sas/sas.o -o build/lib.linux-x86_64-3.8/pandas/io/sas/_sas.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
gcc -pthread -shared -B /home/cristian/miniforge3/envs/pandas-dev/compiler_compat -L/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,-rpath=/home/cristian/miniforge3/envs/pandas-dev/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.8/pandas/_libs/join.o -o build/lib.linux-x86_64-3.8/pandas/_libs/join.cpython-38-x86_64-linux-gnu.so
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /lib64/libpthread.so.0
/home/cristian/miniforge3/envs/pandas-dev/compiler_compat/ld: cannot find /usr/lib64/libpthread_nonshared.a
collect2: error: ld returned 1 exit status
error: command 'gcc' failed with exit status 1
```
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> Enable the string methods for the arrow-backed StringArray. This might also need some additional changes in the string accessor code (eg to dispatch extract to the underlying array as well)
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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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} | 1 | "2021-03-31T20:07:21Z" | "2021-06-04T12:51:37Z" | "2021-06-04T12:51:37Z" | CONTRIBUTOR | null | `DataFrame.to_html` has max rows and max cols to automatically trim the console or string output.
`DataFrame.styler.render` does not and with large DataFrames this can potentially crash the browser of a Jupyter Notebook, or maybe a console.
Personally, I use `Styler` occasionally to quickly avoid the reasonably small max values in the former and this I would want to keep, but some tolerable, larger limit should be imposed in my opinion. | {
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} | 5 | "2021-03-31T21:26:48Z" | "2021-04-01T19:27:51Z" | "2021-04-01T19:27:51Z" | NONE | null | ```python
import pandas as pd
from matplotlib import pyplot as plt
series = [pd.Series([1,2,3,4]) for _ in range(4)]
nrow, ncol = 2, 2
fig, axes = plt.subplots(nrow, ncol)
axes = axes.reshape(-1)
for i, s in enumerate(series):
s.plot(ax=axes[i])
plt.tight_layout()
```
#### Problem description
After executing the previous code the following message from Matplotlib is shown:
```my_personal_folder/lib/python3.8/site-packages/pandas/plotting/_matplotlib/tools.py:400: MatplotlibDeprecationWarning:
The is_first_col function was deprecated in Matplotlib 3.4 and will be removed two minor releases later. Use ax.get_subplotspec().is_first_col() instead.
if ax.is_first_col():
```
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} | 4 | "2021-03-31T23:07:12Z" | "2021-04-02T01:03:35Z" | "2021-04-02T00:50:08Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] 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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