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time
2021-01-01 00:00:00 0.0 7.0
2021-01-01 00:15:00 NaN NaN
2021-01-01 00:30:00 NaN NaN
2021-01-01 00:45:00 NaN NaN
2021-01-01 01:00:00 4.0 11.0
2021-01-01 01:15:00 5.0 11.5
2021-01-01 01:30:00 6.0 12.0
Installed Versions
INSTALLED VERSIONS
commit : 2e218d1
python : 3.10.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.0-38-generic
Version : #39~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 17 21:16:15 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
Allright, it is indeed not a bug. I now understand how this is implemented this way (not sure when this is usefull), the documentation could be more clear.. I would expect having a limit in a interpolation to skip gaps bigger than the limit.
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
Issue Description
This does interpolate the gap bigger than 1 nan?
Expected Behavior
time
2021-01-01 00:00:00 0.0 7.0
2021-01-01 00:15:00 NaN NaN
2021-01-01 00:30:00 NaN NaN
2021-01-01 00:45:00 NaN NaN
2021-01-01 01:00:00 4.0 11.0
2021-01-01 01:15:00 5.0 11.5
2021-01-01 01:30:00 6.0 12.0
Installed Versions
INSTALLED VERSIONS
commit : 2e218d1
python : 3.10.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.0-38-generic
Version : #39~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 17 21:16:15 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.5.3
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 65.6.3
pip : 23.0.1
Cython : None
pytest : 7.2.1
hypothesis : None
sphinx : 6.1.3
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.7.0
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.1
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : 2022.11.0
xlrd : None
xlwt : None
zstandard : None
tzdata : None
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