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https://api.github.com/repos/pandas-dev/pandas/issues/33017 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33017/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33017/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33017/events | https://github.com/pandas-dev/pandas/issues/33017 | 587,871,083 | MDU6SXNzdWU1ODc4NzEwODM= | 33,017 | Unspecific error message when setting singular index with np dtype | {
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```python
some_np_array = np.array([43, 56])
# unspecific error message 'TypeError: len() of unsized object':
pd.DataFrame([4324, 345], index=some_np_array[0])
pd.Series([4324, 345], index=some_np_array[0])
# specific error message 'TypeError: Index(...)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33018 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33018/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33018/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33018/events | https://github.com/pandas-dev/pandas/pull/33018 | 587,884,064 | MDExOlB1bGxSZXF1ZXN0MzkzNzQwMDgx | 33,018 | REF: CategoricalIndex indexing tests | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33020 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33020/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33020/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33020/events | https://github.com/pandas-dev/pandas/issues/33020 | 587,978,506 | MDU6SXNzdWU1ODc5Nzg1MDY= | 33,020 | read_csv ParserError | {
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```python
# Your code here
#import pandas as pd
import pandas as pd
#Indicate file path
url = 'http://localhost:8888/edit/Dropbox/COURSES/Data%20Analysis%20Using%20Python/BookNEW.csv'
#Read data
df= pd.read_csv(url)
df.header()
```
#### Problem des... | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] replaces a number of uses of @Appender() with @doc() in `core/generic.py`
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https://api.github.com/repos/pandas-dev/pandas/issues/33022 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33022/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33022/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33022/events | https://github.com/pandas-dev/pandas/pull/33022 | 588,003,452 | MDExOlB1bGxSZXF1ZXN0MzkzODM4MTgy | 33,022 | Fiy Typo in datetimes (parced) | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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I would like to be able to provide a DateTimeIndex directly to rolling() so that the window is defined as [timestamp in provided DateTimeIndex that is immediately previous to timestamp of current row ; timestamp of current row[
Please, is that possible? | {
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I'm generally grateful for the efficient documentation of pandas, and I like the advancements in the new layout of recent versions, except for one thing:
The function/object signature at the very top is much harder to read now that the type annotations are printed as well. How about shading... | {
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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/33027 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33027/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33027/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33027/events | https://github.com/pandas-dev/pandas/issues/33027 | 588,057,308 | MDU6SXNzdWU1ODgwNTczMDg= | 33,027 | concat with Misaligned Column Labels and Extension Types loses Dtype | {
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```python
In [2]: one = pd.DataFrame([["a"]], dtype="string", columns=["a"])
In [3]: two = pd.DataFrame([["b"]], dtype="string", columns=["b"])
In [4]: pd.concat([one, two]).dtypes
Out[4]:
a object
b ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33028 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33028/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33028/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33028/events | https://github.com/pandas-dev/pandas/pull/33028 | 588,080,643 | MDExOlB1bGxSZXF1ZXN0MzkzODk5NzEy | 33,028 | CLN: de-duplicate Block.should_store and related | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33029 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33029/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33029/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33029/events | https://github.com/pandas-dev/pandas/pull/33029 | 588,080,925 | MDExOlB1bGxSZXF1ZXN0MzkzODk5OTMx | 33,029 | DOC: Fixing links to the contributing page | {
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---
Feel free to close this at anytime. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33030 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33030/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33030/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33030/events | https://github.com/pandas-dev/pandas/issues/33030 | 588,085,349 | MDU6SXNzdWU1ODgwODUzNDk= | 33,030 | Feature request: series.fillna('mean') | {
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] | closed | false | null | [] | null | 3 | 2020-03-26T01:12:55Z | 2020-03-27T15:31:35Z | 2020-03-27T15:31:35Z | NONE | null | I would request pandas devs to implement various nans filling methods.
For example:
- mean
- median
- max
- random forest regressor
so on.
Output:
`df['A'].fillna('mean')` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33031 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33031/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33031/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33031/events | https://github.com/pandas-dev/pandas/pull/33031 | 588,118,039 | MDExOlB1bGxSZXF1ZXN0MzkzOTI3NjY1 | 33,031 | fixed #32904 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33032 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33032/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33032/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33032/events | https://github.com/pandas-dev/pandas/pull/33032 | 588,127,928 | MDExOlB1bGxSZXF1ZXN0MzkzOTM1NDU0 | 33,032 | PERF: remove large-array-creating path in fast_xs | {
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Luckily, that case is obsolete, so this rips it right out. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33033 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33033/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33033/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33033/events | https://github.com/pandas-dev/pandas/pull/33033 | 588,155,169 | MDExOlB1bGxSZXF1ZXN0MzkzOTU2NjEz | 33,033 | fix #32904 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33034 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33034/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33034/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33034/events | https://github.com/pandas-dev/pandas/pull/33034 | 588,171,162 | MDExOlB1bGxSZXF1ZXN0MzkzOTY5MTA2 | 33,034 | Bug: TypeError: ufunc 'sqrt' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'' | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33035 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33035/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33035/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33035/events | https://github.com/pandas-dev/pandas/issues/33035 | 588,221,849 | MDU6SXNzdWU1ODgyMjE4NDk= | 33,035 | Can't Seem to install pandas in python | {
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```
sudo pip install pandas
```
#### Problem description
Tried Installing pandas for python 2.7 . Can't seem to figure it out. Checked similar issues, but they didn't seem to help me.
Numpy version : 1.16.6 (tried other versions as well)
#### Expected Output
Pandas installed successfully... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33036 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33036/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33036/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33036/events | https://github.com/pandas-dev/pandas/issues/33036 | 588,264,656 | MDU6SXNzdWU1ODgyNjQ2NTY= | 33,036 | BUG: DataFrame.mad(axis=1) not working for nullable integer dtype | {
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In [32]: df = pd.DataFrame(np.random.randn(100000, 4).astype(int)).astype("Int64")
In [33]: df.mad()
Out[33]:
0 0.363361
1 0.365456
2 0.369014
3 0.368195
dtype: float64
In [34]: df.mad(axis=1)
---------------------------------------------------------------------------
NotImplemented... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33037 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33037/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33037/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33037/events | https://github.com/pandas-dev/pandas/issues/33037 | 588,365,183 | MDU6SXNzdWU1ODgzNjUxODM= | 33,037 | Inconsistent behavior of `read_csv` when given an additional value on the first row of CSV file | {
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... | 9 | 2020-03-26T11:56:30Z | 2021-01-01T21:53:32Z | 2021-01-01T21:53:24Z | NONE | null | #### Short description
Using the following invalid CSV:
```csv
col1_name,col2_name,col3_name
0,1,2,X
4,5,6,
6,7,8
```
It has 3 columns but the *first row* has 4 values and loading it should raise a `ParsingError`.
However, loading using:
```python
pd.read_csv("test.csv", index_col=False)
```
does not r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33038 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33038/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33038/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33038/events | https://github.com/pandas-dev/pandas/issues/33038 | 588,402,801 | MDU6SXNzdWU1ODg0MDI4MDE= | 33,038 | Why pandas doesn't support python 3.6.1? | {
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the requirements for pandas 1 explicit says, that it needs python>=3.6.1. Why is 3.6.0 not supported?
fin swimmer | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33040 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33040/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33040/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33040/events | https://github.com/pandas-dev/pandas/pull/33040 | 588,544,671 | MDExOlB1bGxSZXF1ZXN0Mzk0MjcxMzQ3 | 33,040 | REF: test_searchorted for PeriodIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33041 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33041/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33041/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33041/events | https://github.com/pandas-dev/pandas/issues/33041 | 588,557,559 | MDU6SXNzdWU1ODg1NTc1NTk= | 33,041 | BUG: DataFrame.at implicitly assumes unique axes | {
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```
arr = np.random.randn(6).reshape(3, 2)
df = pd.DataFrame(arr, columns=["A", "A"])
>>> df.at[0, "A"]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pandas/core/indexing.py", line 2069, in __getitem__
return super().__getite... | {
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] | closed | false | null | [] | null | 5 | 2020-03-26T16:35:35Z | 2021-07-30T04:27:13Z | 2021-07-30T04:27:13Z | NONE | null | #### Code Sample, a copy-pastable example if possible
First we create a raw dataset with MultiIndex-
```
In [166]: import numpy as np; import pandas as pd
In [167]: data_raw = pd.DataFrame([
...: {'frame': 1, 'face': np.NaN, 'lmark': np.NaN, 'x': np.NaN, 'y': np.NaN},
...: {'frame': 197, 'face': ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33043 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33043/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33043/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33043/events | https://github.com/pandas-dev/pandas/issues/33043 | 588,600,661 | MDU6SXNzdWU1ODg2MDA2NjE= | 33,043 | to_json() not including all attributes | {
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#### Code Sample
```python
class MyClass:
def __init__(self,value):
self.value=value
self.one=value+1
self.two=value+2
self.three=value+3
def __repr__(self):
return str(self.value)
# Sample
x = MyClass(1)
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... | 5 | 2020-03-26T17:43:07Z | 2020-03-31T19:05:10Z | 2020-03-31T19:05:10Z | CONTRIBUTOR | null | ```python
pandas.show_versions()
```
is not in pandas API Reference. | {
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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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xref #33041, one more PR coming up to close that. | {
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"default"... | closed | false | null | [] | null | 0 | 2020-03-26T17:59:46Z | 2020-04-28T03:30:40Z | 2020-04-28T03:30:40Z | MEMBER | null | Series.index, DataFrame.index, and DataFrame.columns are `AxisProperty`s and whenever they are set, a callback updates the underlying BlockManager.
We could have that same callback also invalidate the cached `obj.loc` and `obj.at` objects.
If we did that, then `LocIndexer` and `AtIndexer` could assume that they w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33047 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33047/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33047/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33047/events | https://github.com/pandas-dev/pandas/pull/33047 | 588,622,707 | MDExOlB1bGxSZXF1ZXN0Mzk0MzM1MDg5 | 33,047 | BUG: DataFrame.at with non-unique axes | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
Closes #33041 in conjunction with #33045. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33048 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33048/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33048/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33048/events | https://github.com/pandas-dev/pandas/issues/33048 | 588,631,748 | MDU6SXNzdWU1ODg2MzE3NDg= | 33,048 | Convenient way to use offset aliases to create a DateOffset? | {
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```python
import pandas as pd
alias_1H = '1H'
alias_1M = '1M'
offset_dict = {alias_1H: ('hours',1), alias_1M: ('months',1)}
def freq_to_offset(freq):
custom_dict = {offset_dict[freq][0] : offset_dict[freq][1]}
return custom_dict
offset_1H ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33049 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33049/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33049/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33049/events | https://github.com/pandas-dev/pandas/issues/33049 | 588,650,592 | MDU6SXNzdWU1ODg2NTA1OTI= | 33,049 | Comparing monthly to dayly frequencies: DateOffset or Timedelta? | {
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] | closed | false | null | [] | null | 4 | 2020-03-26T18:51:21Z | 2020-03-28T05:53:21Z | 2020-03-26T20:37:34Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
offset_1M = pd.tseries.frequencies.to_offset('1MS')
offset_1D = pd.tseries.frequencies.to_offset('1D')
>>> offset_1M > offset_1D
Traceback (most recent call last):
File "/.local/lib/python3.7/site-packages/pandas/tseries/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33050 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33050/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33050/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33050/events | https://github.com/pandas-dev/pandas/pull/33050 | 588,657,651 | MDExOlB1bGxSZXF1ZXN0Mzk0MzYzMTc5 | 33,050 | REF: RangeIndex tests | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33051 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33051/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33051/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33051/events | https://github.com/pandas-dev/pandas/issues/33051 | 588,713,202 | MDU6SXNzdWU1ODg3MTMyMDI= | 33,051 | A bug of CustomBusinessDay | {
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```python
from pandas.tseries.holiday import USFederalHolidayCalendar
from pandas.tseries.offsets import CustomBusinessDay
US_BD = CustomBusinessDay(calendar=USFederalHolidayCalendar())
from pandas.tseries.holiday import AbstractHolidayCalendar, Holiday... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33055 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33055/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33055/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33055/events | https://github.com/pandas-dev/pandas/pull/33055 | 588,852,694 | MDExOlB1bGxSZXF1ZXN0Mzk0NTIzNzY0 | 33,055 | [WIP] Make Index.values read-only | {
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- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
This is a PR for looking around enforcing immutability of `pd.Index` objects. It will be a draft, but the main idea is to show what tests fail and w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33056 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33056/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33056/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33056/events | https://github.com/pandas-dev/pandas/pull/33056 | 588,860,184 | MDExOlB1bGxSZXF1ZXN0Mzk0NTI5NTkx | 33,056 | REF: avoid internals in tshift | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33057 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33057/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33057/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33057/events | https://github.com/pandas-dev/pandas/pull/33057 | 588,864,156 | MDExOlB1bGxSZXF1ZXN0Mzk0NTMyNzA2 | 33,057 | ERR: Raise NotImplementedError with BaseIndexer and certain rolling operations | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
As a temporary solution for returning incorrect results when using a BaseIndexer subclass with certain rolling operations, a `NotImplementedError` wil... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33058 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33058/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33058/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33058/events | https://github.com/pandas-dev/pandas/issues/33058 | 588,868,649 | MDU6SXNzdWU1ODg4Njg2NDk= | 33,058 | Indexing broken inside groupby - apply | {
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```python
import pandas as pd
import pdb
df = pd.DataFrame(
{
'col1': ['A', 'A', 'A', 'B', 'B', 'B'],
'col2': [1, 2, 3, 4, 5, 6],
}
)
def fn(x):
pdb.set_trace()
x.col2[x.index[-1]] = 0
return x.col2
result = df.groupby(['col1'], as_ind... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33059 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33059/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33059/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33059/events | https://github.com/pandas-dev/pandas/issues/33059 | 588,869,875 | MDU6SXNzdWU1ODg4Njk4NzU= | 33,059 | Series Group-by Boxplot has Overlaid Plots | {
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... | open | false | null | [] | null | 0 | 2020-03-27T03:58:30Z | 2021-07-30T04:27:32Z | null | NONE | null | #### Code Sample
```python
import numpy as np
import pandas as pd
sr = pd.Series(index=pd.MultiIndex.from_product([[1, 2, 3], ['A', 'B', 'C', 'D', 'E']]), data=np.random.rand(15))
sr.groupby(level=0).plot.box()
```
#### Problem description
Below is an image of what currently occurs:
![series_boxplot_bad](h... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33060 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33060/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33060/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33060/events | https://github.com/pandas-dev/pandas/issues/33060 | 588,872,375 | MDU6SXNzdWU1ODg4NzIzNzU= | 33,060 | xlsx cannot open on windows 10 | {
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# Code
xlsx_writer = pd.ExcelWriter(os.path.join(output_path, "report.xlsx"), engine='openpyxl')
df = pd.DataFrame(data=[{"val": val} for val in summary.values()], index=summary.keys()).sort_index()
df.to_excel(xlsx_writer, sheet_name="summary")
xlsx_writ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33061 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33061/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33061/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33061/events | https://github.com/pandas-dev/pandas/issues/33061 | 588,920,768 | MDU6SXNzdWU1ODg5MjA3Njg= | 33,061 | DateTimeIndex.tz_convert() does not apply DST from 2038 onward | {
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```python
assert np.all(pd.date_range('1/1/2037', periods=8760, freq='H', tz='EST').time == pd.date_range('1/1/2037', periods=8760, freq='H', tz='US/Eastern').time) == False
assert np.all(pd.date_range('1/1/2038', periods=8760, freq='H', tz='EST').time == pd.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33062 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33062/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33062/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33062/events | https://github.com/pandas-dev/pandas/pull/33062 | 588,969,282 | MDExOlB1bGxSZXF1ZXN0Mzk0NjE3ODM1 | 33,062 | BUG: implement astype from string dtype to nullable int dtype | {
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This implements a conversion from nullable string dtype to nullable int dtype. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33063 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33063/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33063/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33063/events | https://github.com/pandas-dev/pandas/pull/33063 | 588,973,297 | MDExOlB1bGxSZXF1ZXN0Mzk0NjIxMTI5 | 33,063 | CLN: remove CategoricalBlock.to_native_types | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33064 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33064/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33064/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33064/events | https://github.com/pandas-dev/pandas/pull/33064 | 589,021,519 | MDExOlB1bGxSZXF1ZXN0Mzk0NjYwNjk4 | 33,064 | ENH/PERF: use mask in factorize for nullable dtypes | {
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This adds the option to use a mask in the `HashTable.factorize` (implementation itself is in `HashTable._unique`).
That allows eg IntegerArray to use its mask and avoid the need to convert to object dtype or float dtype (which also avoids a copy of the data),... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33065 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33065/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33065/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33065/events | https://github.com/pandas-dev/pandas/issues/33065 | 589,051,050 | MDU6SXNzdWU1ODkwNTEwNTA= | 33,065 | BUG: truncated repr with pd.NA in object dtype column shows "NaN" | {
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```python
# this return '<NA>', cool
str(pd.DataFrame(np.full((60, 1), pd.NA)))
# this return 'NaN', not cool
str(pd.DataFrame(np.full((61, 1), pd.NA)))
# It's just a problem of str, the entry is actually pd.NA
# this return '<NA>'
str(pd.DataFrame(np.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33066 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33066/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33066/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33066/events | https://github.com/pandas-dev/pandas/issues/33066 | 589,061,346 | MDU6SXNzdWU1ODkwNjEzNDY= | 33,066 | BUG: pd.NA acts differently when inside/outside a series/dataframe with object dtype | {
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```python
# return pd.NA, cool
pd.NA | pd.NA
# return False, not cool
pd.Series([pd.NA]) | pd.Series([pd.NA])
```
#### Problem description
pd.NA acts differently when inside/outside a series/dataframe may be confusing. It force me to handle each entry ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33067 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33067/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33067/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33067/events | https://github.com/pandas-dev/pandas/pull/33067 | 589,081,471 | MDExOlB1bGxSZXF1ZXN0Mzk0NzEwODY4 | 33,067 | BUG: Fix unwanted type casting while replacing values in a DataFrame | {
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"color": "e11... | closed | false | null | [] | null | 4 | 2020-03-27T11:54:17Z | 2020-06-14T21:37:18Z | 2020-05-11T09:17:24Z | MEMBER | null | - [x] closes #32988
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
As mentioned in #32988 [here](https://github.com/pandas-dev/pandas/issues/32988#issuecomment-604727057) I think, that I have found a way to fix this... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33068 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33068/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33068/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33068/events | https://github.com/pandas-dev/pandas/issues/33068 | 589,101,557 | MDU6SXNzdWU1ODkxMDE1NTc= | 33,068 | df.to_feather pandas: Failed to open local file, error: The requested operation cannot be performed on a file with a user-mapped section open. | {
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"... | closed | false | null | [] | null | 3 | 2020-03-27T12:31:25Z | 2020-04-01T11:56:45Z | 2020-04-01T11:56:44Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
# Your code here
df = pd.DataFrame({'Loan':["L1","L2"], 'Gender':["male","Female"], "income":[25000.324, 43422.2754]})
df
df['income'] = df['income'].round(decimals=2)
df = df.astype(dict(zip(['Gender'], ['category'])), copy = True)
df
df.to_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33069 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33069/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33069/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33069/events | https://github.com/pandas-dev/pandas/issues/33069 | 589,191,315 | MDU6SXNzdWU1ODkxOTEzMTU= | 33,069 | read_sas fails when passed a file object from GCSFS | {
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From https://stackoverflow.com/q/60848250/101923
```bash
export BUCKET_NAME=swast-scratch-us
curl -L https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DEMO_J.XPT | gsutil cp - gs://${BUCKET_NAME}/sas_sample/Nchs/Nhanes/2017-2018/DEMO_J.XPT
```
```python
import... | {
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"followers_url": "https://api.github.com/users/j... | 5 | 2020-03-27T15:14:19Z | 2020-04-07T14:09:48Z | 2020-04-07T01:23:30Z | CONTRIBUTOR | null | With GCSFS (and when a binary file buffer is passed in), the output from
the file read is `bytes`, not a Unicode `str`. The `encode` call is unnecessary
in this case.
- [x] closes #33069
- [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/33071 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33071/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33071/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33071/events | https://github.com/pandas-dev/pandas/issues/33071 | 589,248,180 | MDU6SXNzdWU1ODkyNDgxODA= | 33,071 | Why pd.BooleanDtype() is casted to Float64 by groupby/last? | {
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```
>>> import pandas as pd
>>>
>>> df = pd.DataFrame({'a': ['x', 'x', 'y', 'y'], 'b': ['x', 'x', 'y', 'y'], 'c': [False, False, True, False]})
>>> df['d'] = df.c.astype(pd.BooleanDtype())
>>>
>>> df.dtypes
a object
b object
c bool
d bo... | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
Should I add a whatsnew entry? It's not really new, if it is backported to 1.0.1. | {
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**But once i push the notebook in Github the rendering does not work ... | {
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https://dev.azure.com/pandas-dev/pandas/_build/results?buildId=31733&view=logs&j=a3a13ea8-7cf0-5bdb-71bb-6ac8830ae35c&t=add65f64-6c25-5783-8fd6-d9aa1b63d9d4&l=115.
There was an s3fs release earlier today, if that's related.
```pytb
2... | {
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---
Closes #31407 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33082 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33082/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33082/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33082/events | https://github.com/pandas-dev/pandas/issues/33082 | 589,450,711 | MDU6SXNzdWU1ODk0NTA3MTE= | 33,082 | Accessing DataFrame with DatetimeIndex behaves unexpectedly with reverse chronological ordered data | {
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When a Panda's DataFrame with a DatetimeIndex is in reverse chronological order accessing the data using the .loc method does not work unless the range is _also_ in reverse order.
#### Code Sample
```python
import pandas as pd
data = [
("2020-03-25 12:00:00", "A"),
("2020-03... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33083 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33083/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33083/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33083/events | https://github.com/pandas-dev/pandas/pull/33083 | 589,460,263 | MDExOlB1bGxSZXF1ZXN0Mzk1MDA4NzU1 | 33,083 | CLN: avoid internals, some misc cleanups | {
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- [x] closes #32580
- [x] closes #33545 (is a duplicate of 32580)
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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The issue was the concatenation with an empty DataFrame and the result of the min function... | {
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It appears currently impossible (unless I'm mistaken) to specify what pickle protocol will be used by `DataFrame.to_hdf()` (and thus by `PyTables`) if pickling is necessary. That makes it impossible to share HDF5 data written and read by a mix of clients running py37 and py38.
In Python 3... | {
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```python
import pandas as pd
df = pd.DataFrame({"a": [1, 2, 3]})
df["b"] = df["a"].astype("category")
print(df.groupby("a")["b"].first())
print(df.groupby("a")["b"].last())
```
gives
```python
a
1 1
2 2
3 3
Name: b, dtype: int64
a
1 1
2 2
3 3
Name: b, dtype... | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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- [ ] tests added / passed
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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Related to #27977. | {
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```python
# DateOffset creation and string representation
off = pd.tseries.frequencies.to_offset('2MS')
off.freqstr
>>> Out[20]: '2MS'
# Timedelta creation from DateOffset string representation
td = pd.to_timedelta(off.freqstr)
td
>>> Out[21] Timedelta(... | {
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```python
# somewhere
rolling = df.rolling(7, win_type="bartlett")
#somewhere else
plot( rolling._get_window( win_type=rolling.win_type) )
```
#### Problem description
Sometime you receive a Rolling or Window from somewhere and want, e.g. plot its sh... | {
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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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import xlsxwriter
cars = {'Brand': ['Honda Civic','Toyota Corolla','Ford Focus','Audi A8'],
'Price': [22000,25000,27000,35000]}
df = pd.DataFrame(cars, columns = ['Brand', 'Price'])
def add():
ans = input ("Want to add more data.?(y/n):")
if (ans=='y'):
car_... | {
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- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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This PR is a continuation of #32937 (made an error when pulling changes from the master).
I had a more elaborate decision tree for wh... | {
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Some group by functions lost the column index name. For the functions running into ```_get_cythonized_result``` in groupby.py, the index name was j... | {
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```python
import pandas as pd
pd.DataFrame().astype(pd.SparseDtype(float))
```
#### Problem description
Converting an empty dataframe to a sparse representation leads to a `ValueError`.
```
ValueError: No objects to concatenate
```
#### Expected Ou... | {
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```python
>>> import pandas as pd
>>> s = pd.Series([1, 2])
>>> df = pd.Data... | {
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on master
```
>>> import numpy as np
>>> import pandas as pd
>>>
>>> pd.__version__
'1.1.0.dev0+1008.g60b0e9fbc'
>>>
>>> cat = pd.Categorical(["a", "b", "c", "b"], ordered=False)
>>> cat
[a, b, c, b]
Categories (3, object): [a, b, c]
>>>
>>> np.min(cat)
Traceback (most recent call last):
... | {
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