I have a dataframe with some "NaT" values in a datetime column. What does that mean?

   project   status  completed
0  windows     done 2025-08-20
1    doors     done 2025-08-21
2     hvac  delayed        NaT

I checked the docs page pandas.NaT, but it just says "alias of NaT", which doesn't seem to make sense.

I found plenty of SO questions, but I didn't see one that actually explains what NaT is. E.g. How do I check if a specific item in pandas series is NaT

_{This is meant to be a canonical question with a self-answer. I'm not genuinely asking for myself, just want to put this out there since the docs page is lacking, and someone asked this question in earnest here: "What are NaT? All of the time values should be datetime objects."}

NaT means "Not a Time". It's the equivalent of NaN "Not a Number". You'll see it in datetime and timedelta columns for missing values.

The docs page is supposed to have a fuller description, but there seems to be a bug with Pandas 2.2+. For now, see the Missing values page:

NaT is the missing value for timedelta and datetime data (see below):

NaT : (N)ot-(A)-(T)ime, the time equivalent of NaN.

Or the user guide:

Working with missing data

Values considered “missing”

pandas uses different sentinel values to represent a missing (also referred to as NA) depending on the data type. [...]

NaT for NumPy np.datetime64, np.timedelta64, and PeriodDtype.

Or the help text:

In [5]: ?pd.NaT
Type:        NaTType
String form: NaT
File:        .../pandas/_libs/tslibs/nattype.cpython-311-x86_64-linux-gnu.so
Docstring:  
(N)ot-(A)-(T)ime, the time equivalent of NaN.

Examples
--------
>>> pd.DataFrame([pd.Timestamp("2023"), np.nan], columns=["col_1"])
        col_1
0  2023-01-01
1         NaT