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
import pandas as pd
dti = pd.to_datetime(
['2018-01-01 00:00:00', '2018-01-01 00:30:00', '2018-01-01 01:00:00', '2018-01-01 02:00:00']
)
dti.diff()
Issue Description
the code above returns TypeError: dtype timedelta64[ns] cannot be converted to datetime64[ns]
.
I believe this is due to the call to the index constructor (DatetimeIndex
I guess) at the end of Index.diff
.
Expected Behavior
Perhaps I'm getting confused, but I quite remembers having used the diff()
method on DatetimeIndex
instances (to assess periodicity and missing measurement in time series) a few times over the last years.
[edit : the statement "I quite remembers having used the diff()
method on DatetimeIndex
" was false memory, see comments below]
Continuing the above example, I expect DatetimeIndex.diff()
to return the same thing as:
dti[1:] - dti[:-1]
which is TimedeltaIndex(['0 days 00:30:00', '0 days 00:30:00', '0 days 01:00:00'], dtype='timedelta64[ns]', freq=None)
. Indeed this cannot be cast to DatetimeIndex.
Now, I've been looking for deprecation notices in the docs, but haven't found it, but there are so many doc pages! If it's already written somewhere, sorry for the noise.
As a workaround, looking at the code of Index.diff
, I guess I can do:
dti.to_series().diff()
which returns what I'm used to, except perhaps for the first NaT
2018-01-01 00:00:00 NaT
2018-01-01 00:30:00 0 days 00:30:00
2018-01-01 01:00:00 0 days 00:30:00
2018-01-01 02:00:00 0 days 01:00:00
dtype: timedelta64[ns]
Installed Versions
INSTALLED VERSIONS
commit : a60ad39
python : 3.11.5.final.0
python-bits : 64
OS : Linux
OS-release : 6.1.0-13-amd64
Version : #1 SMP PREEMPT_DYNAMIC Debian 6.1.55-1 (2023-09-29)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : fr_FR.UTF-8
LOCALE : fr_FR.UTF-8
pandas : 2.1.2
numpy : 1.26.0
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : None
pytest : 7.4.3
hypothesis : None
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.16.1
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.0
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.3
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : 0.21.0
tzdata : 2023.3
qtpy : None
pyqt5 : None