Switch to OrderedDict for import (#73)

Co-authored-by: Páll Haraldsson <[email protected]>

Co-authored-by: Jonathan Malmaud <[email protected]>

Project.toml

@@ -8,6 +8,7 @@ DataValues = "e7dc6d0d-1eca-5fa6-8ad6-5aecde8b7ea5"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 IteratorInterfaceExtensions = "82899510-4779-5014-852e-03e436cf321d"
 Lazy = "50d2b5c4-7a5e-59d5-8109-a42b560f39c0"
+OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
@@ -25,3 +26,4 @@ TableTraits = "^0.4, ^1"
 TableTraitsUtils = "^0.3, ^0.4, ^1"
 Tables = "1"
 julia = "0.7, 1"
+OrderedCollections = "1"

src/tabletraits.jl

@@ -1,5 +1,6 @@
 using IteratorInterfaceExtensions
 using TableTraitsUtils
+using OrderedCollections: OrderedDict
 import DataValues
 
 IteratorInterfaceExtensions.isiterable(x::DataFrame) = true
@@ -28,7 +29,7 @@ function _construct_pandas_from_iterabletable(source)
     y = create_columns_from_iterabletable(source, errorhandling=:returnvalue)
     y===nothing && return nothing
     columns, column_names = y[1], y[2]
-    cols = Dict{Symbol,Any}(i[1]=>i[2] for i in zip(column_names, columns))
+    cols = OrderedDict{Symbol,Any}(i[1]=>i[2] for i in zip(column_names, columns))
 
     for (k,v) in pairs(cols)
         if eltype(v)<:DataValues.DataValue

test/runtests.jl

@@ -50,7 +50,7 @@ roll = rolling(Series([1,2,3,4,5]), 3)
 # Issue #71
 julia_df = DataFrames.DataFrame(x=[1,2], y=[missing, missing])
 py_df = Pandas.DataFrame(julia_df)
-expected_df = Pandas.DataFrame(:x=>[1,2], :y=>[NaN, NaN])
+expected_df = Pandas.DataFrame(:x=>[1,2], :y=>[NaN, NaN])[["x", "y"]]
 @test Pandas.equals(py_df, expected_df)
 
 # Issue #68
@@ -68,3 +68,8 @@ py_df = py"get_df"()|>Pandas.DataFrame
 julia_df = DataFrames.DataFrame(py_df)
 
 @test julia_df.a == [DateTime(2021, 1, 15), DateTime(2021, 1, 15), DateTime(2020, 4, 6)]
+
+# Issue #72
+julia_df= DataFrames.DataFrame(C = 1:4, A = 5:8, B = 9:12)
+py_df = Pandas.DataFrame(julia_df)
+@test all(Pandas.columns(py_df) .== ["C","A","B"])