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] | closed | false | null | [] | null | 6 | 2019-11-01T00:25:34Z | 2021-11-20T05:42:16Z | 2021-11-20T05:42:16Z | CONTRIBUTOR | null | Running the following:
```scripts/validate_docstrings.py --errors=SS03```
returns the following instances of cases where the Summary doesn't end with a period.
SS03 is one of the pending docstring-related errors as mentioned in #27977
- [ ] pandas.tseries.frequencies.to_offset: Summary does not end with a period
- [ ] pandas.Int64Index: Summary does not end with a period
- [ ] pandas.UInt64Index: Summary does not end with a period
- [ ] pandas.Float64Index: Summary does not end with a period
- [ ] pandas.IntervalIndex.left: Summary does not end with a period
- [ ] pandas.IntervalIndex.right: Summary does not end with a period
- [ ] pandas.IntervalIndex.mid: Summary does not end with a period
- [ ] pandas.IntervalIndex.closed: Summary does not end with a period
- [ ] pandas.IntervalIndex.length: Summary does not end with a period
- [ ] pandas.io.stata.StataReader.data: Summary does not end with a period
- [ ] pandas.plotting.plot_params: Summary does not end with a period
- [ ] pandas.io.formats.style.Styler.loader: Summary does not end with a period
- [ ] pandas.Timestamp.combine: Summary does not end with a period
- [ ] pandas.Timestamp.fromordinal: Summary does not end with a period
- [ ] pandas.Timestamp.isoweekday: Summary does not end with a period
- [ ] pandas.Timestamp.weekday: Summary does not end with a period
- [ ] pandas.Period.strftime: Summary does not end with a period
- [ ] pandas.Interval.closed: Summary does not end with a period
- [ ] pandas.Interval.left: Summary does not end with a period
- [ ] pandas.Interval.length: Summary does not end with a period
- [ ] pandas.Interval.mid: Summary does not end with a period
- [ ] pandas.Interval.right: Summary does not end with a period
The way to go about resolving this issue with such a large number of files has been nicely setup by @datapythonista in #27977 itself. Quoting from the issue:
_**> VERY IMPORTANT
The main challenge will be not repeating the same work as other sprinters, which is very frustrating, and happened massively at every sprint. My recommendation is BEFORE doing any work, to create an issue for the error code you plan to work on (check that it hasn't already been created). In the error write the list of errors that validate_docstrings.py returns. Then in a comment, take 10 of them, and write that you're going to fix them. Other people can work on a different 10. When opening a PR, reference the issue.**_
[UPDATE 1]
List has been updated after @datapythonista's recommendation to remove the ones starting with ```pandas.tseries.offsets``` .
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} | 5 | 2019-11-01T01:13:54Z | 2019-11-01T11:20:48Z | 2019-11-01T11:20:25Z | NONE | null | #### Code Sample, a copy-pastable example if possible
Updated without yfinance as it was a lousy choice of example - requires only standard numpy and datetime. A DateTimeIndex exacerbates the time slowness.
```python
import timeit
timeit.timeit(stmt='for x in range(len(hist)): _ = hist.iloc[x].Col1', setup='import numpy as np; import pandas as pd; col = np.random.uniform(low=-1, high=1, size=(10000)); hist = pd.DataFrame({"Col1":col,"Col2":col,"Col3":col,"Col4":col,"Col5":col})', number=3)
#3.553613900000073
timeit.timeit(stmt='for x in range(len(hist)): _ = hist.Col1[x]', setup='import numpy as np; import pandas as pd; col = np.random.uniform(low=-1, high=1, size=(10000)); hist = pd.DataFrame({"Col1":col,"Col2":col,"Col3":col,"Col4":col,"Col5":col})', number=3)
#0.5215671999999358
timeit.timeit(stmt='for x in range(len(hist)): _ = hist.iloc[x].Col1', setup='import datetime; import numpy as np; import pandas as pd; col = np.random.uniform(low=-1, high=1, size=(10000)); hist = pd.DataFrame({"Col1":col,"Col2":col,"Col3":col,"Col4":col,"Col5":col}, [datetime.datetime.now() + datetime.timedelta(seconds=x) for x in range(10000)])', number=3)
#4.485623600000508
timeit.timeit(stmt='for x in range(len(hist)): _ = hist.Col1[x]', setup='import datetime; import numpy as np; import pandas as pd; col = np.random.uniform(low=-1, high=1, size=(10000)); hist = pd.DataFrame({"Col1":col,"Col2":col,"Col3":col,"Col4":col,"Col5":col}, [datetime.datetime.now() + datetime.timedelta(seconds=x) for x in range(10000)])', number=3)
#0.7185356999998476
```
~~Old code example:~~
~~#requires pip install yfinance for this example - could substitute with any data set~~
~~timeit.timeit(stmt='for x in range(len(hist)): _ = hist.iloc[x].Close', setup='import yfinance as yf; hist = yf.Ticker("MSFT").history(period="max")', number=3)~~
~~#5.178573199999846~~
~~timeit.timeit(stmt='for x in range(len(hist)): _ = hist.iloc[x].Close', setup='import yfinance as yf; hist = yf.Ticker("MSFT").history(period="max")', number=3)~~
~~#0.5886300999998184~~
#### Problem description
One would naturally expect iloc to have close to identical efficiency as column indexing. This is a dramatic blunder in a lot of code more than likely if it is not well documented and known. I would expect some strange inefficiency is present as logically it could be slightly slower to return a row rather than a data point. But 10 times slower is so dramatic that this function should be avoided.
#### Expected Output
Less than double the speed of single column value access. Or at least thorough documentation of this limitation.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en
LOCALE : None.None
pandas : 0.25.1
numpy : 1.16.5
pytz : 2019.3
dateutil : 2.8.0
pip : 19.2.3
setuptools : 41.4.0
Cython : 0.29.13
pytest : 5.2.1
hypothesis : None
sphinx : 2.2.0
blosc : None
feather : None
xlsxwriter : 1.2.1
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.8.0
pandas_datareader: None
bs4 : 4.8.0
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : 1.3.9
tables : 3.5.2
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.1
</details>
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} | 5 | 2019-11-01T07:40:33Z | 2019-11-20T05:26:02Z | 2019-11-20T05:13:38Z | CONTRIBUTOR | null | - [x] closes #26632
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/29318 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29318/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29318/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29318/events | https://github.com/pandas-dev/pandas/pull/29318 | 515,973,620 | MDExOlB1bGxSZXF1ZXN0MzM1MzIwMTg1 | 29,318 | CLN: Consistent imports - linting rules | {
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} | 1 | 2019-11-01T08:22:31Z | 2019-11-01T14:51:04Z | 2019-11-01T14:50:59Z | CONTRIBUTOR | null | - [x] closes #29272
- [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/29319 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29319/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29319/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29319/events | https://github.com/pandas-dev/pandas/issues/29319 | 515,996,967 | MDU6SXNzdWU1MTU5OTY5Njc= | 29,319 | unable to install pandas on python 3.8 [win10] | {
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} | [] | closed | false | null | [] | null | 0 | 2019-11-01T09:15:36Z | 2019-11-01T09:16:33Z | 2019-11-01T09:16:33Z | NONE | null | #### Problem description
I am using the latest 3.8 python
As you can see below, when I try to install pandas, I get an error. Could you please check
#### commands
```cmd
>python -V
Python 3.8.0
>pip -V
pip 19.0.3 from C:\Users\user\.virtualenvs\py38-....
>pip install pandas
Collecting pandas
Using cached https://files.pythonhosted.org/packages/42/cb/e3b69df7d3e6095a5e86fbe930e57f3f0a440fb73f350ab253efe2c7b924/pandas-0.25.2.tar.gz
Complete output from command python setup.py egg_info:
Could not locate executable g77
Could not locate executable f77
Could not locate executable ifort
Could not locate executable ifl
Could not locate executable f90
Could not locate executable efl
Could not locate executable gfortran
Could not locate executable f95
Could not locate executable g95
Could not locate executable efort
Could not locate executable efc
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
'svnversion' is not recognized as an internal or external command,
operable program or batch file.
non-existing path in 'numpy\\distutils': 'site.cfg'
Running from numpy source directory.
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py:418: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:690: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
self.calc_info()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:690: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
self.calc_info()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:690: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
self.calc_info()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:1712: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
if getattr(self, '_calc_info_{}'.format(lapack))():
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:1712: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
if getattr(self, '_calc_info_{}'.format(lapack))():
C:\Python\Python38\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
Traceback (most recent call last):
File "C:\Python\Python38\lib\distutils\core.py", line 148, in setup
dist.run_commands()
File "C:\Python\Python38\lib\distutils\dist.py", line 966, in run_commands
self.run_command(cmd)
File "C:\Python\Python38\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\bdist_egg.py", line 163, in run
File "C:\Python\Python38\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "C:\Python\Python38\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\egg_info.py", line 26, in run
File "C:\Python\Python38\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "C:\Python\Python38\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\build_src.py", line 142, in run
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\build_src.py", line 150, in build_sources
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\build_src.py", line 267, in build_py_modules_sources
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\misc_util.py", line 2270, in generate_config_py
File "C:\Python\Python38\lib\distutils\dir_util.py", line 70, in mkpath
os.mkdir(head, mode)
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 310, in wrap
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 452, in _remap_input
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 407, in _violation
setuptools.sandbox.SandboxViolation: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 154, in save_modules
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 195, in setup_context
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 250, in run_setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 45, in _execfile
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 443, in <module>
suffix = ".pyx"
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 435, in setup_package
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\core.py", line 171, in setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 145, in setup
File "C:\Python\Python38\lib\distutils\core.py", line 163, in setup
raise SystemExit("error: " + str(msg))
SystemExit: error: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 1144, in run_setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 253, in run_setup
File "C:\Python\Python38\lib\contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 195, in setup_context
File "C:\Python\Python38\lib\contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 166, in save_modules
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 141, in resume
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\_vendor\six.py", line 685, in reraise
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 154, in save_modules
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 195, in setup_context
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 250, in run_setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 45, in _execfile
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 443, in <module>
suffix = ".pyx"
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 435, in setup_package
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\core.py", line 171, in setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 145, in setup
File "C:\Python\Python38\lib\distutils\core.py", line 163, in setup
raise SystemExit("error: " + str(msg))
SystemExit: error: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\Users\user\AppData\Local\Temp\pip-install-5ewmgdou\pandas\setup.py", line 809, in <module>
setup(
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 144, in setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 139, in _install_setup_requires
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\dist.py", line 721, in fetch_build_eggs
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\pkg_resources\__init__.py", line 780, in resolve
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\pkg_resources\__init__.py", line 1065, in best_match
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\pkg_resources\__init__.py", line 1077, in obtain
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\dist.py", line 791, in fetch_build_egg
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 679, in easy_install
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 705, in install_item
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 890, in install_eggs
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 1158, in build_and_install
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 1146, in run_setup
distutils.errors.DistutilsError: Setup script exited with error: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in C:\Users\user\AppData\Local\Temp\pip-install-5ewmgdou\pandas\
```
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https://api.github.com/repos/pandas-dev/pandas/issues/29320 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29320/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29320/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29320/events | https://github.com/pandas-dev/pandas/issues/29320 | 515,998,157 | MDU6SXNzdWU1MTU5OTgxNTc= | 29,320 | Unable to install pandas on python 3.8 [Windows OS] | {
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{
"color": "75507B",
"default": false,
"description": "Library building on various platforms",
"id": 129350,
"name": "Build",
"node_id": "MDU6TGFiZWwxMjkzNTA=",
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... | closed | false | null | [] | null | 4 | 2019-11-01T09:18:19Z | 2019-11-04T11:00:54Z | 2019-11-04T11:00:53Z | NONE | null | #### Problem description
I am using the latest 3.8 python
As you can see below, when I try to install pandas, I get an error. Could you please check
#### commands
```cmd
>python -V
Python 3.8.0
>pip -V
pip 19.0.3 from C:\Users\user\.virtualenvs\py38-....
>pip install pandas
Collecting pandas
Using cached https://files.pythonhosted.org/packages/42/cb/e3b69df7d3e6095a5e86fbe930e57f3f0a440fb73f350ab253efe2c7b924/pandas-0.25.2.tar.gz
Complete output from command python setup.py egg_info:
Could not locate executable g77
Could not locate executable f77
Could not locate executable ifort
Could not locate executable ifl
Could not locate executable f90
Could not locate executable efl
Could not locate executable gfortran
Could not locate executable f95
Could not locate executable g95
Could not locate executable efort
Could not locate executable efc
Could not locate executable flang
don't know how to compile Fortran code on platform 'nt'
'svnversion' is not recognized as an internal or external command,
operable program or batch file.
non-existing path in 'numpy\\distutils': 'site.cfg'
Running from numpy source directory.
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py:418: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:690: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
self.calc_info()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:690: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
self.calc_info()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:690: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
self.calc_info()
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:1712: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
if getattr(self, '_calc_info_{}'.format(lapack))():
C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\system_info.py:1712: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
if getattr(self, '_calc_info_{}'.format(lapack))():
C:\Python\Python38\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
Traceback (most recent call last):
File "C:\Python\Python38\lib\distutils\core.py", line 148, in setup
dist.run_commands()
File "C:\Python\Python38\lib\distutils\dist.py", line 966, in run_commands
self.run_command(cmd)
File "C:\Python\Python38\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\bdist_egg.py", line 163, in run
File "C:\Python\Python38\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "C:\Python\Python38\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\egg_info.py", line 26, in run
File "C:\Python\Python38\lib\distutils\cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "C:\Python\Python38\lib\distutils\dist.py", line 985, in run_command
cmd_obj.run()
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\build_src.py", line 142, in run
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\build_src.py", line 150, in build_sources
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\command\build_src.py", line 267, in build_py_modules_sources
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\misc_util.py", line 2270, in generate_config_py
File "C:\Python\Python38\lib\distutils\dir_util.py", line 70, in mkpath
os.mkdir(head, mode)
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 310, in wrap
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 452, in _remap_input
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 407, in _violation
setuptools.sandbox.SandboxViolation: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 154, in save_modules
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 195, in setup_context
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 250, in run_setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 45, in _execfile
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 443, in <module>
suffix = ".pyx"
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 435, in setup_package
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\core.py", line 171, in setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 145, in setup
File "C:\Python\Python38\lib\distutils\core.py", line 163, in setup
raise SystemExit("error: " + str(msg))
SystemExit: error: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 1144, in run_setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 253, in run_setup
File "C:\Python\Python38\lib\contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 195, in setup_context
File "C:\Python\Python38\lib\contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 166, in save_modules
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 141, in resume
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\_vendor\six.py", line 685, in reraise
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 154, in save_modules
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 195, in setup_context
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 250, in run_setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\sandbox.py", line 45, in _execfile
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 443, in <module>
suffix = ".pyx"
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\setup.py", line 435, in setup_package
File "C:\Users\user\AppData\Local\Temp\easy_install-tpb9vsra\numpy-1.17.3\numpy\distutils\core.py", line 171, in setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 145, in setup
File "C:\Python\Python38\lib\distutils\core.py", line 163, in setup
raise SystemExit("error: " + str(msg))
SystemExit: error: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\Users\user\AppData\Local\Temp\pip-install-5ewmgdou\pandas\setup.py", line 809, in <module>
setup(
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 144, in setup
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\__init__.py", line 139, in _install_setup_requires
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\dist.py", line 721, in fetch_build_eggs
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\pkg_resources\__init__.py", line 780, in resolve
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\pkg_resources\__init__.py", line 1065, in best_match
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\pkg_resources\__init__.py", line 1077, in obtain
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\dist.py", line 791, in fetch_build_egg
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 679, in easy_install
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 705, in install_item
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 890, in install_eggs
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 1158, in build_and_install
File "C:\Users\user\.virtualenvs\py38-pnl\lib\site-packages\setuptools-40.8.0-py3.8.egg\setuptools\command\easy_install.py", line 1146, in run_setup
distutils.errors.DistutilsError: Setup script exited with error: SandboxViolation: mkdir('C:\\Users\\user\\AppData\\Local\\Temp\\easy_install-tpb9vsra\\numpy-1.17.3\\build', 511) {}
The package setup script has attempted to modify files on your system
that are not within the EasyInstall build area, and has been aborted.
This package cannot be safely installed by EasyInstall, and may not
support alternate installation locations even if you run its setup
script by hand. Please inform the package's author and the EasyInstall
maintainers to find out if a fix or workaround is available.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in C:\Users\user\AppData\Local\Temp\pip-install-5ewmgdou\pandas\
```
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https://api.github.com/repos/pandas-dev/pandas/issues/29321 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29321/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29321/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29321/events | https://github.com/pandas-dev/pandas/issues/29321 | 516,133,647 | MDU6SXNzdWU1MTYxMzM2NDc= | 29,321 | Pandas dataframe sub-setting returns NaN's when whole column matches fill value | {
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{
"color": "009800",
"default": false,
"description": "Sparse Data Type",
"id": 49182326,
"name": "Sparse",
"node_id": "MDU6TGFiZWw0OTE4MjMyNg==",
"url": "https://api.github.com/repos/pandas-dev/pandas/labels/Sparse"
},
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"description"... | closed | false | null | [] | null | 8 | 2019-11-01T14:06:36Z | 2020-04-20T00:36:25Z | 2020-04-20T00:36:24Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import random
import numpy as np
import multiprocessing as mp
import pandas as pd
TEST_LINES = 10
samezeroint = [0 for i in range(TEST_LINES)]
sameoneint = [1 for i in range(TEST_LINES)]
samezerofloat = [0.0 for i in range(TEST_LINES)]
sameonefloat = [1.0 for i in range(TEST_LINES)]
indexone = [i for i in range(TEST_LINES)]
randomint = []
randomfloat = []
for i in range(TEST_LINES):
randomint.append(random.randint(0,100))
randomfloat.append(random.random())
testdict = {'indexone': indexone, "samezeroint": samezeroint, 'sameoneint': sameoneint, 'samezerofloat': samezerofloat, 'sameonefloat': sameonefloat, 'randomint': randomint, 'randomfloat': randomfloat}
filldict = {'indexone': 0, "samezeroint": 0, 'sameoneint': 1, 'samezerofloat': 0.0,
'sameonefloat': 1.0, 'randomint': random.randint(0,100), 'randomfloat': random.random()}
dtypedict = {'indexone': np.int8, "samezeroint": np.int8, 'sameoneint': np.int8, 'samezerofloat': np.float,
'sameonefloat': np.float, 'randomint': np.int8, 'randomfloat': np.float}
dospar = {}
for l in testdict:
try:
fill = filldict[l]
except KeyError:
fill = None
try:
datatype = dtypedict[l]
except KeyError:
datatype = np.str
if fill is None:
sparr = pd.Series(pd.array(testdict[l], dtype=datatype))
else:
sparr = pd.Series(pd.SparseArray(testdict[l], fill_value=fill, dtype=datatype))
dospar[l] = sparr
testdf = pd.DataFrame.from_dict(dospar, orient='columns')
# Test a single series
print("\n\nSeries: All zeroes")
samezerointseries = pd.Series(pd.SparseArray(testdict['samezeroint'], fill_value=0, dtype=np.int8))
print("\nOriginal")
print(samezerointseries)
samezero = samezerointseries.isin([0])
samezerozero = samezerointseries[samezero]
print("\nFiltered: should be identical to above")
print(samezerozero)
sameone = samezerointseries.isin([1])
samezeroone = samezerointseries[sameone]
print("\nFiltered: should be empty")
print(samezeroone)
print("\n\nDataframe:")
with pd.option_context('display.max_rows', None, 'display.max_columns',
None): # more options can be specified also
print(testdf)
print(testdf.dtypes)
print("\n\nDataframe: should be identical to above")
intone = testdf.loc[:, 'sameoneint'].isin([int(1)])
print(intone)
onedf = testdf[intone]
with pd.option_context('display.max_rows', None, 'display.max_columns',
None): # more options can be specified also
print(onedf)
print(onedf.dtypes)
```
#### Problem description
I've run into something odd with pandas data frames composed of sparse series. I am able to make the DF out of dictionaries of values with fills and types, no problem, but when I try to subset that DF, I get some very weird results. What I have been able to reproducibly show is that when subsetting a DF created out of Sparse series, if a column happens to be identical throughout (i.e. all entires match the fill value), the subset DF turns those columns into NaN's, and the dtype convert into float64.
When I run this test, I get the following result:
'''
Series: All zeroes
Original
0 0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
dtype: Sparse[int8, 0]
Filtered: should be identical to above
0 0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
dtype: Sparse[int8, 0]
Filtered: should be empty
Series([], dtype: Sparse[int8, 0])
Dataframe:
indexone samezeroint sameoneint samezerofloat sameonefloat randomint \
0 0 0 1 0.0 1.0 95
1 1 0 1 0.0 1.0 13
2 2 0 1 0.0 1.0 20
3 3 0 1 0.0 1.0 29
4 4 0 1 0.0 1.0 44
5 5 0 1 0.0 1.0 82
6 6 0 1 0.0 1.0 22
7 7 0 1 0.0 1.0 91
8 8 0 1 0.0 1.0 51
9 9 0 1 0.0 1.0 13
randomfloat densesamezero
0 0.989141 0
1 0.948800 0
2 0.504600 0
3 0.014699 0
4 0.979710 0
5 0.663198 0
6 0.773480 0
7 0.921397 0
8 0.898101 0
9 0.445575 0
indexone Sparse[int8, 0]
samezeroint Sparse[int8, 0]
sameoneint Sparse[int8, 1]
samezerofloat Sparse[float64, 0.0]
sameonefloat Sparse[float64, 1.0]
randomint Sparse[int8, 24]
randomfloat Sparse[float64, 0.08770512017933063]
densesamezero int64
dtype: object
Dataframe: should be identical to above
0 True
1 True
2 True
3 True
4 True
5 True
6 True
7 True
8 True
9 True
Name: sameoneint, dtype: bool
indexone samezeroint sameoneint samezerofloat sameonefloat randomint \
0 0 NaN NaN NaN NaN 95
1 1 NaN NaN NaN NaN 13
2 2 NaN NaN NaN NaN 20
3 3 NaN NaN NaN NaN 29
4 4 NaN NaN NaN NaN 44
5 5 NaN NaN NaN NaN 82
6 6 NaN NaN NaN NaN 22
7 7 NaN NaN NaN NaN 91
8 8 NaN NaN NaN NaN 51
9 9 NaN NaN NaN NaN 13
randomfloat densesamezero
0 0.989141 0
1 0.948800 0
2 0.504600 0
3 0.014699 0
4 0.979710 0
5 0.663198 0
6 0.773480 0
7 0.921397 0
8 0.898101 0
9 0.445575 0
indexone Sparse[int64, 0]
samezeroint Sparse[float64, 0]
sameoneint Sparse[float64, 1]
samezerofloat Sparse[float64, 0.0]
sameonefloat Sparse[float64, 1.0]
randomint Sparse[int8, 24]
randomfloat Sparse[float64, 0.08770512017933063]
densesamezero int64
dtype: object
As you can hopefully see, since I am subsetting "all rows where there is a 0 in the column that is all zeroes", I SHOULD be creating an identical DF - but instead only the Series where there is some variation in the column are preserved, the rest turn into all-NaNs.
For the subsetting command, I have tried every variant I could find:
newdf = testdf.loc[testdf['sameoneint'] == 1]
newdf =testdf.query('sameoneint == 1')
isone = testdf.loc[:, 'sameoneint'].isin([1])
newdf = testdf[isone]
None of those work any better, and some throw a warning about calling to_dense.
So, am I missing something in how I coded that, or is this something in how pandas works I have not yet figured out? Advice most welcome!
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.3.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-693.11.6.el7.x86_64
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.2
pytz : 2019.2
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : 3.5.2
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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} | 9 | 2019-11-01T16:58:09Z | 2019-11-04T15:01:32Z | 2019-11-04T14:59:30Z | MEMBER | null | cc @mroeschke since a lot of this touches libwindow | {
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https://api.github.com/repos/pandas-dev/pandas/issues/29323 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29323/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29323/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29323/events | https://github.com/pandas-dev/pandas/issues/29323 | 516,257,362 | MDU6SXNzdWU1MTYyNTczNjI= | 29,323 | pd.Series.apply can't be made to produce Series of expected dtype when base series is empty | {
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"color": "fbc... | closed | false | null | [] | null | 9 | 2019-11-01T17:47:44Z | 2019-11-06T23:14:40Z | 2019-11-06T23:14:39Z | NONE | null | #### Code Sample
```python
df = pd.DataFrame(data=[3], columns=['colA'], dtype=int)
print(df.colA.dtype)
#> dtype('int64')
# Here things are as expected. A `Series` of dtype=bool is produced
res = df.colA.apply(lambda row: True)
print(res.dtype)
#> dtype('bool')
df = pd.DataFrame(columns=['colA'], dtype=int)
print(df.colA.dtype)
#> dtype('int64')
# Here colA is empty. As a result, a `Series` of dtype=int64 is produced
res = df.colA.apply(lambda row: True)
print(res.dtype)
#> dtype('int64')
```
#### Problem description
May be related to #28427.
When calling `apply()` on a series, you expect to get back a series with a certain `dtype` based on the function you give it. However, if the base `Series` is empty, there is nothing to apply the function to, so the resultant `Series` just has the same `dtype` as the base.
My actual use case is more along the lines of this:
```python
import pandas as pd
import datetime
# Is a List[datetime.datetime], but could be empty
datetime_data = [datetime.datetime.now()]
# datetime_data = []
df = pd.DataFrame(data=[False for i in range(len(datetime_data))], columns=['colA'], index=pd.DatetimeIndex(datetime_data))
df['colB'] = df.index.to_series().apply(lambda x: True if x > datetime.datetime.now() else False)
start_dt = datetime.datetime.now() - datetime.timedelta(days=5)
end_dt = datetime.datetime.now() + datetime.timedelta(days=5)
new_dt_range = pd.date_range(start_dt, end_dt)
df = df.reindex(new_dt_range, fill_value=True)
# If you run this, it will work. But uncomment the empty list datetime_data, and you get:
#> TypeError: Cannot convert input [True] of type <type 'bool'> to Timestamp
```
I would have thought there would be a way to force the type of the return value of `.apply` even when the base vector is empty. You can obviously get around this easily by checking whether the base is empty when you assign `colB`:
```python
df['colB'] = df.index.to_series().apply(lambda row: True if row > datetime.datetime.now() else False) if not df.empty else True
```
Which coerces the `dtype` without setting any values, and that seems hacky and it feels like it should be possible to just make apply do the right thing.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.2.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 0.25.3
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.0
pip : 18.1
setuptools : 40.6.3
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.9.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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} | 2 | 2019-11-01T18:54:28Z | 2020-01-06T16:47:26Z | 2019-11-01T23:16:20Z | CONTRIBUTOR | null | fixing PR09 missing period formatting errors in various parameter descriptions.
Subset of #28602, mainly functions with single parameter's missing periods that didn't make sense to open an entire issue for.
I'm periodically updating the main issue for PR09 with the current list of errors remaining as they're removed. | {
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Looks like the file `web/pandas/about/index.html` has the wrong extension `.html`, since it's a markdown file and should be `.md`. This is causing that the file is not rendered as html but left untouched in the website: https://dev.pandas.io/about/index.html | {
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... | closed | false | null | [] | null | 3 | 2019-11-01T21:05:21Z | 2021-07-22T05:54:39Z | 2021-07-22T05:54:39Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
def store_data(self,table_path,data,append=True,data_columns=True):
pathComps = table_path.split("/")
table_name = pathComps[-1]
dbPath = pathComps[0:-1]
fullPath = os.path.join(self.databasePath,*dbPath)
tableStorePath = os.path.join(fullPath,table_name+".h5")
os.makedirs(fullPath, exist_ok=True)
data.to_hdf(tableStorePath, mode='a', key=table_name, format='table',append=append,data_columns=data_columns,complevel=9,complib='zlib')
```
this could be made in to a standalone function by just replacing `self.databasePath`, I.E:
```python
def store_data(diskPath,table_path,data,append=True,data_columns=True):
pathComps = table_path.split("/")
table_name = pathComps[-1]
dbPath = pathComps[0:-1]
fullPath = os.path.join(diskPath,*dbPath)
tableStorePath = os.path.join(fullPath,table_name+".h5")
os.makedirs(fullPath, exist_ok=True)
data.to_hdf(tableStorePath, mode='a', key=table_name, format='table',append=append,data_columns=data_columns,complevel=9,complib='zlib')
```
#### Problem description
I have a small class that I use to manage some data that I'm working with. I use it to translate a "hdf path" in to an actual on-disk file since storing all the data in one file just ends up being a mess that keeps growing as I debug.
At any rate - it seems when I use `df.to_hdf()`, the target path is on an external drive, and the file does not yet exist, that I get an error saying that the files could not be created (Even though they are and can be seen on disk). Re-running once all the files to be created exist seems to allow the code to run normally. I've only tested this by continually re-running until the files are all created - I'm not sure if using `touch` or similar would have the same effect.
Conversely - running the same commands on my internal disk works fine with no code modification.
I seem to reliably encounter this under MacOS 10.15. I feel like I also encountered this under Windows 10, but it didn't occur to me at the time that it was anything other than a mistake on my part, so I don't have info from that case.
#### Traceback:
```
Traceback (most recent call last):
File "./field.py", line 39, in <module>
main()
File "./field.py", line 31, in main
aman.store_data((some path),rawField.stack())
File "/Users/(me)/Documents/PhD/DataProcessing/modules/datamanager/archivemanager.py", line 72, in store_data
data.to_hdf(tableStorePath, mode='a', key=table_name, format='table',append=append,data_columns=data_columns,complevel=9,complib='zlib')
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/pandas/core/generic.py", line 2530, in to_hdf
pytables.to_hdf(path_or_buf, key, self, **kwargs)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/pandas/io/pytables.py", line 278, in to_hdf
f(store)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/pandas/io/pytables.py", line 269, in <lambda>
f = lambda store: store.append(key, value, **kwargs)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/pandas/io/pytables.py", line 1059, in append
self._write_to_group(key, value, append=append, dropna=dropna, **kwargs)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/pandas/io/pytables.py", line 1528, in _write_to_group
s.create_index(columns=index)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/pandas/io/pytables.py", line 3650, in create_index
v.create_index(**kw)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/table.py", line 3602, in create_index
tmp_dir, _blocksizes, _verbose)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/table.py", line 314, in _column__create_index
blocksizes=blocksizes)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/index.py", line 395, in __init__
super(Index, self).__init__(parentnode, name, title, new, filters)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/group.py", line 235, in __init__
super(Group, self).__init__(parentnode, name, _log)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/node.py", line 273, in __init__
self._g_post_init_hook()
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/index.py", line 549, in _g_post_init_hook
self.create_temp()
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/index.py", line 1012, in create_temp
self.tmpfile = self._openFile(self.tmpfilename, "w")
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/file.py", line 315, in open_file
return File(filename, mode, title, root_uep, filters, **kwargs)
File "/Users/(me)/.python/dataproc/lib/python3.7/site-packages/tables/file.py", line 778, in __init__
self._g_new(filename, mode, **params)
File "tables/hdf5extension.pyx", line 492, in tables.hdf5extension.File._g_new
tables.exceptions.HDF5ExtError: HDF5 error back trace
File "H5F.c", line 444, in H5Fcreate
unable to create file
File "H5Fint.c", line 1531, in H5F_open
unable to truncate a file which is already open
End of HDF5 error back trace
Unable to open/create file '/Volumes/(ExtDrive)/Data/archives/4CamPeriscope/fields/pytables-axuuju27.tmp'
```
#### Expected Output
#### Output of ``pd.show_versions()``
<details>
Python 3.7.3 (default, Sep 5 2019, 17:14:41)
[Clang 11.0.0 (clang-1100.0.33.8)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
>>> pd.show_versions()
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.0.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.2
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3
setuptools : 40.8.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.8.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : 3.6.0
xarray : 0.14.0
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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} | 4 | 2019-11-01T21:31:05Z | 2019-11-02T15:11:56Z | 2019-11-02T14:25:57Z | MEMBER | null | When I run `mypy pandas` locally I get a handful of complaints. This fixes about half of them. The other half are about `FixedOffset` which IIRC we are handling elsewhere.
cc @simonjayhawkins | {
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} | 7 | 2019-11-01T22:00:23Z | 2019-11-04T13:50:14Z | 2019-11-04T13:50:14Z | CONTRIBUTOR | null | Docstring for TO_CSV from my repo
> compression : str, default 'infer'
Compression mode among the following possible values: {'infer',
'gzip', 'bz2', 'zip', 'xz', None}. If 'infer' and `path_or_buf`
is path-like, then detect compression from the following
extensions: '.gz', '.bz2', '.zip' or '.xz'. (otherwise no
compression).
.. versionchanged:: 0.24.0
'infer' option added and set to default.
Docstring for TO_CSV from pandas
> compression : str or dict, default 'infer'
If str, represents compression mode. If dict, value at 'method' is
the compression mode. Compression mode may be any of the following
possible values: {'infer', 'gzip', 'bz2', 'zip', 'xz', None}. If
compression mode is 'infer' and `path_or_buf` is path-like, then
detect compression mode from the following extensions: '.gz',
'.bz2', '.zip' or '.xz'. (otherwise no compression). If dict given
and mode is 'zip' or inferred as 'zip', other entries passed as
additional compression options.
.. versionchanged:: 0.25.0
May now be a dict with key 'method' as compression mode
and other entries as additional compression options if
compression mode is 'zip'.
#### Problem description
Possibly a misunderstaning of documenentation, but based on how it reads I assumed it was released.
TO_CSV has a new compression functionality to accept dictionary with METHOD type and Archive Name, in source repo doc string for TO_CSV says functionality was added to .25.0, but my docstring for TO_CSV doesn't reflect that as shown above.
I'm using a fresh install of Python + Pandas
#### Expected Output
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.8.0.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
pandas : 0.25.3
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.0
pip : 19.2.3
setuptools : 41.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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} | 5 | 2019-11-01T22:35:44Z | 2019-11-04T23:09:41Z | 2019-11-04T21:00:16Z | CONTRIBUTOR | null | - [β] closes #29325
- [β] whatsnew: the about/index.html file is now about/index.md
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} | 1 | 2019-11-01T23:49:33Z | 2019-11-06T18:12:51Z | 2019-11-06T18:12:51Z | MEMBER | null | Noticed this when rebuilding dev environment from scratch, but our current conda specification results in an UnsatisfiableError
<details>
```sh
$ conda env create -f environment.yml
Collecting package metadata (repodata.json): done
Solving environment: \
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Package requests conflicts for:
sphinx -> requests[version='>2.0.0|>=2.0.0|>=2.5.0']
moto -> requests[version='>=2.0|>=2.5']
Package pandas conflicts for:
pyreadstat -> pandas
seaborn -> pandas[version='>=0.14.0']
xarray -> pandas[version='>=0.18.0|>=0.19.2']
statsmodels -> pandas[version='>=0.14']
fastparquet[version='>=0.2.1'] -> pandas[version='>=0.19']
Package python conflicts for:
xlsxwriter -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
flake8-comprehensions -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=3.4|>=3.5']
pycodestyle -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
numexpr[version='>=2.6.8'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
nbconvert[version='>=5.4.1'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pyyaml -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
numpydoc[version='>=0.9.0'] -> python
asv -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
boto3 -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
cython[version='>=0.29.13'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0']
html5lib -> python[version='2.7.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
requests -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
scipy[version='>=1.1'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
ipywidgets -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
botocore[version='>=1.11'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
xarray -> python[version='>=2.7,<2.8.0a0|>=3.5|>=3.5,<3.6.0a0|>=3.5.3|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
matplotlib[version='>=2.2.2'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pytz -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
ipython[version='>=5.6.0'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pytest[version='>=4.0.2'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0']
pytest-mock -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
dask-core -> python[version='>=2.7,<2.8.0a0|>=3.5|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
notebook[version='>=5.7.5'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
cpplint -> python
lxml -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
s3fs -> python[version='>=2.7,<2.8.0a0|>=3.5|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
fsspec[version='>=0.5.1'] -> python[version='>=3.5']
mypy -> python[version='>=3.4|>=3.5|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
seaborn -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
jinja2 -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
ipykernel -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pytables[version='>=3.4.2'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
xlwt -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
isort -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pyreadstat -> python[version='>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
sphinx -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
fastparquet[version='>=0.2.1'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
toolz[version='>=0.7.3'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
numpy[version='>=1.15'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
flake8-rst[version='>=0.6.0,<=0.7.0'] -> python
nbformat -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pytest-cov -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pytest-xdist -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
markdown -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
openpyxl -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
partd[version='>=0.3.10'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
nbsphinx -> python[version='2.7.*|3.4.*|3.5.*|3.6.*|>=3.5']
feedparser -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0']
odfpy -> python[version='2.7.*|3.5.*|3.6.*']
sqlalchemy -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pip -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0']
gitpython -> python[version='>=2.7,<2.8.0a0|>=3|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
hypothesis[version='>=3.82'] -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
bottleneck[version='>=1.2.1'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
flake8 -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
pyqt[version='>=5.9.2'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
black -> python[version='>=3.6']
xlrd -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
statsmodels -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
python-dateutil[version='>=2.6.1'] -> python[version='2.7.*|3.5.*|3.6.*|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
beautifulsoup4[version='>=4.6.0'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0']
moto -> python
cloudpickle[version='>=0.2.1'] -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
python-snappy -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
Package docutils conflicts for:
sphinx -> docutils[version='>=0.11|>=0.12']
botocore[version='>=1.11'] -> docutils[version='>=0.10,<0.16|>=0.10|>=0.10,<0.15']
nbsphinx -> docutils
Package atomicwrites conflicts for:
pytest[version='>=4.0.2'] -> atomicwrites[version='>=1.0']
Package boto conflicts for:
moto -> boto[version='>=2.36.0']
Package functools32 conflicts for:
flake8 -> functools32
matplotlib[version='>=2.2.2'] -> functools32
Package packaging conflicts for:
pytest[version='>=4.0.2'] -> packaging
sphinx -> packaging
Package six conflicts for:
fastparquet[version='>=0.2.1'] -> six
html5lib -> six[version='>=1.9']
pytables[version='>=3.4.2'] -> six
pytest-xdist -> six
python-dateutil[version='>=2.6.1'] -> six[version='>=1.5']
pytest[version='>=4.0.2'] -> six[version='>=1.10.0']
asv -> six
moto -> six
sphinx -> six[version='>=1.5']
Package prometheus_client conflicts for:
notebook[version='>=5.7.5'] -> prometheus_client
Package enum34 conflicts for:
flake8 -> enum34
hypothesis[version='>=3.82'] -> enum34
Package pyparsing conflicts for:
matplotlib[version='>=2.2.2'] -> pyparsing
Package * conflicts for:
scipy[version='>=1.1'] -> *[track_features=nomkl]
Package numpy conflicts for:
pytables[version='>=3.4.2'] -> numpy[version='>=1.11.3,<2.0a0|>=1.9.3,<2.0a0']
xarray -> numpy[version='>=1.11|>=1.12']
matplotlib[version='>=2.2.2'] -> numpy
seaborn -> numpy[version='>=1.9.3']
fastparquet[version='>=0.2.1'] -> numpy[version='>=1.11.3,<2.0a0']
statsmodels -> numpy[version='>=1.11.3,<2.0a0|>=1.9.3,<2.0a0']
scipy[version='>=1.1'] -> numpy[version='>=1.11.3,<2.0a0|>=1.15.1,<2.0a0|>=1.9.3,<2.0a0']
bottleneck[version='>=1.2.1'] -> numpy[version='>=1.11.3,<2.0a0|>=1.9.3,<2.0a0']
numexpr[version='>=2.6.8'] -> numpy[version='>=1.11.3,<2.0a0|>=1.15.4,<2.0a0|>=1.16.4,<2.0a0']
Package alabaster conflicts for:
sphinx -> alabaster[version='>=0.7,<0.8']
Package nbformat conflicts for:
nbsphinx -> nbformat
ipywidgets -> nbformat[version='>=4.2.0']
nbconvert[version='>=5.4.1'] -> nbformat[version='>=4.4']
notebook[version='>=5.7.5'] -> nbformat
Package mock conflicts for:
pytables[version='>=3.4.2'] -> mock
pytest-mock -> mock
moto -> mock
Package pygments conflicts for:
sphinx -> pygments[version='>2.0|>=2.0']
ipython[version='>=5.6.0'] -> pygments
nbconvert[version='>=5.4.1'] -> pygments
Package sip conflicts for:
pyqt[version='>=5.9.2'] -> sip[version='>=4.19.4,<=4.19.8']
Package libpng conflicts for:
matplotlib[version='>=2.2.2'] -> libpng[version='>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0|>=1.6.36,<1.7.0a0|>=1.6.37,<1.7.0a0']
Package kiwisolver conflicts for:
matplotlib[version='>=2.2.2'] -> kiwisolver
Package pandocfilters conflicts for:
nbconvert[version='>=5.4.1'] -> pandocfilters[version='>=1.4.1']
Package pip conflicts for:
python=3 -> pip
Package responses conflicts for:
moto -> responses[version='>=0.9.0']
Package pytest-faulthanlder conflicts for:
pytest[version='>=4.0.2'] -> pytest-faulthanlder[version='>=2']
Package pyflakes conflicts for:
flake8 -> pyflakes[version='>=1.5.0,<1.6.0|>=1.5.0,<1.7.0|>=2.0.0,<2.1.0|>=2.1.0,<2.2.0']
Package cycler conflicts for:
matplotlib[version='>=2.2.2'] -> cycler[version='>=0.10']
Package setuptools conflicts for:
cython[version='>=0.29.13'] -> setuptools
pytest-cov -> setuptools
markdown -> setuptools
asv -> setuptools
jinja2 -> setuptools
flake8 -> setuptools[version='>=30.0.0']
isort -> setuptools
matplotlib[version='>=2.2.2'] -> setuptools
sphinx -> setuptools
pytest[version='>=4.0.2'] -> setuptools[version='>=40.0']
pip -> setuptools
Package bleach conflicts for:
nbconvert[version='>=5.4.1'] -> bleach
Package soupsieve conflicts for:
beautifulsoup4[version='>=4.6.0'] -> soupsieve[version='>=1.2']
Package zlib conflicts for:
pyreadstat -> zlib[version='>=1.2.11,<1.3.0a0']
blosc -> zlib[version='>=1.2.11,<1.3.0a0']
matplotlib[version='>=2.2.2'] -> zlib[version='>=1.2.11,<1.3.0a0']
python=3 -> zlib[version='>=1.2.11,<1.3.0a0']
pytables[version='>=3.4.2'] -> zlib[version='>=1.2.11,<1.3.0a0']
Package flask conflicts for:
moto -> flask
Package bzip2 conflicts for:
pytables[version='>=3.4.2'] -> bzip2[version='>=1.0.6,<2.0a0']
Package jupyter_core conflicts for:
nbconvert[version='>=5.4.1'] -> jupyter_core
notebook[version='>=5.7.5'] -> jupyter_core[version='>=4.4.0']
nbformat -> jupyter_core
Package openssl conflicts for:
python=3 -> openssl[version='1.0.*|1.0.*,>=1.0.2l,<1.0.3a|>=1.0.2m,<1.0.3a|>=1.0.2n,<1.0.3a|>=1.0.2o,<1.0.3a|>=1.0.2p,<1.0.3a|>=1.1.1a,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1d,<1.1.2a']
Package sphinxcontrib-htmlhelp conflicts for:
sphinx -> sphinxcontrib-htmlhelp
Package jsonschema conflicts for:
nbformat -> jsonschema[version='>=2.4,!=2.5.0']
Package backports.shutil_get_terminal_size conflicts for:
ipython[version='>=5.6.0'] -> backports.shutil_get_terminal_size
Package pathlib2 conflicts for:
ipython[version='>=5.6.0'] -> pathlib2
pytest[version='>=4.0.2'] -> pathlib2[version='>=2.2.0']
Package mkl_fft conflicts for:
numpy[version='>=1.15'] -> mkl_fft[version='>=1.0.4|>=1.0.6,<2.0a0']
Package tornado conflicts for:
ipykernel -> tornado[version='>=4.0|>=4.2']
notebook[version='>=5.7.5'] -> tornado[version='>=4.1,<7|>=5.0,<7']
matplotlib[version='>=2.2.2'] -> tornado
Package mypy_extensions conflicts for:
mypy -> mypy_extensions[version='>=0.4.0,<0.5.0']
Package libopenblas conflicts for:
numexpr[version='>=2.6.8'] -> libopenblas[version='>=0.3.2,<0.3.3.0a0|>=0.3.3,<1.0a0']
numpy[version='>=1.15'] -> libopenblas[version='>=0.3.2,<0.3.3.0a0|>=0.3.3,<1.0a0']
scipy[version='>=1.1'] -> libopenblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.2,<0.3.3.0a0|>=0.3.3,<1.0a0']
Package scipy conflicts for:
statsmodels -> scipy[version='>=0.14']
seaborn -> scipy[version='>=0.15.2']
Package typing conflicts for:
mypy -> typing[version='>=3.5.3']
flake8 -> typing
sphinx -> typing
Package pytest conflicts for:
pytest-cov -> pytest[version='>=3.6']
pytest-xdist -> pytest[version='>=3.0.0|>=4.4.0']
fastparquet[version='>=0.2.1'] -> pytest
pytest-mock -> pytest[version='>=2.7']
Package execnet conflicts for:
pytest-xdist -> execnet[version='>=1.1']
Package pandoc conflicts for:
nbconvert[version='>=5.4.1'] -> pandoc[version='>=1.12.1|>=1.12.1,<2.0.0']
Package psutil conflicts for:
mypy -> psutil[version='>=4.0|>=5.4.0,<5.5.0']
Package sphinxcontrib-websupport conflicts for:
sphinx -> sphinxcontrib-websupport
Package wheel conflicts for:
pip -> wheel
Package tk conflicts for:
python=3 -> tk[version='8.6.*|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0']
Package ipython conflicts for:
ipykernel -> ipython[version='>=4.0|>=4.0.0|>=5.0']
ipywidgets -> ipython[version='>=4.0.0']
Package simplegeneric conflicts for:
ipython[version='>=5.6.0'] -> simplegeneric[version='>0.8']
Package funcsigs conflicts for:
pytest[version='>=4.0.2'] -> funcsigs[version='>=1.0']
Package locket conflicts for:
partd[version='>=0.3.10'] -> locket
Package ipykernel conflicts for:
ipywidgets -> ipykernel[version='>=4.5.1']
notebook[version='>=5.7.5'] -> ipykernel
Package python-dateutil conflicts for:
moto -> python-dateutil
matplotlib[version='>=2.2.2'] -> python-dateutil
botocore[version='>=1.11'] -> python-dateutil[version='>=2.1,<3.0.0']
Package xz conflicts for:
python=3 -> xz[version='>=5.2.3,<6.0a0|>=5.2.4,<6.0a0']
Package sphinxcontrib-qthelp conflicts for:
sphinx -> sphinxcontrib-qthelp
Package markupsafe conflicts for:
jinja2 -> markupsafe[version='>=0.23']
Package flake8 conflicts for:
flake8-rst[version='>=0.6.0,<=0.7.0'] -> flake8[version='>=3.5.0']
flake8-comprehensions -> flake8[version='!=3.2.0|>=3.0,!=3.2.0,<4.0']
Package statsmodels conflicts for:
seaborn -> statsmodels[version='>=0.5.0']
Package ipaddress conflicts for:
notebook[version='>=5.7.5'] -> ipaddress
Package patsy conflicts for:
seaborn -> patsy
statsmodels -> patsy[version='>=0.4.0']
Package lz4-c conflicts for:
blosc -> lz4-c[version='>=1.8.1.2,<1.9.0a0']
Package botocore conflicts for:
boto3 -> botocore[version='>=1.10.24,<1.11.0|>=1.10.32,<1.11.0|>=1.10.4,<1.11.0|>=1.10.45,<1.11.0|>=1.10.62,<1.11.0|>=1.11.2,<1.12.0|>=1.12.111,<1.13.0|>=1.12.13,<1.13.0|>=1.12.134,<1.13.0|>=1.12.162,<1.13.0|>=1.12.199,<1.13.0|>=1.12.21,<1.13.0|>=1.12.234,<1.13.0|>=1.12.35,<1.13.0|>=1.12.66,<1.13.0|>=1.12.7,<1.13.0|>=1.12.82,<1.13.0|>=1.7.0,<1.8.0|>=1.8.0,<1.9.0|>=1.8.46,<1.9.0|>=1.9.18,<1.10.0']
moto -> botocore[version='<1.11|>=1.12.13']
Package jinja2 conflicts for:
nbconvert[version='>=5.4.1'] -> jinja2
sphinx -> jinja2[version='>=2.3']
nbsphinx -> jinja2
moto -> jinja2[version='>=2.7.3|>=2.8']
notebook[version='>=5.7.5'] -> jinja2
Package testpath conflicts for:
nbconvert[version='>=5.4.1'] -> testpath
Package mkl conflicts for:
numexpr[version='>=2.6.8'] -> mkl[version='>=2018.0.3,<2019.0a0|>=2019.1,<2020.0a0|>=2019.4,<2020.0a0']
scipy[version='>=1.1'] -> mkl[version='>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2020.0a0|>=2019.4,<2020.0a0']
numpy[version='>=1.15'] -> mkl[version='>=2018.0.3,<2019.0a0|>=2019.1,<2020.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0']
Package readline conflicts for:
python=3 -> readline[version='7.*|>=7.0,<8.0a0']
Package s3transfer conflicts for:
boto3 -> s3transfer[version='>=0.1.10,<0.2.0|>=0.2.0,<0.3.0']
Package pytz conflicts for:
matplotlib[version='>=2.2.2'] -> pytz
moto -> pytz
Package coverage conflicts for:
pytest-cov -> coverage[version='>=4.4']
Package sqlite conflicts for:
python=3 -> sqlite[version='>=3.20.1,<4.0a0|>=3.22.0,<4.0a0|>=3.23.1,<4.0a0|>=3.24.0,<4.0a0|>=3.25.2,<4.0a0|>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.27.2,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0']
Package zstd conflicts for:
blosc -> zstd[version='>=1.3.7,<1.3.8.0a0']
Package backports.functools_lru_cache conflicts for:
matplotlib[version='>=2.2.2'] -> backports.functools_lru_cache
isort -> backports.functools_lru_cache
Package sphinxcontrib-jsmath conflicts for:
sphinx -> sphinxcontrib-jsmath
Package nbconvert conflicts for:
nbsphinx -> nbconvert
notebook[version='>=5.7.5'] -> nbconvert
Package defusedxml conflicts for:
nbconvert[version='>=5.4.1'] -> defusedxml
odfpy -> defusedxml
Package docker-py conflicts for:
moto -> docker-py
Package numba conflicts for:
fastparquet[version='>=0.2.1'] -> numba[version='>=0.28']
Package blas conflicts for:
numexpr[version='>=2.6.8'] -> blas[version='*|1.0',build='openblas|mkl|openblas']
scipy[version='>=1.1'] -> blas[version='*|*|1.0',build='mkl|mkl|openblas|openblas']
numpy[version='>=1.15'] -> blas[version='*|1.0',build='openblas|mkl|openblas']
Package jdcal conflicts for:
openpyxl -> jdcal
Package certifi conflicts for:
requests -> certifi[version='>=2017.4.17']
Package terminado conflicts for:
notebook[version='>=5.7.5'] -> terminado[version='>=0.8.1']
Package boto3 conflicts for:
moto -> boto3[version='>=1.2.1,<1.8.0|>=1.6.15']
s3fs -> boto3
Package dbus conflicts for:
pyqt[version='>=5.9.2'] -> dbus[version='>=1.12.2,<2.0a0|>=1.13.2,<2.0a0']
Package freetype conflicts for:
matplotlib[version='>=2.2.2'] -> freetype[version='>=2.8,<2.9.0a0|>=2.9.1,<3.0a0']
Package jupyter_client conflicts for:
ipykernel -> jupyter_client
notebook[version='>=5.7.5'] -> jupyter_client[version='>=5.2.0|>=5.3.1']
Package pluggy conflicts for:
pytest[version='>=4.0.2'] -> pluggy[version='>=0.12,<1.0|>=0.7|>=0.9|>=0.9,!=0.10,<1.0']
Package matplotlib conflicts for:
seaborn -> matplotlib[version='>=1.4.3']
Package urllib3 conflicts for:
botocore[version='>=1.11'] -> urllib3[version='>=1.20,<1.24|>=1.20,<1.25|>=1.20,<1.26']
requests -> urllib3[version='>=1.21.1,<1.22|>=1.21.1,<1.23|>=1.21.1,<1.24|>=1.21.1,<1.25|>=1.21.1,<1.26,!=1.25.0,!=1.25.1']
Package numpy-base conflicts for:
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Package jedi conflicts for:
ipython[version='>=5.6.0'] -> jedi[version='>=0.10']
Package libcxx conflicts for:
numexpr[version='>=2.6.8'] -> libcxx[version='>=4.0.1']
blosc -> libcxx[version='>=4.0.1']
python=3 -> libcxx[version='>=4.0.1']
pyqt[version='>=5.9.2'] -> libcxx[version='>=4.0.1']
scipy[version='>=1.1'] -> libcxx[version='>=4.0.1']
python-snappy -> libcxx[version='>=4.0.1']
cython[version='>=0.29.13'] -> libcxx[version='>=4.0.1']
matplotlib[version='>=2.2.2'] -> libcxx[version='>=4.0.1']
asv -> libcxx[version='>=4.0.1']
pytables[version='>=3.4.2'] -> libcxx[version='>=4.0.1']
Package python-jose conflicts for:
moto -> python-jose[version='<3.0.0']
Package xmltodict conflicts for:
moto -> xmltodict
Package gitdb2 conflicts for:
gitpython -> gitdb2
Package send2trash conflicts for:
notebook[version='>=5.7.5'] -> send2trash
Package traitlets conflicts for:
ipywidgets -> traitlets[version='>=4.3.1|>=4.3.1,<5.0.0']
ipykernel -> traitlets[version='>=4.1']
ipython[version='>=5.6.0'] -> traitlets[version='>=4.2']
notebook[version='>=5.7.5'] -> traitlets[version='>=4.2.1']
nbformat -> traitlets[version='>=4.1']
nbconvert[version='>=5.4.1'] -> traitlets[version='>=4.2']
Package mistune conflicts for:
nbconvert[version='>=5.4.1'] -> mistune[version='>=0.8.1']
Package sphinx conflicts for:
nbsphinx -> sphinx
numpydoc[version='>=0.9.0'] -> sphinx
Package jmespath conflicts for:
botocore[version='>=1.11'] -> jmespath[version='>=0.7.1,<1.0.0']
boto3 -> jmespath[version='>=0.7.1,<1.0.0']
Package pyaml conflicts for:
moto -> pyaml
Package mkl-service conflicts for:
scipy[version='>=1.1'] -> mkl-service[version='>=2,<3.0a0']
numpy[version='>=1.15'] -> mkl-service[version='>=2,<3.0a0']
numexpr[version='>=2.6.8'] -> mkl-service[version='>=2,<3.0a0']
Package qt conflicts for:
pyqt[version='>=5.9.2'] -> qt[version='5.9.*|5.9.*,>=5.9.6,<5.10.0a0']
Package pexpect conflicts for:
ipython[version='>=5.6.0'] -> pexpect
Package idna conflicts for:
requests -> idna[version='>=2.5,<2.6|>=2.5,<2.7|>=2.5,<2.8|>=2.5,<2.9']
Package subprocess32 conflicts for:
matplotlib[version='>=2.2.2'] -> subprocess32
Package typing_extensions conflicts for:
mypy -> typing_extensions[version='>=3.7.4']
Package futures conflicts for:
isort -> futures
Package werkzeug conflicts for:
moto -> werkzeug
Package attrs conflicts for:
hypothesis[version='>=3.82'] -> attrs[version='>=16.0.0|>=19.2.0']
pytest[version='>=4.0.2'] -> attrs[version='>=17.4.0']
black -> attrs[version='>=18.1.0']
Package backports.tempfile conflicts for:
moto -> backports.tempfile
Package libgfortran conflicts for:
numpy[version='>=1.15'] -> libgfortran[version='>=3.0.1,<4.0.0.a0']
scipy[version='>=1.1'] -> libgfortran[version='>=3.0.1,<4.0.0.a0']
Package pyzmq conflicts for:
notebook[version='>=5.7.5'] -> pyzmq[version='>=17']
Package webencodings conflicts for:
html5lib -> webencodings
Package libxslt conflicts for:
lxml -> libxslt[version='>=1.1.32,<2.0a0|>=1.1.33,<2.0a0']
Package typed-ast conflicts for:
mypy -> typed-ast[version='>=1.1.0,<1.2.0|>=1.2.0,<1.3.0|>=1.3.1,<1.4.0|>=1.4.0,<1.5.0']
Package sphinxcontrib-applehelp conflicts for:
sphinx -> sphinxcontrib-applehelp
Package toml conflicts for:
black -> toml[version='>=0.9.4']
Package ncurses conflicts for:
python=3 -> ncurses[version='>=6.0,<7.0a0|>=6.1,<7.0a0']
Package sphinxcontrib-serializinghtml conflicts for:
sphinx -> sphinxcontrib-serializinghtml
Package widgetsnbextension conflicts for:
ipywidgets -> widgetsnbextension[version='>=3.0.0|>=3.1.0,<4.0|>=3.2.0,<4.0.0|>=3.3.0,<3.4.0|>=3.4.0,<3.5.0|>=3.5.0,<3.6.0']
Package chardet conflicts for:
requests -> chardet[version='>=3.0.2,<3.1.0']
Package entrypoints conflicts for:
nbconvert[version='>=5.4.1'] -> entrypoints[version='>=0.2.2']
flake8 -> entrypoints[version='>=0.3.0,<0.4.0']
Package prompt_toolkit conflicts for:
ipython[version='>=5.6.0'] -> prompt_toolkit[version='>=1.0.4,<2.0.0|>=2.0.0']
Package mkl_random conflicts for:
numpy[version='>=1.15'] -> mkl_random[version='>=1.0.2,<2.0a0']
Package sphinxcontrib-devhelp conflicts for:
sphinx -> sphinxcontrib-devhelp
Package lzo conflicts for:
pytables[version='>=3.4.2'] -> lzo[version='>=2.10,<3.0a0']
Package libxml2 conflicts for:
lxml -> libxml2[version='>=2.9.4,<2.10.0a0|>=2.9.7,<2.10.0a0|>=2.9.8,<2.10.0a0|>=2.9.9,<2.10.0a0']
Package appnope conflicts for:
ipython[version='>=5.6.0'] -> appnope
Package pycodestyle conflicts for:
flake8 -> pycodestyle[version='>=2.0.0,<2.4.0|>=2.0.0,<2.5.0|>=2.4.0,<2.5.0|>=2.5.0,<2.6.0']
Package importlib_metadata conflicts for:
pytest[version='>=4.0.2'] -> importlib_metadata[version='>=0.12']
flake8-comprehensions -> importlib_metadata
Package cookies conflicts for:
moto -> cookies
Package snappy conflicts for:
python-snappy -> snappy[version='>=1.1.7,<2.0a0']
blosc -> snappy[version='>=1.1.7,<2.0a0']
Package py conflicts for:
pytest[version='>=4.0.2'] -> py[version='>=1.5.0']
Package libffi conflicts for:
python=3 -> libffi[version='3.2.*|>=3.2.1,<4.0a0']
Package appdirs conflicts for:
black -> appdirs
Package yaml conflicts for:
pyyaml -> yaml[version='>=0.1.7,<0.2.0a0']
Package pickleshare conflicts for:
ipython[version='>=5.6.0'] -> pickleshare
Package more-itertools conflicts for:
pytest[version='>=4.0.2'] -> more-itertools[version='>=4.0|>=4.0,>=4.0,<6.0']
Package fsspec conflicts for:
s3fs -> fsspec
Package wcwidth conflicts for:
pytest[version='>=4.0.2'] -> wcwidth
Package hdf5 conflicts for:
pytables[version='>=3.4.2'] -> hdf5[version='>=1.10.1,<1.10.2.0a0|>=1.10.2,<1.10.3.0a0|>=1.10.4,<1.10.5.0a0|>=1.8.18,<1.8.19.0a0|>=1.8.20,<1.9.0a0']
Package blosc conflicts for:
pytables[version='>=3.4.2'] -> blosc[version='>=1.14.3,<2.0a0|>=1.14.4,<2.0a0|>=1.15.0,<2.0a0|>=1.16.3,<2.0a0']
Package mccabe conflicts for:
flake8 -> mccabe[version='>=0.6.0,<0.7.0']
Package ipython_genutils conflicts for:
nbformat -> ipython_genutils
notebook[version='>=5.7.5'] -> ipython_genutils
Package backcall conflicts for:
ipython[version='>=5.6.0'] -> backcall
Package decorator conflicts for:
ipython[version='>=5.6.0'] -> decorator
Package snowballstemmer conflicts for:
sphinx -> snowballstemmer[version='>=1.1']
Package pytest-forked conflicts for:
pytest-xdist -> pytest-forked
Package numexpr conflicts for:
pytables[version='>=3.4.2'] -> numexpr
Package click conflicts for:
black -> click[version='>=6.5']
Package configparser conflicts for:
flake8 -> configparser
Package toolz conflicts for:
partd[version='>=0.3.10'] -> toolz
Package aws-xray-sdk conflicts for:
moto -> aws-xray-sdk[version='!=0.96,>=0.93|<0.96,>=0.93']
Package et_xmlfile conflicts for:
openpyxl -> et_xmlfile
Package jsondiff conflicts for:
moto -> jsondiff=1.1.1
Package thrift conflicts for:
fastparquet[version='>=0.2.1'] -> thrift[version='0.11.*|>=0.11.0']
Package babel conflicts for:
sphinx -> babel[version='>=1.3,!=2.0']
Package dicttoxml conflicts for:
moto -> dicttoxml
Package imagesize conflicts for:
sphinx -> imagesize
Note that strict channel priority may have removed packages required for satisfiability.
```
</details>
Setting `conda config --set channel_priority flexible` seemed to get the job done, but note that strict will supposedly be the default in conda 5 (side note: I ran into this on 4.7)
https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-channels.html#strict-channel-priority
Ideally could clean up conflicts in our file, though at the very least a message in the contributing guide about this might be useful to newcomers trying to configure an environment | {
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} | 4 | 2019-11-02T00:19:48Z | 2019-11-06T20:06:35Z | 2019-11-06T20:06:25Z | MEMBER | null | Narrowing down the set of cases where we have to worry about a non-scalar fill_value. I'm pretty sure we can narrow it down further, but saving that for a separate step as it has some complications for EA corner cases.
cc @jreback | {
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} | 0 | 2019-11-02T00:56:50Z | 2019-11-02T15:34:00Z | 2019-11-02T15:32:05Z | MEMBER | null | ATM all places where we use `maybe_upcast_putmask` have `other` as a scalar. By making that into a requirement for the function, we can rule out the possibility of passing non-scalar other into `maybe_promote` (xref #29331).
Note: there are some simplifications within maybe_upcast_putmask that this makes possible that I did not implement in this PR.
cc @jreback @h-vetinari | {
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} | 6 | 2019-11-02T03:03:05Z | 2019-11-03T17:29:37Z | 2019-11-03T16:38:18Z | MEMBER | null | Separating these out from the non-CLN work going on in/around these functions. | {
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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
Previous PR: #26534
In particular, the following code now behaves correctly.
```python
import pandas as pd
df = pd.DataFrame({'a': [0, 1, 2], 'b': [3, 4, 5]})
df[['a', 'c']] = 1
print(df)
```
v0.22: error
master: column `'c'` is converted to index `-1`, which causes last column to be overwritten.
```
a b
0 1 1
1 1 1
2 1 1
```
After this PR:
```
a b c
0 1 3 1
1 1 4 1
2 1 5 1
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} | 1 | 2019-11-02T09:08:09Z | 2019-11-02T16:13:23Z | 2019-11-02T15:36:34Z | CONTRIBUTOR | null | Empty codes should not warn about float codes:
```python
>>> pd.Categorical.from_codes([], ['a', 'b', 'c'])
C:\Users\TP\Miniconda3\envs\pandas-dev\Scripts\ipython:1: FutureWarning: float codes will be disallowed in the future and raise a ValueError
```
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} | 1 | 2019-11-02T11:01:44Z | 2019-11-05T17:18:37Z | 2019-11-05T17:18:22Z | CONTRIBUTOR | null | - [x] closes #22620
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https://api.github.com/repos/pandas-dev/pandas/issues/29339 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29339/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29339/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29339/events | https://github.com/pandas-dev/pandas/pull/29339 | 516,568,679 | MDExOlB1bGxSZXF1ZXN0MzM1ODA5NTY4 | 29,339 | TST: Test Series constructor with dict containing lists and explicit β¦ | {
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} | 1 | 2019-11-02T11:37:54Z | 2019-11-02T14:23:57Z | 2019-11-02T14:23:49Z | CONTRIBUTOR | null | Add test for series constructor with dict of list with explicit dtype.
- closes #18625
- 1 test added / passed
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https://api.github.com/repos/pandas-dev/pandas/issues/29340 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29340/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29340/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29340/events | https://github.com/pandas-dev/pandas/pull/29340 | 516,570,214 | MDExOlB1bGxSZXF1ZXN0MzM1ODEwNjI2 | 29,340 | Fix mypy error messages in pandas/test/tseries/offsets/test_offsets.py | {
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} | 2 | 2019-11-02T11:53:16Z | 2019-11-07T20:50:18Z | 2019-11-07T20:50:12Z | CONTRIBUTOR | null | Activate and fix mypy for test offsets
- xref #28926
- [X] tests added / passed
- [X] passes `black pandas`
- [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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} | 5 | 2019-11-02T11:57:02Z | 2019-11-17T15:42:39Z | 2019-11-17T15:42:12Z | CONTRIBUTOR | null | #### Code Sampl
```bash
black pandas
```
#### Problem description
Currently if using `virtualenv` instead of conda, in `Python 3.7.4` and pip `pip 19.3.1` the requirements automatically install `black==19.10b0` which differs from the conda workflow which install the `black==19.3b0` version.
#### Expected Output
```bash
reformatted /Users/sofianemahiou/Work/pandas/pandas/io/common.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/groupby/grouper.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/algorithms.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/indexing.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/internals/managers.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/indexes/base.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/arrays/sparse/test_array.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/io/parsers.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/io/stata.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/frame.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/dtypes/test_inference.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/io/parser/test_index_col.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/indexing/test_callable.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/indexes/period/test_construction.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/core/generic.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/test_nanops.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/reductions/test_reductions.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/frame/test_constructors.py
reformatted /Users/sofianemahiou/Work/pandas/pandas/tests/test_algos.py
```
##### Git diff
<details>
```bash
diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index c70e62377..cc6c23929 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -1155,7 +1155,7 @@ class SelectNSeries(SelectN):
n = min(n, narr)
kth_val = algos.kth_smallest(arr.copy(), n - 1)
- ns, = np.nonzero(arr <= kth_val)
+ (ns,) = np.nonzero(arr <= kth_val)
inds = ns[arr[ns].argsort(kind="mergesort")]
if self.keep != "all":
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 40efc4c65..7d8cc0b73 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4829,7 +4829,7 @@ class DataFrame(NDFrame):
duplicated = self.duplicated(subset, keep=keep)
if inplace:
- inds, = (-duplicated)._ndarray_values.nonzero()
+ (inds,) = (-duplicated)._ndarray_values.nonzero()
new_data = self._data.take(inds)
self._update_inplace(new_data)
else:
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index f88c26c7b..fa43206b8 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -3613,7 +3613,7 @@ class NDFrame(PandasObject, SelectionMixin):
if isinstance(loc, np.ndarray):
if loc.dtype == np.bool_:
- inds, = loc.nonzero()
+ (inds,) = loc.nonzero()
return self.take(inds, axis=axis)
else:
return self.take(loc, axis=axis)
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index d7eaaca5a..d6beefbf3 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -284,7 +284,11 @@ class Grouping:
if self.name is None:
self.name = index.names[level]
- self.grouper, self._labels, self._group_index = index._get_grouper_for_level( # noqa: E501
+ (
+ self.grouper,
+ self._labels,
+ self._group_index,
+ ) = index._get_grouper_for_level( # noqa: E501
self.grouper, level
)
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 187c7e2f3..954607a0d 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1873,7 +1873,7 @@ class Index(IndexOpsMixin, PandasObject):
@cache_readonly
def _nan_idxs(self):
if self._can_hold_na:
- w, = self._isnan.nonzero()
+ (w,) = self._isnan.nonzero()
return w
else:
return np.array([], dtype=np.int64)
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 44c786f00..1315e9d5b 100755
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -320,7 +320,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase):
# if there is only one block/type, still have to take split path
# unless the block is one-dimensional or it can hold the value
if not take_split_path and self.obj._data.blocks:
- blk, = self.obj._data.blocks
+ (blk,) = self.obj._data.blocks
if 1 < blk.ndim: # in case of dict, keys are indices
val = list(value.values()) if isinstance(value, dict) else value
take_split_path = not blk._can_hold_element(val)
@@ -1120,7 +1120,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase):
if com.is_bool_indexer(key):
# A boolean indexer
key = check_bool_indexer(labels, key)
- inds, = key.nonzero()
+ (inds,) = key.nonzero()
return self.obj.take(inds, axis=axis)
else:
# A collection of keys
@@ -1264,7 +1264,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase):
if com.is_bool_indexer(obj):
obj = check_bool_indexer(labels, obj)
- inds, = obj.nonzero()
+ (inds,) = obj.nonzero()
return inds
else:
# When setting, missing keys are not allowed, even with .loc:
diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py
index c47aaf7c7..db782b455 100644
--- a/pandas/core/internals/managers.py
+++ b/pandas/core/internals/managers.py
@@ -1868,7 +1868,7 @@ def _stack_arrays(tuples, dtype):
def _interleaved_dtype(
- blocks: List[Block]
+ blocks: List[Block],
) -> Optional[Union[np.dtype, ExtensionDtype]]:
"""Find the common dtype for `blocks`.
diff --git a/pandas/io/common.py b/pandas/io/common.py
index 0bef14e49..e08fd37e6 100644
--- a/pandas/io/common.py
+++ b/pandas/io/common.py
@@ -109,7 +109,7 @@ def _is_url(url) -> bool:
def _expand_user(
- filepath_or_buffer: FilePathOrBuffer[AnyStr]
+ filepath_or_buffer: FilePathOrBuffer[AnyStr],
) -> FilePathOrBuffer[AnyStr]:
"""Return the argument with an initial component of ~ or ~user
replaced by that user's home directory.
@@ -139,7 +139,7 @@ def _validate_header_arg(header) -> None:
def _stringify_path(
- filepath_or_buffer: FilePathOrBuffer[AnyStr]
+ filepath_or_buffer: FilePathOrBuffer[AnyStr],
) -> FilePathOrBuffer[AnyStr]:
"""Attempt to convert a path-like object to a string.
diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py
index 058d65b94..4ff988acf 100755
--- a/pandas/io/parsers.py
+++ b/pandas/io/parsers.py
@@ -1918,7 +1918,12 @@ class CParserWrapper(ParserBase):
else:
if len(self._reader.header) > 1:
# we have a multi index in the columns
- self.names, self.index_names, self.col_names, passed_names = self._extract_multi_indexer_columns( # noqa: E501
+ (
+ self.names,
+ self.index_names,
+ self.col_names,
+ passed_names,
+ ) = self._extract_multi_indexer_columns( # noqa: E501
self._reader.header, self.index_names, self.col_names, passed_names
)
else:
@@ -2307,7 +2312,12 @@ class PythonParser(ParserBase):
# The original set is stored in self.original_columns.
if len(self.columns) > 1:
# we are processing a multi index column
- self.columns, self.index_names, self.col_names, _ = self._extract_multi_indexer_columns( # noqa: E501
+ (
+ self.columns,
+ self.index_names,
+ self.col_names,
+ _,
+ ) = self._extract_multi_indexer_columns( # noqa: E501
self.columns, self.index_names, self.col_names
)
# Update list of original names to include all indices.
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index 07475f224..8e5fa48d4 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -614,7 +614,7 @@ def _cast_to_stata_types(data):
data[col] = data[col].astype(np.int32)
else:
data[col] = data[col].astype(np.float64)
- if data[col].max() >= 2 ** 53 or data[col].min() <= -2 ** 53:
+ if data[col].max() >= 2 ** 53 or data[col].min() <= -(2 ** 53):
ws = precision_loss_doc % ("int64", "float64")
elif dtype in (np.float32, np.float64):
value = data[col].max()
diff --git a/pandas/tests/arrays/sparse/test_array.py b/pandas/tests/arrays/sparse/test_array.py
index f9bb4981d..755cbfb71 100644
--- a/pandas/tests/arrays/sparse/test_array.py
+++ b/pandas/tests/arrays/sparse/test_array.py
@@ -658,12 +658,16 @@ class TestSparseArray:
dense = np.array([np.nan, 0, 3, 4, 0, 5, np.nan, np.nan, 0])
sparse = SparseArray(dense)
- res = sparse[4:,] # noqa: E231
+ res = sparse[
+ 4:,
+ ] # noqa: E231
exp = SparseArray(dense[4:,]) # noqa: E231
tm.assert_sp_array_equal(res, exp)
sparse = SparseArray(dense, fill_value=0)
- res = sparse[4:,] # noqa: E231
+ res = sparse[
+ 4:,
+ ] # noqa: E231
exp = SparseArray(dense[4:,], fill_value=0) # noqa: E231
tm.assert_sp_array_equal(res, exp)
@@ -823,11 +827,11 @@ class TestSparseArray:
# Tests regression #21172.
sa = pd.SparseArray([float("nan"), float("nan"), 1, 0, 0, 2, 0, 0, 0, 3, 0, 0])
expected = np.array([2, 5, 9], dtype=np.int32)
- result, = sa.nonzero()
+ (result,) = sa.nonzero()
tm.assert_numpy_array_equal(expected, result)
sa = pd.SparseArray([0, 0, 1, 0, 0, 2, 0, 0, 0, 3, 0, 0])
- result, = sa.nonzero()
+ (result,) = sa.nonzero()
tm.assert_numpy_array_equal(expected, result)
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 62fb118f7..7d5b1891c 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -505,7 +505,7 @@ class TestInference:
result = lib.maybe_convert_numeric(case, set(), coerce_numeric=coerce)
tm.assert_almost_equal(result, expected)
- @pytest.mark.parametrize("value", [-2 ** 63 - 1, 2 ** 64])
+ @pytest.mark.parametrize("value", [-(2 ** 63) - 1, 2 ** 64])
def test_convert_int_overflow(self, value):
# see gh-18584
arr = np.array([value], dtype=object)
diff --git a/pandas/tests/frame/test_constructors.py b/pandas/tests/frame/test_constructors.py
index aa00cf234..f193f97ae 100644
--- a/pandas/tests/frame/test_constructors.py
+++ b/pandas/tests/frame/test_constructors.py
@@ -245,9 +245,9 @@ class TestDataFrameConstructors:
np.array([2 ** 64], dtype=object),
np.array([2 ** 65]),
[2 ** 64 + 1],
- np.array([-2 ** 63 - 4], dtype=object),
- np.array([-2 ** 64 - 1]),
- [-2 ** 65 - 2],
+ np.array([-(2 ** 63) - 4], dtype=object),
+ np.array([-(2 ** 64) - 1]),
+ [-(2 ** 65) - 2],
],
)
def test_constructor_int_overflow(self, values):
diff --git a/pandas/tests/indexes/period/test_construction.py b/pandas/tests/indexes/period/test_construction.py
index 8c75fbbae..1973cb7f4 100644
--- a/pandas/tests/indexes/period/test_construction.py
+++ b/pandas/tests/indexes/period/test_construction.py
@@ -434,7 +434,7 @@ class TestPeriodIndex:
with tm.assert_produces_warning(FutureWarning) as m:
PeriodIndex(start="2000", periods=2)
- warning, = m
+ (warning,) = m
assert 'freq="A-DEC"' in str(warning.message)
def test_constructor(self):
diff --git a/pandas/tests/indexing/multiindex/test_getitem.py b/pandas/tests/indexing/multiindex/test_getitem.py
index 4f95e6bd2..519a1eb5b 100644
--- a/pandas/tests/indexing/multiindex/test_getitem.py
+++ b/pandas/tests/indexing/multiindex/test_getitem.py
@@ -108,7 +108,7 @@ def test_series_getitem_indexing_errors(
def test_series_getitem_corner_generator(
- multiindex_year_month_day_dataframe_random_data
+ multiindex_year_month_day_dataframe_random_data,
):
s = multiindex_year_month_day_dataframe_random_data["A"]
result = s[(x > 0 for x in s)]
diff --git a/pandas/tests/indexing/multiindex/test_xs.py b/pandas/tests/indexing/multiindex/test_xs.py
index 99f343c2f..40483ffec 100644
--- a/pandas/tests/indexing/multiindex/test_xs.py
+++ b/pandas/tests/indexing/multiindex/test_xs.py
@@ -211,7 +211,7 @@ def test_xs_level_series_ymd(multiindex_year_month_day_dataframe_random_data):
def test_xs_level_series_slice_not_implemented(
- multiindex_year_month_day_dataframe_random_data
+ multiindex_year_month_day_dataframe_random_data,
):
# this test is not explicitly testing .xs functionality
# TODO: move to another module or refactor
diff --git a/pandas/tests/indexing/test_callable.py b/pandas/tests/indexing/test_callable.py
index aa73bd728..81dedfdc7 100644
--- a/pandas/tests/indexing/test_callable.py
+++ b/pandas/tests/indexing/test_callable.py
@@ -17,10 +17,14 @@ class TestIndexingCallable:
res = df.loc[lambda x: x.A > 2]
tm.assert_frame_equal(res, df.loc[df.A > 2])
- res = df.loc[lambda x: x.A > 2,] # noqa: E231
+ res = df.loc[
+ lambda x: x.A > 2,
+ ] # noqa: E231
tm.assert_frame_equal(res, df.loc[df.A > 2,]) # noqa: E231
- res = df.loc[lambda x: x.A > 2,] # noqa: E231
+ res = df.loc[
+ lambda x: x.A > 2,
+ ] # noqa: E231
tm.assert_frame_equal(res, df.loc[df.A > 2,]) # noqa: E231
res = df.loc[lambda x: x.B == "b", :]
@@ -90,7 +94,9 @@ class TestIndexingCallable:
res = df.loc[lambda x: ["A", "C"]]
tm.assert_frame_equal(res, df.loc[["A", "C"]])
- res = df.loc[lambda x: ["A", "C"],] # noqa: E231
+ res = df.loc[
+ lambda x: ["A", "C"],
+ ] # noqa: E231
tm.assert_frame_equal(res, df.loc[["A", "C"],]) # noqa: E231
res = df.loc[lambda x: ["A", "C"], :]
diff --git a/pandas/tests/io/parser/test_index_col.py b/pandas/tests/io/parser/test_index_col.py
index 4dfb8d3bd..812255999 100644
--- a/pandas/tests/io/parser/test_index_col.py
+++ b/pandas/tests/io/parser/test_index_col.py
@@ -22,8 +22,8 @@ KORD4,19990127, 21:00:00, 21:18:00, -0.9900, 2.0100, 3.6000, 0.0000, 270.0000
KORD5,19990127, 22:00:00, 21:56:00, -0.5900, 1.7100, 5.1000, 0.0000, 290.0000
KORD6,19990127, 23:00:00, 22:56:00, -0.5900, 1.7100, 4.6000, 0.0000, 280.0000""" # noqa
header = (
- "ID,date,NominalTime,ActualTime,TDew,TAir,Windspeed,Precip,WindDir\n"
- ) # noqa
+ "ID,date,NominalTime,ActualTime,TDew,TAir,Windspeed,Precip,WindDir\n" # noqa
+ )
if with_header:
data = header + no_header
diff --git a/pandas/tests/reductions/test_reductions.py b/pandas/tests/reductions/test_reductions.py
index 05ebff438..9bd6fb41c 100644
--- a/pandas/tests/reductions/test_reductions.py
+++ b/pandas/tests/reductions/test_reductions.py
@@ -179,8 +179,8 @@ class TestIndexReductions:
[
(0, 400, 3),
(500, 0, -6),
- (-10 ** 6, 10 ** 6, 4),
- (10 ** 6, -10 ** 6, -4),
+ (-(10 ** 6), 10 ** 6, 4),
+ (10 ** 6, -(10 ** 6), -4),
(0, 10, 20),
],
)
diff --git a/pandas/tests/test_algos.py b/pandas/tests/test_algos.py
index 9dd88fd5d..885428e51 100644
--- a/pandas/tests/test_algos.py
+++ b/pandas/tests/test_algos.py
@@ -216,10 +216,10 @@ class TestFactorize:
tm.assert_numpy_array_equal(uniques, exp_uniques)
def test_int64_factorize(self, writable):
- data = np.array([2 ** 63 - 1, -2 ** 63, 2 ** 63 - 1], dtype=np.int64)
+ data = np.array([2 ** 63 - 1, -(2 ** 63), 2 ** 63 - 1], dtype=np.int64)
data.setflags(write=writable)
exp_labels = np.array([0, 1, 0], dtype=np.intp)
- exp_uniques = np.array([2 ** 63 - 1, -2 ** 63], dtype=np.int64)
+ exp_uniques = np.array([2 ** 63 - 1, -(2 ** 63)], dtype=np.int64)
labels, uniques = algos.factorize(data)
tm.assert_numpy_array_equal(labels, exp_labels)
@@ -258,7 +258,7 @@ class TestFactorize:
"data",
[
np.array([0, 1, 0], dtype="u8"),
- np.array([-2 ** 63, 1, -2 ** 63], dtype="i8"),
+ np.array([-(2 ** 63), 1, -(2 ** 63)], dtype="i8"),
np.array(["__nan__", "foo", "__nan__"], dtype="object"),
],
)
@@ -275,8 +275,8 @@ class TestFactorize:
[
(np.array([0, 1, 0, 2], dtype="u8"), 0),
(np.array([1, 0, 1, 2], dtype="u8"), 1),
- (np.array([-2 ** 63, 1, -2 ** 63, 0], dtype="i8"), -2 ** 63),
- (np.array([1, -2 ** 63, 1, 0], dtype="i8"), 1),
+ (np.array([-(2 ** 63), 1, -(2 ** 63), 0], dtype="i8"), -(2 ** 63)),
+ (np.array([1, -(2 ** 63), 1, 0], dtype="i8"), 1),
(np.array(["a", "", "a", "b"], dtype=object), "a"),
(np.array([(), ("a", 1), (), ("a", 2)], dtype=object), ()),
(np.array([("a", 1), (), ("a", 1), ("a", 2)], dtype=object), ("a", 1)),
diff --git a/pandas/tests/test_nanops.py b/pandas/tests/test_nanops.py
index 49d1777df..e6cff5c26 100644
--- a/pandas/tests/test_nanops.py
+++ b/pandas/tests/test_nanops.py
@@ -302,7 +302,7 @@ class TestnanopsDataFrame:
# In the previous implementation mean can overflow for int dtypes, it
# is now consistent with numpy
- for a in [2 ** 55, -2 ** 55, 20150515061816532]:
+ for a in [2 ** 55, -(2 ** 55), 20150515061816532]:
s = Series(a, index=range(500), dtype=np.int64)
result = s.mean()
np_result = s.values.mean()
```
</details>
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : 0de99558b497c5611cbe5d35d504763bd7692275
python : 3.7.4.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.26.0.dev0+734.g0de99558b
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.6.0
Cython : 0.29.14
pytest : 5.2.2
hypothesis : 4.42.6
sphinx : 2.2.1
blosc : 1.8.1
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : 0.15.1
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : 3.6.1
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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} | 1 | 2019-11-02T12:14:13Z | 2019-11-02T14:21:15Z | 2019-11-02T14:21:06Z | CONTRIBUTOR | null | check reindex() and astype() order consistency for Series
- [x] closes #17444
- [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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} | 3 | 2019-11-02T13:07:14Z | 2019-11-05T17:19:56Z | 2019-11-05T17:19:53Z | CONTRIBUTOR | null | -closes #14422
-passes `black pandas`
-added test test_downcast_uint64_exception() | {
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https://api.github.com/repos/pandas-dev/pandas/issues/29349 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29349/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29349/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29349/events | https://github.com/pandas-dev/pandas/issues/29349 | 516,592,249 | MDU6SXNzdWU1MTY1OTIyNDk= | 29,349 | Local test failure: TestMathNumExprPython.test_result_complex128 | {
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"d... | closed | false | null | [] | null | 2 | 2019-11-02T13:24:32Z | 2020-04-19T22:09:25Z | 2020-04-19T22:09:25Z | CONTRIBUTOR | null | When running the pytest suite, I get the following error locally.
```
_________________ TestMathNumExprPython.test_result_complex128 _________________
self = <pandas.tests.computation.test_eval.TestMathNumExprPython object at 0x1c1e588250>
@td.skip_if_windows
def test_result_complex128(self):
# xref https://github.com/pandas-dev/pandas/issues/12293
# this fails on Windows, apparently a floating point precision issue
# Did not test complex64 because DataFrame is converting it to
# complex128. Due to https://github.com/pandas-dev/pandas/issues/10952
> self.check_result_type(np.complex128, np.complex128)
pandas/tests/computation/test_eval.py:1811:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
pandas/tests/computation/test_eval.py:1796: in check_result_type
tm.assert_series_equal(got, expect, check_names=False)
pandas/_libs/testing.pyx:65: in pandas._libs.testing.assert_almost_equal
cpdef assert_almost_equal(a, b,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> raise_assert_detail(obj, msg, lobj, robj)
E AssertionError: Series are different
E
E Series values are different (10.0 %)
E [left]: [(-0.9522952601059279-0j), (-0.17178347753563025+0j), (-0.44142785973450865+0j), (0.9805014538002449-0j), (0.33466949854846434+0j), (0.18226199407925794+0j), (0.5086971691486349+0j), (-0.34119630264795875+0j), (0.8144747173149681+0j), (-0.14905691528482845+0j)]
E [right]: [(-0.9522952601059279+0j), (-0.17178347753563025+0j), (-0.44142785973450865+0j), (0.9805014538002449+0j), (0.33466949854846434+0j), (0.18226199407925794+0j), (0.5086971691486349+0j), (-0.34119630264795875+0j), (0.814474717314968+0j), (-0.14905691528482845+0j)]
pandas/_libs/testing.pyx:176: AssertionError
```
<details>
INSTALLED VERSIONS
------------------
commit : 84386976a113b9f7e84863f5a8329f129d1b2a92
python : 3.7.5.final.0
python-bits : 64
OS : Darwin
OS-release : 17.5.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 0.26.0.dev0+736.g84386976a
numpy : 1.17.2
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.6.0.post20191030
Cython : 0.29.13
pytest : 5.2.2
hypothesis : 4.36.2
sphinx : 2.2.1
blosc : None
feather : None
xlsxwriter : 1.2.2
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : 0.15.0
pytables : None
s3fs : 0.3.4
scipy : 1.3.1
sqlalchemy : 1.3.10
tables : 3.5.1
xarray : 0.13.0
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.2
</details>
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} | 3 | 2019-11-02T13:40:57Z | 2019-11-02T16:09:16Z | 2019-11-02T15:51:27Z | CONTRIBUTOR | null | Python 3.8.0 stable release is now available on travis https://travis-ci.community/t/add-python-3-8-support/5463 we can use it?
The 3.8-dev snapshot seemed to cause some issues here:
https://travis-ci.org/pandas-dev/pandas/jobs/606411398?utm_medium=notification&utm_source=github_status
related - https://github.com/pandas-dev/pandas/issues/26626 | {
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} | 2 | 2019-11-02T13:57:20Z | 2019-11-04T16:28:05Z | 2019-11-02T15:02:06Z | CONTRIBUTOR | null | xref #29341
pinning until we can update the codebase | {
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- [ x ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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This PR closes https://github.com/pandas-dev/pandas/issues/29128 | {
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} | 2 | 2019-11-02T14:58:13Z | 2019-11-13T01:57:24Z | 2019-11-13T01:57:20Z | CONTRIBUTOR | null | TST: Test type issue fix in empty groupby from DataFrame with categorical
closes #9614 | {
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} | 1 | 2019-11-02T15:11:47Z | 2019-11-16T22:06:14Z | 2019-11-16T22:06:10Z | CONTRIBUTOR | null | Tried unsuccessfully reproducing Issue #20757 on pandas: 0.23.0 and 0.26.0.dev0+734.g0de99558b.dirty. That's why I decided to keep the input data from Issue #20757 unchanged.
- [x] closes #20757
- [x] tests added / passed
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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} | 1 | 2019-11-02T15:23:05Z | 2019-11-02T19:51:13Z | 2019-11-02T19:51:08Z | CONTRIBUTOR | null | I added a unit test for an edge case that was failing. Using the apply method on an empty integer series with a datetime index would throw an error.
- [x] closes #21245
- [x] 1 test added
- [x] passes pandas and flake8
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} | 1 | 2019-11-02T16:10:56Z | 2019-11-02T20:58:25Z | 2019-11-02T19:48:23Z | MEMBER | null | Also use the new _validate_limit in two places in the non-cython code | {
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} | 3 | 2019-11-02T16:27:26Z | 2019-11-04T14:59:25Z | 2019-11-04T14:41:06Z | MEMBER | null | Along with #29331 and #29332 this allows us to rule out non-scalar fill_value being passed to maybe_promote for _almost_ all cases, the last few of which we'll have to address individually.
The restriction in `Block.shift` could be an API change if you squint and tilt your head.
The assertion in masked_rec_array_to_mgr is based on my read of the numpy docs, but it'd be worth double-checking. | {
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- [x] tests added / passed
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- [ n/a] whatsnew entry
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- [X] passes `black pandas`
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- [x] tests added / passed
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
---
## What
Whilst the original issue is from the factory method `DataFrame.from_dict(d, orient='index')`, the main issue is the *order* of elements within the list in the main constructor:
For example:
```
pd.DataFrame([[1, 2, 3], 4]) # doesn't work
# TypeError: object of type 'int' has no len()
In [2]: pd.DataFrame([4, [1, 2, 3]]) # works, creates a 1D DataFrame
Out[2]:
0
0 4
1 [1, 2, 3]
```
## Current Constructor Logic on List Argument
- Current logic looks at the [first element](https://github.com/pandas-dev/pandas/blob/master/pandas/core/frame.py#L462-L465), and *infers* that all other elements are iterables as well.
- if all elements in the list are iterables, it generates a 2D DataFrame.
- if any element from index-1 onwards is a non-iterable, it doesn't have a len() method and fails.
## Proposed Solution
- Based on the first element, *try* to infer that all elements are iterables as well.
- If not all subsequent elements are iterables, then return 1D DataFrame. This would be the same behaviour as it would have been if the first element in the list is non-iterable.
- This should not have performance degradation as there is noneed to check if all elements in the list are iterables.
## Note
- This does not solve the issue whereby we have iterables of different types (such as lists and strings...)
```
In [2]: pd.DataFrame([[1, 2, 3], 'foobar'])
Out[2]:
0 1 2 3 4 5
0 1 2 3 None None None
1 f o o b a r
``` | {
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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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} | 5 | 2019-11-02T17:30:12Z | 2019-11-07T01:48:17Z | 2019-11-06T17:51:05Z | CONTRIBUTOR | null | - [x] closes #27054
See the image below which highlights what i've done here
`flake8-rst doc/source --filename=/getting_started/basics.rst` runs clean
cc. @datapythonista to review | {
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} | 1 | 2019-11-02T17:39:28Z | 2019-11-03T14:59:10Z | 2019-11-03T14:59:06Z | CONTRIBUTOR | null | - [x] closes #11670
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} | 2 | 2019-11-02T17:55:39Z | 2019-11-03T21:23:12Z | 2019-11-03T21:23:01Z | CONTRIBUTOR | null | - [x] closes #17962
- [x] tests added / passed
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} | 5 | 2019-11-02T21:26:57Z | 2019-11-03T22:11:47Z | 2019-11-03T22:11:43Z | CONTRIBUTOR | null | Deprivatize ``_factorize_from_iterable`` and ``_factorize_from_iterables`` | {
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} | 1 | 2019-11-03T00:41:52Z | 2019-11-07T22:13:43Z | 2019-11-07T22:13:28Z | CONTRIBUTOR | null | - [x] closes #14525
- [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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Calling `.drop_duplicates()` on a large dataframe say of over 1 million rows with sufficient duplicate values should suffice
#### Problem description
I have a very large data frame object ( a little less than 10 million rows). It has 5 columns, most of which at this time are empty. However, for the non-empty columns, there are duplicate values. I have used both `drop_duplicates` and `duplicated` to attempt removing these duplicates. For every variation of these methods, I always get a `MemoryError`. I am running pandas in a jupyter notebook using Python3 on an AWS instance. The AWS instance has 16 GB of RAM.
How can I solve this issue?
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Linux
OS-release : 4.14.146-120.181.amzn2.x86_64
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.2
pytz : 2019.2
dateutil : 2.8.0
pip : 9.0.3
setuptools : 38.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : 7.8.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : 0.11.0
pyarrow : None
pytables : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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#### Problem description
I found the `resample` for subsampling to aggregate would take NaN(`np.nan`) as zero.
I have seen the similar question in [Handling NaN during resampling #22065](https://github.com/pandas-dev/pandas/issues/22065)
I use `.sum()`, `.sum(skipna=False)`, `.apply(np.sum)`, and my function `.apply(lambda x: np.sum(x.values)` to test the same series. Only my function work out with my expected result.
my environment
numpy: 1.16.5
pandas: 0.25.1
```python
import numpy as np
import pandas as pd
index = pd.date_range('1/1/2019', periods=12, freq='T')
series = pd.Series(range(12), index=index)
series[5:7] = np.nan
```
```
series
> 2019-01-01 00:00:00 0.0
> 2019-01-01 00:01:00 1.0
> 2019-01-01 00:02:00 2.0
> 2019-01-01 00:03:00 3.0
> 2019-01-01 00:04:00 4.0
> 2019-01-01 00:05:00 NaN
> 2019-01-01 00:06:00 NaN
> 2019-01-01 00:07:00 7.0
> 2019-01-01 00:08:00 8.0
> 2019-01-01 00:09:00 9.0
> 2019-01-01 00:10:00 10.0
> 2019-01-01 00:11:00 11.0
> Freq: T, dtype: float64
```
**1** using `.sum()`
```
series.resample('2T').sum()
print(series.resample('2T').apply(lambda x: np.sum(x.values)))
> 2019-01-01 00:00:00 1.0
> 2019-01-01 00:02:00 5.0
> 2019-01-01 00:04:00 4.0
> 2019-01-01 00:06:00 7.0
> 2019-01-01 00:08:00 17.0
> 2019-01-01 00:10:00 21.0
> Freq: 2T, dtype: float64
```
**2** using `.sum(skipna=False)` will raise an error
```
series.resample('2T').sum(skipna=False)
>UnsupportedFunctionCall: numpy operations are not valid with resample. Use .resample(...).sum() instead
```
**3** using `.apply(np.sum)`
```
series.resample('2T').apply(np.sum)
> 2019-01-01 00:00:00 1.0
> 2019-01-01 00:02:00 5.0
> 2019-01-01 00:04:00 4.0
> 2019-01-01 00:06:00 7.0
> 2019-01-01 00:08:00 17.0
> 2019-01-01 00:10:00 21.0
> Freq: 2T, dtype: float64
```
**4** using `.apply(lambda x: np.sum(x.values))`
```
series.resample('2T').apply(lambda x: np.sum(x.values))
> 2019-01-01 00:00:00 1.0
> 2019-01-01 00:02:00 5.0
> 2019-01-01 00:04:00 NaN
> 2019-01-01 00:06:00 NaN
> 2019-01-01 00:08:00 17.0
> 2019-01-01 00:10:00 21.0
> Freq: 2T, dtype: float64
```
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Foreshadowing: some of the TypeErrors we are catching are being caused by `self.axis` not being an Index instead of an int in some cases. | {
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- Just updating doc-string for to_csv() compression.
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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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} | 8 | 2019-11-04T09:25:45Z | 2020-01-28T15:29:45Z | 2020-01-27T12:34:43Z | CONTRIBUTOR | null | - [x] closes https://github.com/pandas-dev/pandas/issues/25495
- [x] 1 test added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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] | closed | false | null | [] | null | 3 | 2019-11-04T12:29:11Z | 2020-09-24T13:40:09Z | 2020-09-24T13:39:46Z | MEMBER | null | #### Code Sample, a copy-pastable example if possible
code sample from DataFrame.select_dtypes docstring
```python
>>> import pandas as pd
>>>
>>> pd.__version__
'0.26.0.dev0+767.gb3490cbd9'
>>>
>>> df = pd.DataFrame({"a": [1, 2] * 3, "b": [True, False] * 3, "c": [1.0, 2.0] * 3})
>>> df
a b c
0 1 True 1.0
1 2 False 2.0
2 1 True 1.0
3 2 False 2.0
4 1 True 1.0
5 2 False 2.0
>>>
>>> df.select_dtypes(exclude=["int"])
a b c
0 1 True 1.0
1 2 False 2.0
2 1 True 1.0
3 2 False 2.0
4 1 True 1.0
5 2 False 2.0
>>>
```
#### Problem description
seen locally on master and 0.25.1
The docstring implies `"int"` is a valid dtype to exclude. Only `"int64"` produces the expected output shown in the docstring.
The same applies to the `include` argument.
#### Expected Output
```python
>>> df.select_dtypes(exclude=["int64"])
b c
0 True 1.0
1 False 2.0
2 True 1.0
3 False 2.0
4 True 1.0
5 False 2.0
>>>
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : b3490cbd98b96aa5064e87b11c391596e32f7993
python : 3.7.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : None.None
pandas : 0.26.0.dev0+767.gb3490cbd9
numpy : 1.17.2
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.6.0.post20191030
Cython : 0.29.13
pytest : 5.2.2
hypothesis : 4.36.2
sphinx : 2.2.1
blosc : None
feather : None
xlsxwriter : 1.2.2
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.8.1
bottleneck : 1.2.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : 0.15.1
pytables : None
s3fs : 0.3.4
scipy : 1.3.1
sqlalchemy : 1.3.10
tables : 3.5.1
xarray : 0.13.0
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.2
>>>
</details>
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} | 1 | 2019-11-04T14:05:01Z | 2019-11-04T14:53:10Z | 2019-11-04T14:53:10Z | CONTRIBUTOR | null | - [x] closes #24617
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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} | 2 | 2019-11-04T14:58:19Z | 2020-01-06T16:47:02Z | 2019-11-04T16:11:23Z | CONTRIBUTOR | null | Another batch of commits for #28602. Also fixes a few summary formatting errors and PR08 capitalization errors. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/29397 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29397/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29397/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29397/events | https://github.com/pandas-dev/pandas/issues/29397 | 517,286,694 | MDU6SXNzdWU1MTcyODY2OTQ= | 29,397 | Style problem using Styler.set_table_styles | {
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... | closed | false | null | [] | null | 8 | 2019-11-04T17:08:22Z | 2020-08-31T15:17:46Z | 2020-08-31T15:17:45Z | NONE | null | I am using the pd.Styler to style tables and render a HTML/CSS code from him.
But this python code has some problems:
```python
import pandas as pd
x = [0, 1]
y = [0, 1]
data = [[2, 3], [5, 6]]
df = pd.DataFrame(data, index=x, columns=y)
def detailedTableConfig():
table = {
"border-collapse": "collapse",
"border": "1px solid black",
}
return [dict(selector="table", props=list(table.items()))]
s = df.style.set_table_styles(detailedTableConfig())
with open('table.html', 'w') as fhtml:
print(s.render(), file=fhtml)
```
I am trying to put border around the table. But this python code generates this HTML/CSS code:
```html
<style type="text/css" >
#T_60255858_ff24_11e9_9c6a_988389d0b304 table {
border-collapse: collapse;
border: 1px solid black;
}</style><table id="T_60255858_ff24_11e9_9c6a_988389d0b304" ><thead> <tr> <th class="blank level0" ></th> <th class="col_heading level0 col0" >0</th> <th class="col_heading level0 col1" >1</th> </tr></thead><tbody>
<tr>
<th id="T_60255858_ff24_11e9_9c6a_988389d0b304level0_row0" class="row_heading level0 row0" >0</th>
<td id="T_60255858_ff24_11e9_9c6a_988389d0b304row0_col0" class="data row0 col0" >2</td>
<td id="T_60255858_ff24_11e9_9c6a_988389d0b304row0_col1" class="data row0 col1" >3</td>
</tr>
<tr>
<th id="T_60255858_ff24_11e9_9c6a_988389d0b304level0_row1" class="row_heading level0 row1" >1</th>
<td id="T_60255858_ff24_11e9_9c6a_988389d0b304row1_col0" class="data row1 col0" >5</td>
<td id="T_60255858_ff24_11e9_9c6a_988389d0b304row1_col1" class="data row1 col1" >6</td>
</tr>
</tbody></table>
```
But this does not work:
This HTML/CSS snippet work only if
```html
<style type="text/css" >
#T_60255858_ff24_11e9_9c6a_988389d0b304 {
border-collapse: collapse;
border: 1px solid black;
...
```
or:
```html
<style type="text/css" >
table{
border-collapse: collapse;
border: 1px solid black;
...
```
and still:
```html
<style type="text/css" >
table#T_60255858_ff24_11e9_9c6a_988389d0b304 {
border-collapse: collapse;
border: 1px solid black;
...
```
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https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reindex.html | {
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"id": 7171206... | closed | true | null | [] | null | 7 | 2019-11-04T18:56:20Z | 2021-06-23T12:16:05Z | 2020-02-12T01:16:30Z | MEMBER | spam | Looks like #11604 is our most visited page on GitHub after the home (it's got half of the visits of the home, see "Popular content" in https://github.com/pandas-dev/pandas/graphs/traffic).
Someone recommended `sudo pip3 install pandas`, and I guess a person having that error will google it, read that issue and end up running that, which is not great.
I think we should have somewhere on the documentation information about that error, and give better information about the issue. And recommend using conda, discouraging pip, and creating an environment.
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} | 1 | 2019-11-04T21:43:44Z | 2019-11-05T17:47:01Z | 2019-11-05T17:13:17Z | MEMBER | null | The implementation here operates on the values (ndarray or EA) instead of on the Series/DataFrame.
This lets us avoid a runtime import of Series, so core.missing joins the Simple Dependencies Club. | {
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} | 10 | 2019-11-04T22:02:52Z | 2019-12-05T16:35:52Z | 2019-12-05T16:35:46Z | CONTRIBUTOR | null | closes #29270
Following is the output after removing "kendall"
```
Β· Creating environments
Β· Discovering benchmarks
Β·Β· Uninstalling from conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
Β·Β· Building cd59acf5 <fix-kendall-issues> for conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt................................................
Β·Β· Installing cd59acf5 <fix-kendall-issues> into conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt..
Β· Running 14 total benchmarks (2 commits * 1 environments * 7 benchmarks)
[ 0.00%] Β· For pandas commit 165d5ee4 <master> (round 1/2):
[ 0.00%] Β·Β· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt...
[ 0.00%] Β·Β· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 7.14%] Β·Β·Β· Running (stat_ops.Correlation.time_corr--)....
[ 21.43%] Β·Β·Β· Running (stat_ops.Correlation.time_corrwith_cols--)..
[ 25.00%] Β· For pandas commit cd59acf5 <fix-kendall-issues> (round 1/2):
[ 25.00%] Β·Β· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt...
[ 25.00%] Β·Β· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 32.14%] Β·Β·Β· Running (stat_ops.Correlation.time_corr--)....
[ 46.43%] Β·Β·Β· Running (stat_ops.Correlation.time_corrwith_cols--)..
[ 50.00%] Β· For pandas commit cd59acf5 <fix-kendall-issues> (round 2/2):
[ 50.00%] Β·Β· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 53.57%] Β·Β·Β· stat_ops.Correlation.peakmem_corr_wide ok
[ 53.57%] Β·Β·Β· ========== ====== =======
-- use_bottleneck
---------- --------------
method True False
========== ====== =======
spearman 108M 108M
pearson 105M 105M
========== ====== =======
[ 57.14%] Β·Β·Β· stat_ops.Correlation.time_corr ok
[ 57.14%] Β·Β·Β· ========== ============ ============
-- use_bottleneck
---------- -------------------------
method True False
========== ============ ============
spearman 8.74Β±1ms 8.71Β±2ms
pearson 2.88Β±0.6ms 2.84Β±0.4ms
========== ============ ============
[ 60.71%] Β·Β·Β· stat_ops.Correlation.time_corr_series ok
[ 60.71%] Β·Β·Β· ========== ============ ============
-- use_bottleneck
---------- -------------------------
method True False
========== ============ ============
spearman 1.34Β±0.2ms 1.35Β±0.3ms
pearson 317Β±60ΞΌs 319Β±70ΞΌs
========== ============ ============
[ 64.29%] Β·Β·Β· stat_ops.Correlation.time_corr_wide ok
[ 64.29%] Β·Β·Β· ========== ========== ==========
-- use_bottleneck
---------- ---------------------
method True False
========== ========== ==========
spearman 286Β±40ms 273Β±10ms
pearson 176Β±10ms 178Β±10ms
========== ========== ==========
[ 67.86%] Β·Β·Β· stat_ops.Correlation.time_corr_wide_nans ok
[ 67.86%] Β·Β·Β· ========== ============ ============
-- use_bottleneck
---------- -------------------------
method True False
========== ============ ============
spearman 3.23Β±0.02s 3.20Β±0.01s
pearson 196Β±7ms 192Β±10ms
========== ============ ============
[ 71.43%] Β·Β·Β· stat_ops.Correlation.time_corrwith_cols ok
[ 71.43%] Β·Β·Β· ========== ============ ============
-- use_bottleneck
---------- -------------------------
method True False
========== ============ ============
spearman 24.2Β±1ms 25.5Β±1ms
pearson 36.1Β±0.3ms 36.2Β±0.4ms
========== ============ ============
[ 75.00%] Β·Β·Β· stat_ops.Correlation.time_corrwith_rows ok
[ 75.00%] Β·Β·Β· ========== ========= ==========
-- use_bottleneck
---------- --------------------
method True False
========== ========= ==========
spearman 549Β±4ms 551Β±3ms
pearson 884Β±7ms 890Β±20ms
========== ========= ==========
[ 75.00%] Β· For pandas commit 165d5ee4 <master> (round 2/2):
[ 75.00%] Β·Β· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt...
[ 75.00%] Β·Β· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 78.57%] Β·Β·Β· stat_ops.Correlation.peakmem_corr_wide ok
[ 78.57%] Β·Β·Β· ========== ====== =======
-- use_bottleneck
---------- --------------
method True False
========== ====== =======
spearman 108M 108M
pearson 106M 106M
========== ====== =======
[ 82.14%] Β·Β·Β· stat_ops.Correlation.time_corr ok
[ 82.14%] Β·Β·Β· ========== ============ =============
-- use_bottleneck
---------- --------------------------
method True False
========== ============ =============
spearman 10.2Β±0.2ms 10.1Β±0.2ms
pearson 3.51Β±0.2ms 3.54Β±0.09ms
========== ============ =============
[ 85.71%] Β·Β·Β· stat_ops.Correlation.time_corr_series ok
[ 85.71%] Β·Β·Β· ========== ============= =============
-- use_bottleneck
---------- ---------------------------
method True False
========== ============= =============
spearman 1.52Β±0.03ms 1.26Β±0.01ms
pearson 316Β±10ΞΌs 389Β±0.6ΞΌs
========== ============= =============
[ 89.29%] Β·Β·Β· stat_ops.Correlation.time_corr_wide ok
[ 89.29%] Β·Β·Β· ========== ========== ==========
-- use_bottleneck
---------- ---------------------
method True False
========== ========== ==========
spearman 359Β±20ms 288Β±10ms
pearson 186Β±6ms 184Β±7ms
========== ========== ==========
[ 92.86%] Β·Β·Β· stat_ops.Correlation.time_corr_wide_nans ok
[ 92.86%] Β·Β·Β· ========== ============ ============
-- use_bottleneck
---------- -------------------------
method True False
========== ============ ============
spearman 3.29Β±0.01s 3.26Β±0.03s
pearson 195Β±6ms 203Β±5ms
========== ============ ============
[ 96.43%] Β·Β·Β· stat_ops.Correlation.time_corrwith_cols ok
[ 96.43%] Β·Β·Β· ========== ============ ============
-- use_bottleneck
---------- -------------------------
method True False
========== ============ ============
spearman 24.4Β±2ms 24.8Β±0.9ms
pearson 35.8Β±0.5ms 36.1Β±0.5ms
========== ============ ============
[100.00%] Β·Β·Β· stat_ops.Correlation.time_corrwith_rows ok
[100.00%] Β·Β·Β· ========== ========== ==========
-- use_bottleneck
---------- ---------------------
method True False
========== ========== ==========
spearman 551Β±6ms 555Β±7ms
pearson 894Β±10ms 899Β±10ms
========== ========== ==========
before after ratio
[165d5ee4] [cd59acf5]
<master> <fix-kendall-issues>
- 3.54Β±0.09ms 2.84Β±0.4ms 0.80 stat_ops.Correlation.time_corr('pearson', False)
SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY.
PERFORMANCE INCREASED.
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} | 3 | 2019-11-04T22:24:21Z | 2019-11-07T01:34:51Z | 2019-11-07T01:34:47Z | CONTRIBUTOR | null | This PR renames the various ``*label*`` names in core/groupby to like-named ``*codes*``.
I think the name ``label`` can be confused by the single values in a index, and ``codes`` sound smore like an array of ints, so by renaming we get a cleaner nomenclature, IMO.
All these attributes/methods are internal, so no deprecations needed. | {
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} | 3 | 2019-11-04T22:38:36Z | 2019-12-15T22:11:58Z | 2019-12-15T22:11:58Z | CONTRIBUTOR | null | ```python
from collections import deque
pd.to_datetime(deque([Timestamp('2010-06-02 09:30:00')] * 51))
```
core.tools.datetimes.should_cache gives `sequence index must be integer, not 'slice` at `unique(arg[:check_count])`
if deque is not expected it would make more sense to give a better message, otherwise support?
looks like a "good first issue" ?
version 0.25+ (i think it works on 0.24 but i only tested 0.25) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/29404 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29404/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29404/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29404/events | https://github.com/pandas-dev/pandas/pull/29404 | 517,454,962 | MDExOlB1bGxSZXF1ZXN0MzM2NTIxNzg3 | 29,404 | BUG: GH29310 HDF file compression not working | {
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] | closed | false | null | [] | null | 9 | 2019-11-04T23:06:06Z | 2020-02-07T07:55:31Z | 2020-02-07T07:55:30Z | NONE | null | - [x] closes #29310
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
Re #29310, the complib and complevel parameters were not being passed down all the way previously, hence HDF compression not working.
I noticed that the implementation of to_hdf() specifies that compression is not allowed for fixed formats:
` if not s.is_table and complib:
raise ValueError("Compression not supported on Fixed format stores")`
I'm guessing that means the performance comparison section for https://github.com/pandas-dev/pandas/pull/28890/files will also need to be updated to remove the test_fixed_compress test @WuraolaOyewusi?
Also, after the update, the following test is currently failing:
due to a ValueError for using compression with a fixed format, and I'm not sure as to why the expected behaviour for this test is what it is? Why should setting complib disable compression? I would appreciate any further info on that.
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} | 28 | 2019-11-04T23:20:57Z | 2019-12-05T22:29:50Z | 2019-12-05T19:00:16Z | CONTRIBUTOR | null | - [x] closes #17261
- [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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Help please. I am having trouble downloading scikit-learn and scipy.
The thing is: I installed pandas without trouble..
Thank you! | {
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} | 0 | 2019-11-05T07:53:29Z | 2019-11-09T19:18:31Z | 2019-11-09T19:18:31Z | MEMBER | null | xref #22539
`assert_series_equal` and `assert_frame_equal` do not return `True` or` False`.
```
See Also
--------
Series.eq : Compare two Series objects of the same length
and return a Series where each element is True if the element
in each Series is equal, False otherwise.
DataFrame.eq : Compare two DataFrame objects of the same shape and
return a DataFrame where each element is True if the respective
element in each DataFrame is equal, False otherwise.
assert_series_equal : Return True if left and right Series are equal,
False otherwise.
assert_frame_equal : Return True if left and right DataFrames are
equal, False otherwise.
numpy.array_equal : Return True if two arrays have the same shape
and elements, False otherwise.
```
also the entries in `See Also` for `assert_series_equal` and `assert_frame_equal` don't link to anything.
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.equals.html#pandas-dataframe-equals
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will update with reproducible example in a couple of days
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} | 1 | 2019-11-05T08:24:51Z | 2019-11-06T06:37:57Z | 2019-11-05T15:19:21Z | CONTRIBUTOR | null | Fixed SS03 errors for:
`pandas.Timestamp.combine`; `pandas.Timestamp.fromordinal`; `pandas.Period.strftime`; `pandas.Interval.closed`; `pandas.Interval.left`; `pandas.Interval.length`; `pandas.Interval.mid`; `pandas.Interval.right`.
- [x] xref to #29315
- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Similar to #28053 I could not find methods for `pandas.Timestamp.isoweekday` or `pandas.Timestamp.weekday`. This was not resolved in #28053. I think this may be due to docstrings in the original python datetime file.
Timestamp import _Timestamp which imports datetime. Neither Timestamp nor _Timestamp have `isoweekday` or `weekday` methods.
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"default": false,
"description": "Memory or execution speed performance",
"id": 8935311,
"name": "Performance",
"node_id": "MDU6TGFiZWw4OTM1MzEx",
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"default"... | open | false | null | [] | null | 2 | 2019-11-05T09:52:21Z | 2020-04-20T00:37:54Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import numpy as np
import pandas as pd
import gc
import os
import psutil
def get_process_memory():
return round(psutil.Process(os.getpid()).memory_info().rss / float(2 ** 20), 2)
test_dict = {}
for i in range(0, 50):
test_dict[i] = np.empty(10)
dfs = []
for i in range(0, 1000):
df = pd.DataFrame(test_dict)
dfs.append(df)
gc.collect()
# before
print('memory usage (before "memory_usage"):\t{} MB'.format(get_process_memory()))
for df in dfs:
df.memory_usage(index=True, deep=True)
gc.collect()
# after
print('memory usage (after "memory_usage"):\t{} MB'.format(get_process_memory()))
```
#### Problem description
Dataframe's memory_usage function has memory leak. Memory usage after executing 'memory_usage' function should be the same as before.
<img width="399" alt="ζͺε±2019-11-05δΈε5 44 25" src="https://user-images.githubusercontent.com/7194638/68196715-f390ce00-fff3-11e9-939a-e84d850673e8.png">
#### Expected Output
None
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.16.final.0
python-bits: 64
OS: Darwin
OS-release: 19.0.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: zh_CN.UTF-8
LOCALE: None.None
pandas: 0.24.2
pytest: None
pip: 19.3.1
setuptools: 19.6.1
Cython: 0.29.13
numpy: 1.16.5
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.8.1
pytz: 2019.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/29412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/29412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/29412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/29412/events | https://github.com/pandas-dev/pandas/issues/29412 | 517,821,743 | MDU6SXNzdWU1MTc4MjE3NDM= | 29,412 | Remove all preprocessing from PlotAccessor.__call__ | {
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"de... | open | false | null | [] | null | 2 | 2019-11-05T14:51:47Z | 2021-07-22T05:58:12Z | null | CONTRIBUTOR | null | In https://github.com/pandas-dev/pandas/pull/28647, we discovered that `PlotAccessor.__call___` does quite a bit of preprocessing of the data before handing it off to the backend.
https://github.com/pandas-dev/pandas/blob/399212673ea8101a65d95830604edb633da0860d/pandas/plotting/_core.py#L728-L794
Depending on the plot kind and backend, *some* of this preprocesing may not be appropriate. The backend might want to see the "raw" data. That's not to say we shouldn't do any preprocessing though. We'll need some feedback from backend authors on what should be done before handing it off. | {
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} | [] | closed | false | null | [] | null | 7 | 2019-11-05T16:01:28Z | 2019-11-06T11:04:36Z | 2019-11-06T11:04:35Z | MEMBER | null | When running the command:
```
python -m pip install -r requirements-dev.txt
```
I got an error massage that says:
```
ERROR: botocore 1.13.9 has requirement python-dateutil<2.8.1,>=2.1; python_version >= "2.7", but you'll have python-dateutil 2.8.1 which is incompatible.
```
But the followed commands haven't raised an error:
1. ```python setup.py build_ext --inplace -j 0```
2. ```python -m pip install -e . --no-build-isolation --no-use-pep517```
P.S
Everything seems normal ATM, just never saw that error message before.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : 399212673ea8101a65d95830604edb633da0860d
python : 3.7.4.final.0
python-bits : 64
OS : Linux
OS-release : 5.3.8.a-1-hardened
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.26.0.dev0+781.g399212673
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 41.6.0
Cython : 0.29.14
pytest : 5.2.2
hypothesis : 4.43.3
sphinx : 2.2.1
blosc : 1.8.1
feather : None
xlsxwriter : 1.2.2
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.8.1
bottleneck : 1.2.1
fastparquet : 0.3.2
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.0
pandas_gbq : None
pyarrow : 0.15.1
pytables : None
s3fs : 0.3.5
scipy : 1.3.1
sqlalchemy : 1.3.10
tables : 3.6.1
xarray : 0.14.0
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.2
</details>
Screen shot of the error:
The full text of image above:
```
venv-pandas) [bummy@null pandas-MomIsBestFriend]$ python -m pip install -r requirements-dev.txt
Collecting git+https://github.com/pandas-dev/pandas-sphinx-theme.git@master (from -r requirements-dev.txt (line 68))
Cloning https://github.com/pandas-dev/pandas-sphinx-theme.git (to revision master) to /tmp/pip-req-build-vdm84z_f
Running command git clone -q https://github.com/pandas-dev/pandas-sphinx-theme.git /tmp/pip-req-build-vdm84z_f
Collecting numpy>=1.15
Downloading https://files.pythonhosted.org/packages/00/4a/e34fce8f18c0e052c2b49f1b3713469d855f7662d58ae2b82a88341e865b/numpy-1.17.3-cp37-cp37m-manylinux1_x86_64.whl (20.0MB)
|ββββββββββββββββββββββββββββββββ| 20.0MB 1.2MB/s
Collecting python-dateutil>=2.6.1
Downloading https://files.pythonhosted.org/packages/d4/70/d60450c3dd48ef87586924207ae8907090de0b306af2bce5d134d78615cb/python_dateutil-2.8.1-py2.py3-none-any.whl (227kB)
|ββββββββββββββββββββββββββββββββ| 235kB 8.7MB/s
Collecting pytz
Downloading https://files.pythonhosted.org/packages/e7/f9/f0b53f88060247251bf481fa6ea62cd0d25bf1b11a87888e53ce5b7c8ad2/pytz-2019.3-py2.py3-none-any.whl (509kB)
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Collecting asv
Downloading https://files.pythonhosted.org/packages/6e/94/4521cc0183a5656de9470452ddd2b6170a2d04ba9b18b84c597db09b8b0d/asv-0.4.1.tar.gz (470kB)
|ββββββββββββββββββββββββββββββββ| 471kB 20.9MB/s
Collecting cython>=0.29.13
Downloading https://files.pythonhosted.org/packages/d8/58/2deb24de3c10cc4c0f09639b46f4f4b50059f0fdc785128a57dd9fdce026/Cython-0.29.14-cp37-cp37m-manylinux1_x86_64.whl (2.1MB)
|ββββββββββββββββββββββββββββββββ| 2.1MB 6.6MB/s
Collecting black<=19.3b0
Downloading https://files.pythonhosted.org/packages/30/62/cf549544a5fe990bbaeca21e9c419501b2de7a701ab0afb377bc81676600/black-19.3b0-py36-none-any.whl (89kB)
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Collecting cpplint
Downloading https://files.pythonhosted.org/packages/30/9f/a44a503d457ebdb78298a1cb4dad99c1e506b901b300829fc28f3b3ddd6a/cpplint-1.4.4-py3-none-any.whl (73kB)
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Collecting flake8
Downloading https://files.pythonhosted.org/packages/f8/1f/7ea40d1e4146ea55dbab41cda1376db092a75794914169aabd7e8d7a7def/flake8-3.7.9-py2.py3-none-any.whl (69kB)
|ββββββββββββββββββββββββββββββββ| 71kB 983kB/s
Collecting flake8-comprehensions
Downloading https://files.pythonhosted.org/packages/76/1f/3a2eaf62799c2c7409db6eb71fb34b8ba64b4a0fcdbf26e1063349062825/flake8_comprehensions-3.0.1-py3-none-any.whl
Collecting flake8-rst<=0.7.0,>=0.6.0
Downloading https://files.pythonhosted.org/packages/81/50/96c9207354feae7ff27dcbd5e27585bac55a1a7b539f6b15e1fced1904a8/flake8_rst-0.7.0-py3-none-any.whl
Collecting isort
Downloading https://files.pythonhosted.org/packages/e5/b0/c121fd1fa3419ea9bfd55c7f9c4fedfec5143208d8c7ad3ce3db6c623c21/isort-4.3.21-py2.py3-none-any.whl (42kB)
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Collecting mypy
Downloading https://files.pythonhosted.org/packages/8f/b0/9b6488f6ff5c3499f9840b46b55affccf929c281eb7108abb19c9ca21cd6/mypy-0.740-cp37-cp37m-manylinux1_x86_64.whl (23.2MB)
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Collecting pycodestyle
Downloading https://files.pythonhosted.org/packages/0e/0c/04a353e104d2f324f8ee5f4b32012618c1c86dd79e52a433b64fceed511b/pycodestyle-2.5.0-py2.py3-none-any.whl (51kB)
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Collecting gitpython
Downloading https://files.pythonhosted.org/packages/aa/25/9fd9f0b05408021736a22ae73f837152c132e4ea85cdd71d186e24efec31/GitPython-3.0.4-py3-none-any.whl (454kB)
|ββββββββββββββββββββββββββββββββ| 460kB 7.5MB/s
Collecting sphinx
Downloading https://files.pythonhosted.org/packages/1d/58/a547b02946af1cf337c701cafcf3267065c1c83d6e701f540961f4907b5d/Sphinx-2.2.1-py3-none-any.whl (3.3MB)
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Collecting numpydoc>=0.9.0
Downloading https://files.pythonhosted.org/packages/6a/f3/7cfe4c616e4b9fe05540256cc9c6661c052c8a4cec2915732793b36e1843/numpydoc-0.9.1.tar.gz
Collecting nbconvert>=5.4.1
Downloading https://files.pythonhosted.org/packages/79/6c/05a569e9f703d18aacb89b7ad6075b404e8a4afde2c26b73ca77bb644b14/nbconvert-5.6.1-py2.py3-none-any.whl (455kB)
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Collecting nbsphinx
Downloading https://files.pythonhosted.org/packages/39/1f/c912f2f95d53d818dc76867f950883ae8a92849b7bef12a783106143cf08/nbsphinx-0.4.3-py2.py3-none-any.whl
Collecting pandoc
Downloading https://files.pythonhosted.org/packages/49/b1/d2d4b30ee81ea5cb7aee5ba3591752a637fdc49d0a42fa9683874b60b9fb/pandoc-1.0.2.tar.gz (488kB)
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Collecting dask
Downloading https://files.pythonhosted.org/packages/f8/70/b7e55088c6a6c9d5e786c85738d92e99c4bf085fc4009d5ffe483cd6b44f/dask-2.6.0-py3-none-any.whl (760kB)
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Collecting toolz>=0.7.3
Downloading https://files.pythonhosted.org/packages/22/8e/037b9ba5c6a5739ef0dcde60578c64d49f45f64c5e5e886531bfbc39157f/toolz-0.10.0.tar.gz (49kB)
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Collecting fsspec>=0.5.1
Downloading https://files.pythonhosted.org/packages/54/18/59f1850336568168144a746afa7199a0311f1a89bdb7b0d8e8b50d2c3d93/fsspec-0.5.2.tar.gz (64kB)
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Collecting partd>=0.3.10
Downloading https://files.pythonhosted.org/packages/8b/17/09c352519da1db31634979c3aa9126078e9ece0f561c5f641e0649b78905/partd-1.0.0-py2.py3-none-any.whl
Collecting cloudpickle>=0.2.1
Downloading https://files.pythonhosted.org/packages/c1/49/334e279caa3231255725c8e860fa93e72083567625573421db8875846c14/cloudpickle-1.2.2-py2.py3-none-any.whl
Collecting markdown
Downloading https://files.pythonhosted.org/packages/c0/4e/fd492e91abdc2d2fcb70ef453064d980688762079397f779758e055f6575/Markdown-3.1.1-py2.py3-none-any.whl (87kB)
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Collecting feedparser
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Collecting pyyaml
Downloading https://files.pythonhosted.org/packages/e3/e8/b3212641ee2718d556df0f23f78de8303f068fe29cdaa7a91018849582fe/PyYAML-5.1.2.tar.gz (265kB)
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Collecting requests
Downloading https://files.pythonhosted.org/packages/51/bd/23c926cd341ea6b7dd0b2a00aba99ae0f828be89d72b2190f27c11d4b7fb/requests-2.22.0-py2.py3-none-any.whl (57kB)
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Collecting future<1.0
Downloading https://files.pythonhosted.org/packages/45/0b/38b06fd9b92dc2b68d58b75f900e97884c45bedd2ff83203d933cf5851c9/future-0.18.2.tar.gz (829kB)
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Collecting ecdsa<1.0
Downloading https://files.pythonhosted.org/packages/a6/81/2b170b460c84fdc8700cf08aa077ac6a9ff41f4ad3f05d0b3a64ba9f8f2e/ecdsa-0.13.3-py2.py3-none-any.whl (52kB)
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Collecting rsa
Downloading https://files.pythonhosted.org/packages/02/e5/38518af393f7c214357079ce67a317307936896e961e35450b70fad2a9cf/rsa-4.0-py2.py3-none-any.whl
Collecting websocket-client>=0.32.0
Downloading https://files.pythonhosted.org/packages/29/19/44753eab1fdb50770ac69605527e8859468f3c0fd7dc5a76dd9c4dbd7906/websocket_client-0.56.0-py2.py3-none-any.whl (200kB)
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Collecting jsonpickle
Downloading https://files.pythonhosted.org/packages/07/07/c157520a3ebd166c8c24c6ae0ecae7c3968eb4653ff0e5af369bb82f004d/jsonpickle-1.2-py2.py3-none-any.whl
Collecting wrapt
Downloading https://files.pythonhosted.org/packages/23/84/323c2415280bc4fc880ac5050dddfb3c8062c2552b34c2e512eb4aa68f79/wrapt-1.11.2.tar.gz
Collecting jsonpatch
Downloading https://files.pythonhosted.org/packages/86/7e/035d19a73306278673039f0805b863be8798057cc1b4008b9c8c7d1d32a3/jsonpatch-1.24-py2.py3-none-any.whl
Collecting aws-sam-translator>=1.15.1
Downloading https://files.pythonhosted.org/packages/1c/1e/134c579a98d070cb8d5801c317fb0f21018629e7fa0b8de82a408e61d1c7/aws-sam-translator-1.15.1.tar.gz (110kB)
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Collecting apipkg>=1.4
Downloading https://files.pythonhosted.org/packages/67/08/4815a09603fc800209431bec5b8bd2acf2f95abdfb558a44a42507fb94da/apipkg-1.5-py2.py3-none-any.whl
Collecting pyrsistent>=0.14.0
Downloading https://files.pythonhosted.org/packages/30/86/53a88c0a57698fa228db29a4000c28f4124823010388cb7042fe6e2be8dd/pyrsistent-0.15.5.tar.gz (107kB)
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Collecting ptyprocess; os_name != "nt"
Downloading https://files.pythonhosted.org/packages/d1/29/605c2cc68a9992d18dada28206eeada56ea4bd07a239669da41674648b6f/ptyprocess-0.6.0-py2.py3-none-any.whl
Collecting parso>=0.5.0
Downloading https://files.pythonhosted.org/packages/a3/bd/bf4e5bd01d79906e5b945a7af033154da49fd2b0d5b5c705a21330323305/parso-0.5.1-py2.py3-none-any.whl (95kB)
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Collecting llvmlite>=0.30.0dev0
Downloading https://files.pythonhosted.org/packages/1f/3e/642ffb29ed35ca5e93f171ba327452bdee81ec76f2d711ef0f15b411928a/llvmlite-0.30.0-cp37-cp37m-manylinux1_x86_64.whl (20.2MB)
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Collecting pycparser
Downloading https://files.pythonhosted.org/packages/68/9e/49196946aee219aead1290e00d1e7fdeab8567783e83e1b9ab5585e6206a/pycparser-2.19.tar.gz (158kB)
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Collecting pyasn1>=0.1.3
Downloading https://files.pythonhosted.org/packages/a1/71/8f0d444e3a74e5640a3d5d967c1c6b015da9c655f35b2d308a55d907a517/pyasn1-0.4.7-py2.py3-none-any.whl (76kB)
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Collecting jsonpointer>=1.9
Downloading https://files.pythonhosted.org/packages/18/b0/a80d29577c08eea401659254dfaed87f1af45272899e1812d7e01b679bc5/jsonpointer-2.0-py2.py3-none-any.whl
ERROR: botocore 1.13.9 has requirement python-dateutil<2.8.1,>=2.1; python_version >= "2.7", but you'll have python-dateutil 2.8.1 which is incompatible.
Installing collected packages: numpy, six, python-dateutil, pytz, asv, cython, attrs, click, toml, appdirs, black, cpplint, mccabe, entrypoints, pycodestyle, pyflakes, flake8, more-itertools, zipp, importlib-metadata, flake8-comprehensions, flake8-rst, isort, typing-extensions, typed-ast, mypy-extensions, mypy, smmap2, gitdb2, gitpython, alabaster, sphinxcontrib-qthelp, snowballstemmer, pyparsing, packaging, sphinxcontrib-htmlhelp, imagesize, sphinxcontrib-devhelp, MarkupSafe, jinja2, docutils, babel, urllib3, chardet, certifi, idna, requests, Pygments, sphinxcontrib-serializinghtml, sphinxcontrib-applehelp, sphinxcontrib-jsmath, sphinx, numpydoc, decorator, ipython-genutils, traitlets, jupyter-core, defusedxml, webencodings, bleach, testpath, mistune, pyrsistent, jsonschema, nbformat, pandocfilters, nbconvert, nbsphinx, ply, pandoc, dask, toolz, fsspec, locket, partd, cloudpickle, markdown, feedparser, pyyaml, jmespath, botocore, s3transfer, boto3, hypothesis, boto, pycparser, cffi, cryptography, zope.interface, datetime, xmltodict, werkzeug, future, ecdsa, pyasn1, rsa, python-jose, mock, websocket-client, docker, jsondiff, jsonpickle, wrapt, aws-xray-sdk, responses, jsonpointer, jsonpatch, aws-sam-translator, cfn-lint, sshpubkeys, moto, wcwidth, py, atomicwrites, pluggy, pytest, coverage, pytest-cov, pytest-mock, apipkg, execnet, pytest-forked, pytest-xdist, scipy, kiwisolver, cycler, matplotlib, pandas, seaborn, patsy, statsmodels, pickleshare, prompt-toolkit, backcall, parso, jedi, ptyprocess, pexpect, ipython, pyzmq, Send2Trash, tornado, jupyter-client, ipykernel, prometheus-client, terminado, notebook, widgetsnbextension, ipywidgets, blosc, bottleneck, numexpr, soupsieve, beautifulsoup4, llvmlite, numba, thrift, fastparquet, html5lib, lxml, jdcal, et-xmlfile, openpyxl, pyarrow, PyQt5-sip, pyqt5, tables, python-snappy, s3fs, sqlalchemy, xarray, xlrd, xlsxwriter, xlwt, odfpy, pyreadstat, pandas-sphinx-theme
Running setup.py install for asv ... done
Running setup.py install for numpydoc ... done
Running setup.py install for pyrsistent ... done
Running setup.py install for pandocfilters ... done
Running setup.py install for pandoc ... done
Running setup.py install for toolz ... done
Running setup.py install for fsspec ... done
Running setup.py install for locket ... done
Running setup.py install for feedparser ... done
Running setup.py install for pyyaml ... done
Running setup.py install for pycparser ... done
Running setup.py install for future ... done
Running setup.py install for jsondiff ... done
Running setup.py install for wrapt ... done
Running setup.py install for aws-sam-translator ... done
Running setup.py install for moto ... done
Running setup.py install for backcall ... done
Running setup.py install for tornado ... done
Running setup.py install for prometheus-client ... done
Running setup.py install for blosc ... done
Running setup.py install for bottleneck ... done
Running setup.py install for thrift ... done
Running setup.py install for fastparquet ... done
Running setup.py install for et-xmlfile ... done
Running setup.py install for openpyxl ... done
Running setup.py install for python-snappy ... done
Running setup.py install for s3fs ... done
Running setup.py install for sqlalchemy ... done
Running setup.py install for odfpy ... done
Running setup.py install for pandas-sphinx-theme ... done
Successfully installed MarkupSafe-1.1.1 PyQt5-sip-12.7.0 Pygments-2.4.2 Send2Trash-1.5.0 alabaster-0.7.12 apipkg-1.5 appdirs-1.4.3 asv-0.4.1 atomicwrites-1.3.0 attrs-19.3.0 aws-sam-translator-1.15.1 aws-xray-sdk-2.4.2 babel-2.7.0 backcall-0.1.0 beautifulsoup4-4.8.1 black-19.3b0 bleach-3.1.0 blosc-1.8.1 boto-2.49.0 boto3-1.10.9 botocore-1.13.9 bottleneck-1.2.1 certifi-2019.9.11 cffi-1.13.2 cfn-lint-0.24.8 chardet-3.0.4 click-7.0 cloudpickle-1.2.2 coverage-4.5.4 cpplint-1.4.4 cryptography-2.8 cycler-0.10.0 cython-0.29.14 dask-2.6.0 datetime-4.3 decorator-4.4.1 defusedxml-0.6.0 docker-4.1.0 docutils-0.15.2 ecdsa-0.13.3 entrypoints-0.3 et-xmlfile-1.0.1 execnet-1.7.1 fastparquet-0.3.2 feedparser-5.2.1 flake8-3.7.9 flake8-comprehensions-3.0.1 flake8-rst-0.7.0 fsspec-0.5.2 future-0.18.2 gitdb2-2.0.6 gitpython-3.0.4 html5lib-1.0.1 hypothesis-4.43.3 idna-2.8 imagesize-1.1.0 importlib-metadata-0.23 ipykernel-5.1.3 ipython-7.9.0 ipython-genutils-0.2.0 ipywidgets-7.5.1 isort-4.3.21 jdcal-1.4.1 jedi-0.15.1 jinja2-2.10.3 jmespath-0.9.4 jsondiff-1.1.2 jsonpatch-1.24 jsonpickle-1.2 jsonpointer-2.0 jsonschema-3.1.1 jupyter-client-5.3.4 jupyter-core-4.6.1 kiwisolver-1.1.0 llvmlite-0.30.0 locket-0.2.0 lxml-4.4.1 markdown-3.1.1 matplotlib-3.1.1 mccabe-0.6.1 mistune-0.8.4 mock-3.0.5 more-itertools-7.2.0 moto-1.3.13 mypy-0.740 mypy-extensions-0.4.3 nbconvert-5.6.1 nbformat-4.4.0 nbsphinx-0.4.3 notebook-6.0.2 numba-0.46.0 numexpr-2.7.0 numpy-1.17.3 numpydoc-0.9.1 odfpy-1.4.0 openpyxl-3.0.0 packaging-19.2 pandas-0.25.3 pandas-sphinx-theme-0.0.1.dev0 pandoc-1.0.2 pandocfilters-1.4.2 parso-0.5.1 partd-1.0.0 patsy-0.5.1 pexpect-4.7.0 pickleshare-0.7.5 pluggy-0.13.0 ply-3.11 prometheus-client-0.7.1 prompt-toolkit-2.0.10 ptyprocess-0.6.0 py-1.8.0 pyarrow-0.15.1 pyasn1-0.4.7 pycodestyle-2.5.0 pycparser-2.19 pyflakes-2.1.1 pyparsing-2.4.3 pyqt5-5.13.2 pyreadstat-0.2.9 pyrsistent-0.15.5 pytest-5.2.2 pytest-cov-2.8.1 pytest-forked-1.1.3 pytest-mock-1.11.2 pytest-xdist-1.30.0 python-dateutil-2.8.1 python-jose-3.0.1 python-snappy-0.5.4 pytz-2019.3 pyyaml-5.1.2 pyzmq-18.1.0 requests-2.22.0 responses-0.10.6 rsa-4.0 s3fs-0.3.5 s3transfer-0.2.1 scipy-1.3.1 seaborn-0.9.0 six-1.12.0 smmap2-2.0.5 snowballstemmer-2.0.0 soupsieve-1.9.5 sphinx-2.2.1 sphinxcontrib-applehelp-1.0.1 sphinxcontrib-devhelp-1.0.1 sphinxcontrib-htmlhelp-1.0.2 sphinxcontrib-jsmath-1.0.1 sphinxcontrib-qthelp-1.0.2 sphinxcontrib-serializinghtml-1.1.3 sqlalchemy-1.3.10 sshpubkeys-3.1.0 statsmodels-0.10.1 tables-3.6.1 terminado-0.8.2 testpath-0.4.4 thrift-0.11.0 toml-0.10.0 toolz-0.10.0 tornado-6.0.3 traitlets-4.3.3 typed-ast-1.4.0 typing-extensions-3.7.4.1 urllib3-1.25.6 wcwidth-0.1.7 webencodings-0.5.1 websocket-client-0.56.0 werkzeug-0.16.0 widgetsnbextension-3.5.1 wrapt-1.11.2 xarray-0.14.0 xlrd-1.2.0 xlsxwriter-1.2.2 xlwt-1.3.0 xmltodict-0.12.0 zipp-0.6.0 zope.interface-4.6.0
(venv-pandas) [bummy@null pandas-MomIsBestFriend]$
```
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