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Drop dump from the reshaping docs
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@cjprybol
cjprybol committed Oct 17, 2017
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Expand Up @@ -274,146 +274,6 @@ This is provides a view of the original columns stacked together.
Id columns -- `RepeatedVector`
This repeats the original columns N times where N is the number of columns stacked.

For more details on the storage representation, see:

```jldoctest reshape
julia> dump(stackdf(iris))
DataFrames.DataFrame 600 observations of 4 variables
variable: DataFrames.RepeatedVector{Symbol}
parent: Array{Symbol}((4,))
1: Symbol SepalLength
2: Symbol SepalWidth
3: Symbol PetalLength
4: Symbol PetalWidth
inner: Int64 150
outer: Int64 1 value: DataFrames.StackedVector
components: Array{Any}((4,))
1: Array{Float64}((150,)) [5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9 … 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9]
2: Array{Float64}((150,)) [3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1 … 3.1, 3.1, 2.7, 3.2, 3.3, 3.0, 2.5, 3.0, 3.4, 3.0]
3: Array{Float64}((150,)) [1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5 … 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5.0, 5.2, 5.4, 5.1]
4: Array{Float64}((150,)) [0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1 … 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2.0, 2.3, 1.8] Species: DataFrames.RepeatedVector{CategoricalArrays.CategoricalValue{String,UInt32}}
parent: CategoricalArrays.CategoricalArray{String,1,UInt32,String,Union{}}
refs: Array{UInt32}((150,)) UInt32[0x00000001, 0x00000001, 0x00000001, 0x00000001, 0x00000001, 0x00000001, 0x00000001, 0x00000001, 0x00000001, 0x00000001 … 0x00000003, 0x00000003, 0x00000003, 0x00000003, 0x00000003, 0x00000003, 0x00000003, 0x00000003, 0x00000003, 0x00000003]
pool: CategoricalArrays.CategoricalPool{String,UInt32,CategoricalArrays.CategoricalValue{String,UInt32}}
index: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
invindex: Dict{String,UInt32}
slots: Array{UInt8}((16,)) UInt8[0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00]
keys: Array{String}((16,))
1: #undef
2: #undef
3: #undef
4: #undef
5: #undef
...
12: #undef
13: String "setosa"
14: String "versicolor"
15: #undef
16: #undef
vals: Array{UInt32}((16,)) UInt32[0x04e581f0, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000003, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000001, 0x00000002, 0x00000000, 0x00000000]
ndel: Int64 0
count: Int64 3
age: UInt64 3
idxfloor: Int64 7
maxprobe: Int64 1
order: Array{UInt32}((3,)) UInt32[0x00000001, 0x00000002, 0x00000003]
levels: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
valindex: Array{CategoricalArrays.CategoricalValue{String,UInt32}}((3,))
1: CategoricalArrays.CategoricalValue{String,UInt32}
level: UInt32 1
pool: CategoricalArrays.CategoricalPool{String,UInt32,CategoricalArrays.CategoricalValue{String,UInt32}}
index: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
invindex: Dict{String,UInt32}
slots: Array{UInt8}((16,)) UInt8[0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00]
keys: Array{String}((16,))
vals: Array{UInt32}((16,)) UInt32[0x04e581f0, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000003, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000001, 0x00000002, 0x00000000, 0x00000000]
ndel: Int64 0
count: Int64 3
age: UInt64 3
idxfloor: Int64 7
maxprobe: Int64 1
order: Array{UInt32}((3,)) UInt32[0x00000001, 0x00000002, 0x00000003]
levels: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
valindex: Array{CategoricalArrays.CategoricalValue{String,UInt32}}((3,))
1: CategoricalArrays.CategoricalValue{String,UInt32}
2: CategoricalArrays.CategoricalValue{String,UInt32}
3: CategoricalArrays.CategoricalValue{String,UInt32}
ordered: Bool false
2: CategoricalArrays.CategoricalValue{String,UInt32}
level: UInt32 2
pool: CategoricalArrays.CategoricalPool{String,UInt32,CategoricalArrays.CategoricalValue{String,UInt32}}
index: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
invindex: Dict{String,UInt32}
slots: Array{UInt8}((16,)) UInt8[0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00]
keys: Array{String}((16,))
vals: Array{UInt32}((16,)) UInt32[0x04e581f0, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000003, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000001, 0x00000002, 0x00000000, 0x00000000]
ndel: Int64 0
count: Int64 3
age: UInt64 3
idxfloor: Int64 7
maxprobe: Int64 1
order: Array{UInt32}((3,)) UInt32[0x00000001, 0x00000002, 0x00000003]
levels: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
valindex: Array{CategoricalArrays.CategoricalValue{String,UInt32}}((3,))
1: CategoricalArrays.CategoricalValue{String,UInt32}
2: CategoricalArrays.CategoricalValue{String,UInt32}
3: CategoricalArrays.CategoricalValue{String,UInt32}
ordered: Bool false
3: CategoricalArrays.CategoricalValue{String,UInt32}
level: UInt32 3
pool: CategoricalArrays.CategoricalPool{String,UInt32,CategoricalArrays.CategoricalValue{String,UInt32}}
index: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
invindex: Dict{String,UInt32}
slots: Array{UInt8}((16,)) UInt8[0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00]
keys: Array{String}((16,))
vals: Array{UInt32}((16,)) UInt32[0x04e581f0, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000003, 0x00000001, 0x00000000, 0x00000000, 0x04e5c018, 0x00000001, 0x00000001, 0x00000002, 0x00000000, 0x00000000]
ndel: Int64 0
count: Int64 3
age: UInt64 3
idxfloor: Int64 7
maxprobe: Int64 1
order: Array{UInt32}((3,)) UInt32[0x00000001, 0x00000002, 0x00000003]
levels: Array{String}((3,))
1: String "setosa"
2: String "versicolor"
3: String "virginica"
valindex: Array{CategoricalArrays.CategoricalValue{String,UInt32}}((3,))
1: CategoricalArrays.CategoricalValue{String,UInt32}
2: CategoricalArrays.CategoricalValue{String,UInt32}
3: CategoricalArrays.CategoricalValue{String,UInt32}
ordered: Bool false
ordered: Bool false
inner: Int64 1
outer: Int64 4 id: DataFrames.RepeatedVector{Int64}
parent: UnitRange{Int64}
start: Int64 1
stop: Int64 150
inner: Int64 1
outer: Int64 4
```

None of these reshaping functions perform any aggregation. To do aggregation, use the split-apply-combine functions in combination with reshaping. Here is an example:

```jldoctest reshape
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