ENH: Add DatetimeIndexResampler.nlargest · Issue #17791 · pandas-dev/pandas (original) (raw)
Code Sample, a copy-pastable example if possible
With this setup:
import numpy as np n = 1000 dates = pd.date_range(start='2010-01-01', periods=n) rain_random = pd.Series(data=np.random.uniform(size=n), index=dates)
these two operations given different results:
rain_random.groupby(rain_random.index.year).nlargest(3)
rain_random.resample('A').nlargest(3)
Problem description
The Series.resample().nlargest()
operation is inconsistent with DataFrame.resample()[column].nlargest()
and the groupby
equivalent. It emits a warning
Output:
/Users/schofield/miniconda/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning:
.resample() is now a deferred operation
You called nlargest(...) on this deferred object which materialized it into a series
by implicitly taking the mean. Use .resample(...).mean() instead
"""Entry point for launching an IPython kernel.
Out[427]:
2010-12-31 0.507550
2012-12-31 0.490082
2011-12-31 0.478356
dtype: float64
Expected output:
Date Date
1930-12-31 1930-10-06 288.135370
1930-10-05 285.587734
1930-10-07 259.439935
1930-10-08 227.587389
1930-10-09 190.054844
1931-12-31 1931-01-26 3052.104566
1931-01-25 2839.126102
1931-01-29 2196.167129
1931-02-01 1953.331709
1931-01-27 1893.975328
1932-12-31 1932-01-19 9526.953864
1932-01-20 4278.291105
1932-03-03 2952.348903
1932-03-02 2946.385433
1932-03-04 2098.108897
pd.show_versions() output:
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 16.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_AU.UTF-8
LOCALE: en_AU.UTF-8
pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: 0.5.0