DateTime columns #2861Description
The following exemplifies a DataFrame with datetime data:
datetime_table.csv
Time, Value
2014-01-01T00:00:00.0,0.485207
2014-01-01T00:00:01.0,0.485207
2014-01-01T00:00:02.0,0.485207
2014-01-01T00:00:03.0,0.485207
2014-01-01T00:00:04.0,0.485207
2014-01-01T00:00:05.0,0.485207
2014-01-01T00:00:06.0,0.485207
2014-01-01T00:00:07.0,0.485207
2014-01-01T00:00:08.0,0.485207
2014-01-01T00:00:09.0,0.485207
2014-01-01T00:00:10.0,0.485207
2014-01-01T00:00:11.0,0.485207
2014-01-01T00:00:12.0,0.485207
2014-01-01T00:00:13.0,0.485207
2014-01-01T00:00:14.0,0.485207
using Dates
using DataFrames, CSV
df = CSV.File("datetime_table.csv") |> DataFrameThe DateTime entries are displayed in a redundant form
julia> df
15×2 typename(DataFrame)
│ Row │ Time │ Value │
│ │ DateTime │ Float64 │
├─────┼─────────────────────────────────┼──────────┤
│ 1 │ DateTime("2014-01-01T00:00:00") │ 0.485207 │
│ 2 │ DateTime("2014-01-01T00:00:01") │ 0.485207 │
│ 3 │ DateTime("2014-01-01T00:00:02") │ 0.485207 │
│ 4 │ DateTime("2014-01-01T00:00:03") │ 0.485207 │
│ 5 │ DateTime("2014-01-01T00:00:04") │ 0.485207 │
│ 6 │ DateTime("2014-01-01T00:00:05") │ 0.485207 │
│ 7 │ DateTime("2014-01-01T00:00:06") │ 0.485207 │
│ 8 │ DateTime("2014-01-01T00:00:07") │ 0.485207 │
│ 9 │ DateTime("2014-01-01T00:00:08") │ 0.485207 │
│ 10 │ DateTime("2014-01-01T00:00:09") │ 0.485207 │
│ 11 │ DateTime("2014-01-01T00:00:10") │ 0.485207 │
│ 12 │ DateTime("2014-01-01T00:00:11") │ 0.485207 │
│ 13 │ DateTime("2014-01-01T00:00:12") │ 0.485207 │
│ 14 │ DateTime("2014-01-01T00:00:13") │ 0.485207 │
│ 15 │ DateTime("2014-01-01T00:00:14") │ 0.485207 │
Instead, the normal show method for DateTime is less verbose, simply showing the timestamp in ISO format.
julia> DateTime("2014-01-01T00:00:00")
2014-01-01T00:00:00