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https://api.github.com/repos/pandas-dev/pandas/issues/32617 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32617/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32617/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32617/events | https://github.com/pandas-dev/pandas/issues/32617 | 579,107,613 | MDU6SXNzdWU1NzkxMDc2MTM= | 32,617 | improve read_excel performance | {
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"default"... | closed | false | null | [] | null | 3 | 2020-03-11T09:04:07Z | 2020-05-08T00:47:33Z | 2020-05-08T00:47:33Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
# Your code here
```
#### Problem description
I have a spreadsheet of 600,000 rows and the read_excel function takes around 10mins to process.
Is there any way to improve the performance?
[this should explain **why** the current behaviour i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32618 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32618/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32618/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32618/events | https://github.com/pandas-dev/pandas/pull/32618 | 579,149,111 | MDExOlB1bGxSZXF1ZXN0Mzg2NTk2NjYw | 32,618 | DOC: Clarify pivot_table fill_value description | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
---
Clarify that `fill_value` gets used after performing the aggregation (i.e. it fills values in the resulting pivot table).
(Depending on the a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32619 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32619/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32619/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32619/events | https://github.com/pandas-dev/pandas/issues/32619 | 579,210,212 | MDU6SXNzdWU1NzkyMTAyMTI= | 32,619 | Allow choosing the utc timezone class in pd.to_datetime | {
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... | 8 | 2020-03-11T11:55:18Z | 2021-07-30T03:23:32Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
from datetime import datetime, timezone
import pandas as pd
dt1 = pd.to_datetime(datetime(2020, 3, 11), utc=True)
print(repr(dt1))
print(type(dt1.tz))
dt2 = pd.to_datetime(datetime(2020, 3, 11, tzinfo=timezone.utc))
print(repr(dt2))
print(ty... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32620 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32620/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32620/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32620/events | https://github.com/pandas-dev/pandas/pull/32620 | 579,233,183 | MDExOlB1bGxSZXF1ZXN0Mzg2NjY0MTQ0 | 32,620 | DOC: fix formatting / links of API refs in 1.0.2 whatsnew | {
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```python
import pandas as pd
import numpy as np
rep = {'one': '1', 'two': '2'}
a = pd.Series(['one', 'two'], dtype='string')
b = pd.Series(['one', 'two', np.nan])
c = pd.Series(['one', 'two', np.nan], dtype='string')
# A: this works
a.replace(to_re... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32622 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32622/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32622/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32622/events | https://github.com/pandas-dev/pandas/issues/32622 | 579,252,850 | MDU6SXNzdWU1NzkyNTI4NTA= | 32,622 | df.index.is_unique inflates index memory | {
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```python
l = np.arange(9)
df = pd.DataFrame({'a':l, 'b':l, 'c':l})
print('shape', df.shape)
display(df.memory_usage(deep=True, index=True))
print()
print('drop one row')
df.drop(index=[1], inplace=True)
display(df.memory_usage(deep=Tr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32623 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32623/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32623/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32623/events | https://github.com/pandas-dev/pandas/issues/32623 | 579,258,847 | MDU6SXNzdWU1NzkyNTg4NDc= | 32,623 | Pandas 1.0.1 unable to read excels it created itself | {
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`writer=pd.ExcelWriter(outfile)`
Then in a different script, when processing the same files with `pd.read_excel(outfile)`
on some (but not all) files I get error:
`xlrd.biffh.XLRDError: ZIP file cont... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32624 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32624/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32624/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32624/events | https://github.com/pandas-dev/pandas/issues/32624 | 579,261,065 | MDU6SXNzdWU1NzkyNjEwNjU= | 32,624 | BUG in _unstack_multiple | {
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Next code fail to do unstack.
```python
d = pd.DataFrame([[1,2,3],[2,2,3],[3,2,3],[4,2,3],[5,2,3]],
columns=pd.MultiIndex.from_tuples([[0, 0, 0], [0, 0, 1], [0, 0, 2]], names=['c1', 'c2', 'c3']),
index=pd.MultiIndex.from_tuples([[0, 0, 0, 0, 0, 0, 0],
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4 France 1784 NaN 33.0 NaN 12.0 1739 86.0 27.3
.. ... ... ... ... ... ... ... ... ...
115 Mongolia 1 NaN NaN NaN NaN 1 NaN 0.3... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32628 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32628/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32628/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32628/events | https://github.com/pandas-dev/pandas/issues/32628 | 579,307,871 | MDU6SXNzdWU1NzkzMDc4NzE= | 32,628 | Test warnings on 32bit build | {
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A few different classes
```
2020-03-11T13:55:49.8259424Z ##[warning]elementwise == comparison failed; this will raise an error in the future.
2020... | {
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Do NOT accept this at this point. Right now I am trying to figure out where a bug is originating and I need the tests to run. | {
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... | closed | false | null | [] | null | 8 | 2020-03-11T16:59:21Z | 2020-03-12T13:37:12Z | 2020-03-11T22:31:58Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
import numpy as np
df = pd.DataFrame({'x': [1, 1, 1, 2, 2, 2], 'y': [1, 2, np.nan, np.nan, np.nan, 6]})
print(df)
# Doesn't replace NaN's
df.groupby('x').sum()
print(df)
# Replaces NaN's
df.groupby('x').nunique()
prin... | {
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- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/32634 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32634/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32634/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32634/events | https://github.com/pandas-dev/pandas/issues/32634 | 579,440,728 | MDU6SXNzdWU1Nzk0NDA3Mjg= | 32,634 | pandas plotting - matplotlib 3.2.0 deprecation warning for rowNum/colNum attributes | {
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Environment:
```
c> conda list "python|pandas|matplotlib|numpy|conda"
# packages in environment at C:\Users\me\Miniconda3\env... | {
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Over there, we removed `_ensure_type` because it broke things like
```python
import pandas as pd
import pandas.testing as pdt
class MyDataFrame(pd.DataFrame):
pass
mdf = MyDataFrame()
df = pd.DataFrame()
# In DataFrame.reindex_like, the... | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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Ideally I'd want to keep the method and change the behavior to (an improved variant of) _internal_get_values, but so it goes. | {
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Copies ``._cache`` also when copying using ``.shallow_copy`` for:
* CategoricalIndex
* DatetimeIndex
* PeriodIndex
* DateTimeIndex
* IntervalIndex
After this PR, only ``MultiIndex._shallow_copy`` is missing this optimization. ``MultiIndex._shallow_copy`` is a bit special and might requi... | {
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This PR doesn't solve that, but simplifies the logic to make it easier to grok | {
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- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
ATM if we call MultiIndex.union with e.g. a Float64Index, we get `ValueError: Buffer dtype mismatch, expected 'Python object' but got 'double'` from ... | {
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```python
import pandas as pd
import numpy as np
int64_info = np.iinfo("int64")
s = pd.Series([int64_info.max, None, int64_info.min], dtype=pd.Int64Dtype())
df = pd.DataFrame({"Int64": s})
df.max()
Int64 9.223372e+18
dtype: float64
```
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] | closed | false | null | [] | null | 7 | 2020-03-12T08:35:13Z | 2020-04-18T02:46:09Z | 2020-04-18T02:46:09Z | CONTRIBUTOR | null | Calling `.min()` or `.max()` on `pd.Int64` data returns integers, but uses `float64` as an intermediate representation, leading to data corruption.
This PR attempts to whitelist them to be processed entirely as `Int64`s. Also add a test that verifies this behavior, as existing tests failed to detect the bug.
- [x... | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Related to #27977.
```
################################################################################
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```
df.drop(columns='My Col')
```
But neither of these do:
```
df.dropna(subset='My Col')
df.drop_duplicates(subset='My Col')
df.duplicated(subset='My Col')
```
all of which instead should be called with `subset=['My Col']`.
This is a feature request for the three latter functions to allow the s... | {
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Hello!
I have a fresh Rstudio where i want to work with some data which come from python scripts. I try to use reticulate to source the following python script:
```python
# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
import functools as ft
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```
Contributors
============
A total of 143 people contributed patches to this release. People with a
"+" by their names contributed a patch for the first time.
* 3vts +
* A Brooks +
* Abbie Popa +
* Achmad Syarif Hidayatullah +
```
PR
```
Contributors
============
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https://api.github.com/repos/pandas-dev/pandas/issues/32663 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32663/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32663/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32663/events | https://github.com/pandas-dev/pandas/issues/32663 | 580,077,391 | MDU6SXNzdWU1ODAwNzczOTE= | 32,663 | read_sql_query convert TEXT looking like floats to float | {
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```python
import pandas as pd
query = "SELECT MYSTR FROM TABLE"
df = pd.read_sql_query(query, engine)
df.info()
```
returns
```
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 524 entries, 0 to 523
Data columns (total 1 columns... | {
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The docs for read_csv currently include the following:
index_col:
int, str, sequence of int / str, or False, default None
Column(s) to use as the row labels of the DataFrame, either given as string name or column index. If a sequence of int / str is given, a MultiIndex is used.... | {
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Modified to get it through ``dtype`` of Series, which is known to be ``Period``.
- [X] closes #31917
- [X] fix #31917
- [x] tests added / passed
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- [ x ] closes #26278
- [ x] tests added / passed
- [ x] passes `black pandas`
- [ x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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This is a feature request to add an optional `index=False` argument to the new `to_markdown()` dataframe method. This would produce a markdown table without the initial unnamed index column.
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Identified when making the change this makes in Series. | {
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Improves performance of ``MultiIndex._shallow_copy``. Example:
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
Re-introduced `check_series_type` in `assert_series_equal` which was recently removed in #32513. It was a part of public API which is not used internally, but it is used elsewhere (like geopandas). Discussion in #32513 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32672 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32672/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32672/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32672/events | https://github.com/pandas-dev/pandas/pull/32672 | 580,325,788 | MDExOlB1bGxSZXF1ZXN0Mzg3NTU1MTA4 | 32,672 | Avoid bare pytest.raises in dtypes/test_dtypes.py | {
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* [x] tests added / passed
* [x] passes `black pandas`
* [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/32673 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32673/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32673/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32673/events | https://github.com/pandas-dev/pandas/issues/32673 | 580,336,950 | MDU6SXNzdWU1ODAzMzY5NTA= | 32,673 | API: should values_for_factorize and _from_factorized round-trip missing values? | {
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```
from pandas.tests.extension.json.test_json import *
dtype = JSONDtype()
data = make_data()
while len(data[0]) == len(data[1]):
data = make_data()
data = JSONArray(data)
values = data._values_for_factorize()[0]
result = t... | {
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] | closed | false | null | [] | null | 4 | 2020-03-13T06:36:39Z | 2020-03-22T02:19:28Z | 2020-03-17T07:01:40Z | NONE | null | #### Problem description
Why am i getting this warning? i am just creating a dataframe using DataFrame function
#### Expected Output
#### Output of ``pd.show_versions()``
version is 1.0.1
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```
def isna(df, how='any', subset: Collection[str] = ()) -> pd.Series:
"""
Like DataFrame.isna(), but allows `how` and `subset` arguments
"""
if not subset:
subset = df.columns
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- [ ] tests added / passed
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---
Benchmarks:
#### Master:
```
In [1]: import pandas as pd ... | {
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```python
import pandas as pd
class ServiceMetadataClass(object):
"""Stores Metadata from Service endpoint"""
url = None
info = None
renderer = None
def __init__(self, url=None, renderer=None, original_fields=None):
self.url ... | {
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The documentation for `pandas.Index.slice_locs` does not specify what happens if the label(s) are not found. Internally it seems to be using `pandas.Index.get_slice_bound`, so maybe a reference to this method should be added.
Another thing that would be nice is if `pandas.Index.slice_loc... | {
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- [ ] tests added / passed
- [x] passes `black pandas`
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---
This PR was opened as @jbrockmendel suggested (ref https://github.com/pandas-dev/pandas/pull/32177#discussion_r382923663)
---
### Benchm... | {
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For th... | {
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"followers_url": "https://api.github.com/users/jorisva... | 15 | 2020-03-13T15:33:15Z | 2020-07-17T11:21:59Z | 2020-07-17T11:21:59Z | NONE | null | Hello. The PR fixes https://github.com/pandas-dev/pandas/issues/31930
Please review and merge if you think it is good enough :)
Regards,
Artyom.
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cc @spencerclark I think this fixes a subset of the issues reported in https://github.com/pydata/xarray/issues/3751, can you confirm?
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https://api.github.com/repos/pandas-dev/pandas/issues/32685 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32685/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32685/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32685/events | https://github.com/pandas-dev/pandas/issues/32685 | 580,735,593 | MDU6SXNzdWU1ODA3MzU1OTM= | 32,685 | Regression in artihmetic ops with alignment and special cases | {
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"followers_url": "https://api.github.c... | 3 | 2020-03-13T17:12:42Z | 2020-03-17T15:41:09Z | 2020-03-17T15:41:09Z | CONTRIBUTOR | null | I think 1.0.2 has a regression in arithmetic when we align but the result of `op(a, NA)` isn't NA. For example 1**np.nan should be 1.
Previous
```python
In [3]: pd.__version__
Out[3]: '1.0.1'
In [4]: pd.DataFrame({"A": [0, 1, 2]}) ** pd.DataFrame(index=[0, 1, 2])
Out[4]:
A
0 NaN
1 1.0
2 NaN
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https://api.github.com/repos/pandas-dev/pandas/issues/32686 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/32686/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/32686/comments | https://api.github.com/repos/pandas-dev/pandas/issues/32686/events | https://github.com/pandas-dev/pandas/issues/32686 | 580,781,153 | MDU6SXNzdWU1ODA3ODExNTM= | 32,686 | Unable to store NaT in parquet format. | {
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```python
import pandas as pd
df = pd.DataFrame({"date": ["", "2019-05-01"]})
df.date = pd.to_datetime(df.date).dt.date
df.to_parquet("issue_NaT_parquet")
```
#### Problem description
The above gives me the following error:
<details>
> -------------------------------------------------... | {
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```
[ 1167s] =================================== FAILURES ===================================
[ 1167s] ______________ tes... | {
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```python
>>> import pandas as pd
>>> x = pd.Series([1, 2, 3], index=pd.to_datetime(['2020-01-01', '2020-01-02', '2020-01-03']))
>>> x[:,None].ndim
>>> x.to_numpy()[:,None].ndim
>>> x.index.array[:,None].ndim
>>> x.array[:,None].ndim
```
#### Problem description
Currently PandasArray be... | {
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Using ``.mean(skipna = True)`` or ``.mean(skipna = False)`` on a ``groupby`` object gives error:
```python
UnsupportedFunctionCall: numpy operations are not valid with groupby. Use .groupby(...).mean() instead
```
skipna is a crucial parameter while doing analysis. By default ``skipna = ... | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Related to #27977.
```
################################################################################
################################## Vali... | {
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```
In [3]: import sqlalchemy
...: import pandas as pd
In [4]: conn = sqlalchemy.create_engine('postgres://xxx:xxx@xxx/xxx')
In [5]... | {
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- [x] tests passed
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] note about dtype in `diff` in Dataframa and Series
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The h5 files generated with track_times=False has the same md5 hashes, that is covered in the unit test as well as the fact that the hashes are not the same with trac... | {
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- [x] closes #25509
- [x] tests added / passed
- [x] passes `black pandas`
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- [x] whatsnew entry
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```python
import pandas as pd
a = [4,6,9,5,2,4]
pleft = pd.DataFrame.from_dict({'a':a})
pright = pleft.copy(deep=True)
# Make two indices to also be used as join columns
pleft.index = [6,5,4,7,5,5]
pright.index = [5,4,1,9,4,3]
pd_result = pleft.merge(... | {
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`pandas.Series.divmod` is still missing an example as discussed in #25524.
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