Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
In [1]: import pandas as pd
In [2]: index = pd.Series([pd.Timedelta(seconds=120 + i * 30) for i in range(10)])
In [3]: series = pd.Series(range(10), index=index)
In [4]: series
Out[4]:
0 days 00:02:00 0
0 days 00:02:30 1
0 days 00:03:00 2
0 days 00:03:30 3
0 days 00:04:00 4
0 days 00:04:30 5
0 days 00:05:00 6
0 days 00:05:30 7
0 days 00:06:00 8
0 days 00:06:30 9
dtype: int64
In [5]: series.resample('T', closed='left', label='left').sum()
Out[5]:
0 days 00:02:00 1
0 days 00:03:00 5
0 days 00:04:00 9
0 days 00:05:00 13
0 days 00:06:00 17
Freq: T, dtype: int64
In [6]: series.resample('T', closed='right', label='right').sum() # WRONG!
Out[6]:
0 days 00:02:00 1
0 days 00:03:00 5
0 days 00:04:00 9
0 days 00:05:00 13
0 days 00:06:00 17
Freq: T, dtype: int64Issue Description
closed=right argument takes no effect, the output is same as closed=left.
Expected Behavior
The same computation on a DatetimeIndex, which is the expected behavior:
In [7]: index = pd.Series([pd.Timedelta(seconds=120 + i * 30) for i in range(10)])
In [8]: index = index + pd.to_datetime('2000-01-01')
In [9]: series = pd.Series(range(10), index=index)
In [10]: series
Out[10]:
2000-01-01 00:02:00 0
2000-01-01 00:02:30 1
2000-01-01 00:03:00 2
2000-01-01 00:03:30 3
2000-01-01 00:04:00 4
2000-01-01 00:04:30 5
2000-01-01 00:05:00 6
2000-01-01 00:05:30 7
2000-01-01 00:06:00 8
2000-01-01 00:06:30 9
dtype: int64
In [11]: series.resample('T', closed='left', label='left').sum()
Out[11]:
2000-01-01 00:02:00 1
2000-01-01 00:03:00 5
2000-01-01 00:04:00 9
2000-01-01 00:05:00 13
2000-01-01 00:06:00 17
Freq: T, dtype: int64
In [12]: series.resample('T', closed='right', label='right').sum() # RIGHT
Out[12]:
2000-01-01 00:02:00 0
2000-01-01 00:03:00 3
2000-01-01 00:04:00 7
2000-01-01 00:05:00 11
2000-01-01 00:06:00 15
2000-01-01 00:07:00 9
Freq: T, dtype: int64Installed Versions
INSTALLED VERSIONS
commit : 66e3805
python : 3.8.8.final.0
python-bits : 64
OS : Linux
OS-release : 4.9.130-0409130-generic
Version : #201809291131 SMP Sat Sep 29 11:33:40 UTC 2018
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.3.5
numpy : 1.19.5
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : None
pytest : 6.2.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : 1.0.2
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.22.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.9.0
fastparquet : 0.7.1
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 6.0.1
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : 1.4.23
tables : None
tabulate : 0.8.9
xarray : 0.19.0
xlrd : 2.0.1
xlwt : None
numba : 0.53.1