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BUG: pd.qcut with q=1 and input with identical values #15431
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this is the same as #15428 so ideally let's solve in the same PR., just list it as a separate case there. |
I am not sure I am following your reasoning. From my point of view It's a different issue (totally different code bug) and they are also two different functions (qcut vs cut). |
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BUG: pd.qcut with q=1 and input with identical values
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BUG: pd.qcut with q=1 and input with identical values
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BUG: pd.qcut with q=1 and input with identical values
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The special case of running pd.cut() qith bins=1 an input containing all 0s raises a ValueError closes #15428 closes #15431 Author: Luca Scarabello <[email protected]> Author: Luca <[email protected]> Closes #15437 from luca-s/issue_15428 and squashes the following commits: 1248987 [Luca] rebased on master def84ba [Luca] Yet another implementation attempt 692503a [Luca Scarabello] Improved solution: using same approach as pd.cut b7d92dc [Luca] Added 'allow' duplicates option to _bins_to_cuts f56a27f [Luca Scarabello] Issue #15431 55806cf [Luca Scarabello] BUG: pd.cut with bins=1 and input all 0s
AnkurDedania
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Mar 21, 2017
The special case of running pd.cut() qith bins=1 an input containing all 0s raises a ValueError closes pandas-dev#15428 closes pandas-dev#15431 Author: Luca Scarabello <[email protected]> Author: Luca <[email protected]> Closes pandas-dev#15437 from luca-s/issue_15428 and squashes the following commits: 1248987 [Luca] rebased on master def84ba [Luca] Yet another implementation attempt 692503a [Luca Scarabello] Improved solution: using same approach as pd.cut b7d92dc [Luca] Added 'allow' duplicates option to _bins_to_cuts f56a27f [Luca Scarabello] Issue pandas-dev#15431 55806cf [Luca Scarabello] BUG: pd.cut with bins=1 and input all 0s
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Code Sample, a copy-pastable example if possible
Problem description
If the input contains identical values pd.qcut fails even with q=1. I had a look at the code and I can try to relax the check to allow this specific case to pass and avoid the exception, but then I have to make sure the code can handle a single edge.
Expected Output
Output of
pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.8.0-36-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None
pandas: 0.19.2
nose: 1.3.7
pip: 8.1.1
setuptools: 32.3.1
Cython: 0.23.4
numpy: 1.12.0
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999
httplib2: 0.9.1
apiclient: None
sqlalchemy: 1.1.4
pymysql: None
psycopg2: None
jinja2: 2.8.1
boto: None
pandas_datareader: 0.2.1
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