I think Explorer only supports NaiveDatetime. I made it work with this code in Livebook:

tmp_dir = System.tmp_dir!()
test_csv_path = Path.join(tmp_dir, "test.csv")

File.write!(test_csv_path, 
"""
datetime_ns
1738573413286629810
""")

df = Explorer.DataFrame.from_csv!(test_csv_path, [
  infer_schema_length: 0,
  columns: [
    "datetime_ns"
  ],
  dtypes: [
    datetime_ns: {:u, 64}
  ]
])

dt = df["datetime_ns"]
  |> Explorer.Series.transform(fn dns -> DateTime.from_unix!(dns, :nanosecond) end)


Explorer.DataFrame.put(df, "datetime_ns", dt)

@evadne Glad you figured it out

FWIW I couldn’t get Polars to (which Explorer uses under the hood) to parse the timestamp directly either. So your cast approach is what I’d use too. I will throw a few more pointers out there.

DF.mutate/2 is nice because you don’t need to keep around the original column:

require Explorer.DataFrame, as: DF

path = "./ingestion_test.csv"

path
|> DF.from_csv!(dtypes: %{datetime_ns: :u64})
|> DF.mutate(datetime_ns: cast(datetime_ns, {:naive_datetime, :nanosecond}))
# #Explorer.DataFrame<
#   Polars[1 x 1]
#   datetime_ns naive_datetime[ns] [2025-02-03 09:03:33.286629]
# >

There is also the :lazy option. It will defer the computation so that you never create the intermediate column in the first place:

path
|> DF.from_csv!(dtypes: %{datetime_ns: :u64}, lazy: true)
|> DF.mutate(datetime_ns: cast(datetime_ns, {:naive_datetime, :nanosecond}))
|> DF.collect()
# #Explorer.DataFrame<
#   Polars[1 x 1]
#   datetime_ns naive_datetime[ns] [2025-02-03 09:03:33.286629]
# >

That option is only needed if you need to go real fast for some reason.

Also, we do have support for non-naive datetimes. But that doesn’t seem super relevant for this use case.