I am trying to populate a dash table and think the issue is that I don’t know how to traverse a nested dict properly. I have a Dict
data_flow =
Dict{String, Any}("AMZN" => Dict{String, Any}("hv10" => "45.99", "price" => "122.16", "iv_%" => "83.4", "hv20" => "52.14", "iv" => "40.64", "hv5" => "41.21", "prc_%" => "7.51"), "VZ" => Dict{String, Any}("hv10" => "13.87", "price" => "51.27", "iv_%" => "65.61", "hv20" => "12.71", "iv" => "17.62", "hv5" => "10.32", "prc_%" => "19.37"), "C" => Dict{String, Any}("hv10" => "21.26", "price" => "51.78", "iv_%" => "72.73", "hv20" => "42.75", "iv" => "31.75", "hv5" => "20.79", "prc_%" => "11.86"), "IEX" => Dict{String, Any}("hv10" => "19.16", "price" => "195.55", "iv_%" => "70.36", "hv20" => "24.97", "iv" => "27.62", "hv5" => "18.77"))
so to get my column headings for dash I need to isolate out
HV_10 PRICE IV_% hv20 iv hv5 prc_%
but I can’t figure out how to do it.
I can get the rows
keys(data_flow)
julia> keys(data_flow)
KeySet for a Dict{String, Any} with 4 entries. Keys:
"AMZN"
"VZ"
"C"
"IEX"
and the values for the table
values(data_flow)
ValueIterator for a Dict{String, Any} with 4 entries. Values:
Dict{String, Any}("hv10" => "45.99", "price" => "122.16", "iv_%" => "83.4", "hv20" => "52.14", "iv" => "40.64", "hv5" => "41.21", "prc_%" => "7.51")
Dict{String, Any}("hv10" => "13.87", "price" => "51.27", "iv_%" => "65.61", "hv20" => "12.71", "iv" => "17.62", "hv5" => "10.32", "prc_%" => "19.37")
Dict{String, Any}("hv10" => "21.26", "price" => "51.78", "iv_%" => "72.73", "hv20" => "42.75", "iv" => "31.75", "hv5" => "20.79", "prc_%" => "11.86")
Dict{String, Any}("hv10" => "19.16", "price" => "195.55", "iv_%" => "70.36", "hv20" => "24.97", "iv" => "27.62", "hv5" => "18.77")
can someone help me isolate out the column headings in this Dict of dicts.
I’m trying to get this into dash
HV_10 PRICE IV_% hv20 iv hv5 prc_%
AMZN 45.99 122.16 83.4 52.14 40.64 41.21 7.51
VZ 13.87 51.27 65.61 12.71 17.62 10.32 19.37
C 21.26 51.78 72.73 42.75 31.75 20.79 11.86
IEX 19.16 195.55 70.36 24.97 27.62 18.77
thank you