Merge pull request JuliaData#213 from HarlanH/getset

Switch to get/set methods

demo/examples.jl

@@ -81,7 +81,7 @@ dv = DataArray(1:3)
 #
 # To order to provide a very concise constructor, we've hacked in
 # a very cute constructor for DataVector's using a trick involving
-# their ref() method.
+# their getindex() method.
 #
 
 dv = DataVector[1, 2, NA, 4]
@@ -425,7 +425,7 @@ df .== df
 #
 # abs, sign, acos, acosh, asin, asinh, atan, atan2, atanh, sin, sinh
 # cos, cosh, tan, tanh, ceil, floor, round, trunc, signif, exp, log
-# log10, log1p, log2, logb, sqrt
+# log10, log1p, log2, exponent, sqrt
 #
 ##############################################################################
 

doc/sections/03_design_details.md

@@ -139,7 +139,7 @@ In contrast to these normal-looking constructors, when some of the values in the
 
 	dv = DataVector[1, 2, NA, 4]
 
-_Technical Note: This special type of constructor is defined by overloading the `ref()` function to apply to values of type `DataVector`.
+_Technical Note: This special type of constructor is defined by overloading the `getindex()` function to apply to values of type `DataVector`.
 
 # DataVector's with Special Types
 
@@ -444,7 +444,7 @@ The standard comparison operators work on `DataVector`'s:
 * `log10`
 * `log1p`
 * `log2`
-* `logb`
+* `exponent`
 * `sqrt`
 
 Standard functions that apply to scalar values of type `Number` return `NA` when applied to `NA`:

doc/sections/04_specification.md

@@ -176,6 +176,6 @@ DataFrame's add two new indexer types:
 
 These can only occur as (a) the only indexer or (b) in the second slot of a paired indexer
 
-Anything that can be ref()'d can also be assign()'d
+Anything that can be getindex()'d can also be setindex!()'d
 
 Where do we allow Expr indexing?

doc/sections/05_function_reference_guide.md

@@ -109,14 +109,14 @@ are selected. Indexing along rows works like Matrix indexing. Indexing
 along columns works like Matrix indexing with the addition of column
 name access. 
 
-#### `ref(df::DataFrame, ind)`  or `df[ind]`
+#### `getindex(df::DataFrame, ind)`  or `df[ind]`
 
 Returns a subset of the columns of `df` as specified by `ind`, which
 may be an `Int`, a `Range`, a `Vector{Int}`, `ByteString`, or
 `Vector{ByteString}`. Columns are referenced, not copied. For a
 single-element `ind`, the column by itself is returned.
 
-#### `ref(df::DataFrame, irow, icol)`  or `df[irow,icol]`
+#### `getindex(df::DataFrame, irow, icol)`  or `df[irow,icol]`
 
 Returns a subset of `df` as specified by `irow` and `icol`. `irow` may
 be an `Int`, a `Range`, or a `Vector{Int}`. `icol` may be an `Int`, a
@@ -138,7 +138,7 @@ See the Indexing section for these operations on column indexes.
 
 The column names as an `Array{ByteString}`
 
-#### `assign(df::DataFrame, newcol, colname)` or `df[colname] = newcol`
+#### `setindex!(df::DataFrame, newcol, colname)` or `df[colname] = newcol`
 
 Replace or add a new column with name `colname` and contents `newcol`.
 Arrays are converted to DataVector's. Values are recycled to match the
@@ -224,8 +224,8 @@ Return a SubDataFrame with references to rows and columns of `df`.
 
 Return a SubDataFrame with references to rows and columns of `df`.
 
-#### `ref(sd::SubDataFrame, r, c)` or `sd[r,c]`
-#### `ref(sd::SubDataFrame, c)` or `sd[c]`
+#### `getindex(sd::SubDataFrame, r, c)` or `sd[r,c]`
+#### `getindex(sd::SubDataFrame, c)` or `sd[c]`
 
 Referencing should work the same as DataFrames.
 
@@ -241,7 +241,7 @@ columns with one or more names given in `cols`.
 
 Methods to iterate over GroupedDataFrame groupings.
 
-#### `ref(gd::GroupedDataFrame, idx)` or `gd[idx]`
+#### `getindex(gd::GroupedDataFrame, idx)` or `gd[idx]`
 
 Reference a particular grouping. Referencing returns a SubDataFrame.
 
@@ -344,7 +344,7 @@ Set names `nm` in `x`.
 
 Replace names `from` with `to` in `x`.
 
-#### `ref(x::Index, idx)` or `x[idx]`
+#### `getindex(x::Index, idx)` or `x[idx]`
 
 This does the mapping from name(s) to Indices (positions). `idx` may
 be ByteString, Vector{ByteString}, Int, Vector{Int}, Range{Int},

spec/FunctionReference.md

@@ -109,14 +109,14 @@ are selected. Indexing along rows works like Matrix indexing. Indexing
 along columns works like Matrix indexing with the addition of column
 name access. 
 
-#### `ref(df::DataFrame, ind)`  or `df[ind]`
+#### `getindex(df::DataFrame, ind)`  or `df[ind]`
 
 Returns a subset of the columns of `df` as specified by `ind`, which
 may be an `Int`, a `Range`, a `Vector{Int}`, `ByteString`, or
 `Vector{ByteString}`. Columns are referenced, not copied. For a
 single-element `ind`, the column by itself is returned.
 
-#### `ref(df::DataFrame, irow, icol)`  or `df[irow,icol]`
+#### `getindex(df::DataFrame, irow, icol)`  or `df[irow,icol]`
 
 Returns a subset of `df` as specified by `irow` and `icol`. `irow` may
 be an `Int`, a `Range`, or a `Vector{Int}`. `icol` may be an `Int`, a
@@ -138,7 +138,7 @@ See the Indexing section for these operations on column indexes.
 
 The column names as an `Array{ByteString}`
 
-#### `assign(df::DataFrame, newcol, colname)` or `df[colname] = newcol`
+#### `setindex!(df::DataFrame, newcol, colname)` or `df[colname] = newcol`
 
 Replace or add a new column with name `colname` and contents `newcol`.
 Arrays are converted to DataVector's. Values are recycled to match the
@@ -224,8 +224,8 @@ Return a SubDataFrame with references to rows and columns of `df`.
 
 Return a SubDataFrame with references to rows and columns of `df`.
 
-#### `ref(sd::SubDataFrame, r, c)` or `sd[r,c]`
-#### `ref(sd::SubDataFrame, c)` or `sd[c]`
+#### `getindex(sd::SubDataFrame, r, c)` or `sd[r,c]`
+#### `getindex(sd::SubDataFrame, c)` or `sd[c]`
 
 Referencing should work the same as DataFrames.
 
@@ -241,7 +241,7 @@ columns with one or more names given in `cols`.
 
 Methods to iterate over GroupedDataFrame groupings.
 
-#### `ref(gd::GroupedDataFrame, idx)` or `gd[idx]`
+#### `getindex(gd::GroupedDataFrame, idx)` or `gd[idx]`
 
 Reference a particular grouping. Referencing returns a SubDataFrame.
 
@@ -344,7 +344,7 @@ Set names `nm` in `x`.
 
 Replace names `from` with `to` in `x`.
 
-#### `ref(x::Index, idx)` or `x[idx]`
+#### `getindex(x::Index, idx)` or `x[idx]`
 
 This does the mapping from name(s) to Indices (positions). `idx` may
 be ByteString, Vector{ByteString}, Int, Vector{Int}, Range{Int},

src/DataFrames.jl

@@ -1,5 +1,11 @@
 require("Options")
 
+# Note that the two calls to using Stats in this file are
+# strictly required: one pulls the names into DataFrames
+# for easy access within the module, whereas the other call
+# pushes those names into Main.
+using Stats
+
 module DataFrames
 
 ##############################################################################

src/RDA.jl

@@ -180,7 +180,7 @@ function namedobjects(io::IO, fl::Uint32, A::Bool, symtab::Array{RSymbol,1})
     while uint8(fl) != 0xfe
         ## need to call RSymbol here b/c of symbol reference table
         nm = RSymbol(io, readuint32(io, A), A, symtab).displayname
-        assign(res, readitem(io, A, symtab), nm)
+        setindex!(res, readitem(io, A, symtab), nm)
         fl = readuint32(io, A)
     end
     res