DataFrames to Database tables - database

Question

geniouses. I am a newbie in Julia, but have an ambitious.
I am trying to a following stream so far, of course it's an automatic process.
read data from csv file to DataFrames
Checking the data then cerate DB tables due to DataFrames data type
Insert data from DataFrames to the created table ( eg. SQLite )
I am sticking at No.2 now, because, for example the column's data type 'Vector{String15}'.
I am struggling how can I reflect the datatype to the query of creating table.
I mean I could not find any solutions below (a) (b).
fname = string( #__DIR__,"/","testdata/test.csv")
df = CSV.read( fname, DataFrame )
last = ncol(df)
for i = 1:last
col[i] = typeof(df[!,i]) # ex. Vector{String15}
if String == col[i] # (a) does not work
# create table sql
# expect
query = 'create table testtable( col1 varchar(15),....'
elseif Int == col[i] # (b) does not work
# create table sql
# expect
query = 'create table testtable( col1 int,....'
end
・
　　　　　・
end
I am wonderring,
I really have to get the type of table column from 'Vector{String15}' anyhow?
Does DataFrames has an utility method to do it?
Should combine with other module to do it?
I am expecting smart tips by you, thanks any advances.

Answer 1

Here is how you can do it both ways:
julia> using DataFrames
julia> using CSV
julia> df = CSV.read("test.csv", DataFrame)
3×3 DataFrame
Row │ a b c
│ String15 Int64 Float64
─────┼─────────────────────────────
1 │ a1234567890 1 1.5
2 │ b1234567890 11 11.5
3 │ b1234567890 111 111.5
julia> using SQLite
julia> db = SQLite.DB("test.db")
SQLite.DB("test.db")
julia> SQLite.load!(df, db, "df")
"df"
julia> SQLite.columns(db, "df")
(cid = [0, 1, 2], name = ["a", " b", " c"], type = ["TEXT", "INT", "REAL"], notnull = [1, 1, 1], dflt_value = [missing, missing, missing], pk = [0, 0, 0])
julia> query = DBInterface.execute(db, "SELECT * FROM df")
SQLite.Query(SQLite.Stmt(SQLite.DB("test.db"), 4), Base.RefValue{Int32}(100), [:a, Symbol(" b"), Symbol(" c")], Type[Union{Missing, String}, Union{Missing, Int64}, UnionMissing, Float64}], Dict(:a => 1, Symbol(" c") => 3, Symbol(" b") => 2), Base.RefValue{Int64}(0))
julia> DataFrame(query)
3×3 DataFrame
Row │ a b c
│ String Int64 Float64
─────┼─────────────────────────────
1 │ a1234567890 1 1.5
2 │ b1234567890 11 11.5
3 │ b1234567890 111 111.5
If you would need more explanations this is covered in chapter 8 of Julia for Data Analysis. This chapter should be available on MEAP in 1-2 weeks (and the source code is already available at https://github.com/bkamins/JuliaForDataAnalysis)