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GroupBy OHLC Error When Used in .agg with Other Functions #21716

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WillAyd opened this issue Jul 3, 2018 · 0 comments · Fixed by #21769
Closed

GroupBy OHLC Error When Used in .agg with Other Functions #21716

WillAyd opened this issue Jul 3, 2018 · 0 comments · Fixed by #21769
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@WillAyd
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WillAyd commented Jul 3, 2018

Code Sample, a copy-pastable example if possible

In [12]: np.random.seed(1234)
In [13]: df = pd.DataFrame(np.random.rand(10, 1), 
    index=pd.date_range(start='2018-01-01', freq='5H', periods=10))

# This call works fine
In [14]: df.groupby(pd.Grouper(freq='D')).agg(['ohlc', 'sum'])
Out[14]: 
                   0                                        
                ohlc                                     sum
                open      high       low     close         0
2018-01-01  0.191519  0.785359  0.191519  0.779976  2.816690
2018-01-02  0.272593  0.958139  0.272593  0.875933  3.185001

# Switching the order of ops in agg doesn't work
In [16]: df.groupby(pd.Grouper(freq='D')).agg(['sum', 'ohlc'])
ValueError: no results

I noticed that ohlc gets special treatment in some of the groupby functions to assign names. That occurs while iterating over self._iterate_slices however and therefore may be dependent upon the order of evaluation (have not confirmed in looking at code)

INSTALLED VERSIONS

commit: 7cd2679
python: 3.6.4.final.0
python-bits: 64
OS: Darwin
OS-release: 17.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.0.dev0+205.g7cd267998
pytest: 3.4.1
pip: 10.0.1
setuptools: 38.5.1
Cython: 0.27.3
numpy: 1.14.1
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.0
IPython: 6.2.1
sphinx: 1.7.0
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2018.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.1.2
openpyxl: 2.5.0
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.5
pymysql: 0.8.0
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: 0.1.3
fastparquet: 0.1.4
pandas_gbq: 0.4.1
pandas_datareader: None
gcsfs: None

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