BUG: DataFrame.from_records() ignores columns with iterator and nrows=0

[jlumpe]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

>>> import pandas as pd
>>> rows = []
>>> pd.DataFrame.from_records(iter(rows), columns=['a', 'b'], nrows=0)
Empty DataFrame
Columns: []
Index: []

Issue Description

Passing an empty iterator to DataFrame.from_records() along with nrows=0 results in a DataFrame with no columns, even if the columns argument is provided.

Oddly, the correct result is obtained with an empty iterator and nrows > 0. However, columns are still ignored if the iterator is non-empty and nrows=0.

Expected Behavior

Should return a DataFrame with 0 rows and the columns provided.

Installed Versions

INSTALLED VERSIONS
------------------
commit                : 0691c5cf90477d3503834d983f69350f250a6ff7
python                : 3.12.9
python-bits           : 64
OS                    : Linux
OS-release            : 5.15.167.4-microsoft-standard-WSL2
Version               : #1 SMP Tue Nov 5 00:21:55 UTC 2024
machine               : x86_64
processor             : x86_64
byteorder             : little
LC_ALL                : None
LANG                  : C.UTF-8
LOCALE                : C.UTF-8

pandas                : 2.2.3
numpy                 : 2.2.3
pytz                  : 2024.1
dateutil              : 2.9.0.post0
pip                   : 25.0.1
Cython                : None
sphinx                : None
IPython               : None
adbc-driver-postgresql: None
adbc-driver-sqlite    : None
bs4                   : None
blosc                 : None
bottleneck            : None
dataframe-api-compat  : None
fastparquet           : None
fsspec                : None
html5lib              : None
hypothesis            : None
gcsfs                 : None
jinja2                : None
lxml.etree            : None
matplotlib            : None
numba                 : None
numexpr               : None
odfpy                 : None
openpyxl              : None
pandas_gbq            : None
psycopg2              : None
pymysql               : None
pyarrow               : None
pyreadstat            : None
pytest                : None
python-calamine       : None
pyxlsb                : None
s3fs                  : None
scipy                 : None
sqlalchemy            : None
tables                : None
tabulate              : None
xarray                : None
xlrd                  : None
xlsxwriter            : None
zstandard             : None
tzdata                : 2025.1
qtpy                  : None
pyqt5                 : None

[kpvenkat47]

Hi, I’ve already resolved this issue and submitted a pull request #61143 . I’m currently awaiting feedback from the pandas community. Thank you!