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Reproducible Example

import pandas as pd
from pandas import Timedelta, Timestamp
df = pd.DataFrame({"col": [1, 2]}, index=pd.to_datetime(["1969-06-01 00:00:00.000000000","1969-06-01 02:01:00.000000001"]))
rule = "7315s"
offset = pd.Timedelta("23min")
df.resample(rule, origin="end_day", offset=offset, closed="right", label="left").agg(None, col_first=("col", "first"), col_count=("col", "count"))


This outputs

    col_first   col_count
1969-06-01  1   2

Issue Description

The bucket starting at 1969-06-01 should not include the first row from the dataframe. The index is 1969-06-01 00:00:00.000000000 and closed is right which means that the value is on the opened boundary thus it does not fall into the bucket.

Moreover if the second row is removed we get

import pandas as pd
from pandas import Timedelta, Timestamp
df = pd.DataFrame({"col": [1]}, index=pd.to_datetime(["1969-06-01 00:00:00.000000000"]))
rule = "7315s"
offset = pd.Timedelta("23min")
df.resample(rule, origin="end_day", offset=offset, closed="right", label="left").agg(None, col_first=("col", "first"), col_count=("col", "count"))

Which outputs: ``` col_first col_count 1969-05-31 22:21:05 1 1


### Expected Behavior

```python
import pandas as pd
from pandas import Timedelta, Timestamp
df = pd.DataFrame({"col": [1, 2]}, index=pd.to_datetime(["1969-06-01 00:00:00.000000000","1969-06-01 02:01:00.000000001"]))
rule = "7315s"
offset = pd.Timedelta("23min")
df.resample(rule, origin="end_day", offset=offset, closed="right", label="left").agg(None, col_first=("col", "first"), col_count=("col", "count"))

The first row should not be part of the bucket. It's part of the bucket starting at 1969-05-31 22:21:05 but as this is before the first value of the dataframe that bucket is not created.

    col_first   col_count
1969-06-01  2   1

Installed Versions

INSTALLED VERSIONS ------------------ commit : c888af6d0bb674932007623c0867e1fbd4bdc2c6 python : 3.11.2 python-bits : 64 OS : Linux OS-release : 6.1.0-38-amd64 Version : #1 SMP PREEMPT_DYNAMIC Debian 6.1.147-1 (2025-08-02) machine : x86_64 processor : byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.3.1 numpy : 1.26.4 pytz : 2025.2 dateutil : 2.9.0.post0 pip : 25.2 Cython : None sphinx : None IPython : 9.3.0 adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : 4.13.4 blosc : None bottleneck : None dataframe-api-compat : None fastparquet : None fsspec : None html5lib : None hypothesis : 6.72.4 gcsfs : None jinja2 : 3.1.6 lxml.etree : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None psycopg2 : None pymysql : None pyarrow : 21.0.0 pyreadstat : None pytest : 8.4.0 python-calamine : None pyxlsb : None s3fs : None scipy : None sqlalchemy : None tables : None tabulate : 0.9.0 xarray : None xlrd : None xlsxwriter : None zstandard : None tzdata : 2025.2 qtpy : None pyqt5 : None

Comment From: Nikhil-Narayanan

take