I have the following dataframe, with original columns of String type:
using DataFrames df_0 = DataFrame(Inicio = ["10 Jan 2021 15:00 ", "10 Jan 2021 16:43 ", "10 Jan 2021 17:13 "], Q1 = ["0.50", "0.00", "0.50"])
I am able to convert the column named “Q1” to a Float64 type with (à la Query) the command:
using Query df_1 = df_0 |> @mutate(Q1 = parse(Float64, _.Q1)) |> DataFrame
It does mutate the original df_0 to a new df_1 with “Inicio” remaining of String type and “Q1” now a Float64 type, as expected (is there a better or more efficient way?).
However, if then I try the naive commands below, inspired by Standalone Query Commands · Query.jl , to convert the column named “Inicio” to a DateTime type with proper format( notice the spaces within the strings!):
using Dates dtformat = DateFormat("d u Y H:M ") df_2 = df_1 |> @mutate(Inicio = DateTime(_.Inicio, dtformat)) |> DataFrame
it generates another df_2 with the columns “Inicio” and “Q1” now both of type Any (sic!). The conversion of the column Inicio to the DateTime seems to have worked, however. In fact, when I just type:
it displays the dataframe with the types Any (in slight gray, on the REPL), right below the two named columns, whereas when I type, e.g.:
I get the wanted output tuple: (DateTime, Float64)…
What is happening here? Shouldn’t the columns of df_2 be of type DateTime and Float64, respectively?