fix typos in docs and comments (#3143)

Author: musvaage

src/abstractdataframe/io.jl

@@ -99,7 +99,7 @@ Render a data frame to an I/O stream in MIME type `mime`.
 - `df::AbstractDataFrame`: The data frame to print.
 
 Additionally selected MIME types support passing the following keyword arguments:
-- MIME type `"text/plain"` accepts all listed keyword arguments and therir behavior
+- MIME type `"text/plain"` accepts all listed keyword arguments and their behavior
   is identical as for `show(::IO, ::AbstractDataFrame)`
 - MIME type `"text/html"` accepts `summary` keyword argument which
   allows to choose whether to print a brief string summary of the data frame.

src/abstractdataframe/selection.jl

@@ -803,8 +803,8 @@ function select_transform!((nc,)::Ref{Any}, df::AbstractDataFrame, newdf::DataFr
     if newname isa DataType
         newname === AsTable || throw(ArgumentError("Only DataType supported as target is AsTable"))
     end
-    # It is allowed to request a tranformation operation into a newname column
-    # only once. This is ensured by the logic related to transformed_cols dictionaly
+    # It is allowed to request a transformation operation into a newname column
+    # only once. This is ensured by the logic related to transformed_cols set
     # in _manipulate, therefore in select_transform! such a duplicate should not happen
     res = _transformation_helper(df, col_idx, Ref{Any}(fun))
 
@@ -1731,7 +1731,7 @@ function _manipulate(df::AbstractDataFrame, normalized_cs::Vector{Any}, copycols
                 newname = _names(df)[i]
                 # as nc is a multiple column selection without transformations
                 # we allow duplicate column names with selections applied earlier
-                # and ignore them for convinience, to allow for e.g. select(df, :x1, :)
+                # and ignore them for convenience, to allow for e.g. select(df, :x1, :)
                 if !hasproperty(newdf, newname)
                     # allow shortening to 0 rows
                     if allow_resizing_newdf[] && nrow(newdf) == 1

src/groupeddataframe/splitapplycombine.jl

@@ -314,7 +314,7 @@ function _combine_process_proprow((cs_i,)::Ref{Any},
     end
 end
 
-# move one column without transorming it
+# move one column without transforming it
 function _combine_process_noop(cs_i::Pair{<:Union{Int, AbstractVector{Int}}, Pair{typeof(identity), Symbol}},
                                optional_i::Bool,
                                parentdf::AbstractDataFrame,

src/groupeddataframe/utils.jl

@@ -197,7 +197,7 @@ function row_group_slots(cols::Tuple{Vararg{AbstractVector}},
     row_group_slots(cols, refpools, refarrays, hash, groups, skipmissing, sort === true)
 end
 
-# Generic fallback method based on open adressing hash table
+# Generic fallback method based on open addressing hash table
 function row_group_slots(cols::Tuple{Vararg{AbstractVector}},
                          refpools::Any,  # Ignored
                          refarrays::Any, # Ignored

src/other/utils.jl

@@ -379,11 +379,11 @@ function _findall(B::BitVector)::Union{UnitRange{Int}, Vector{Int}}
     local I
     Bc = B.chunks
     Bi = 1 # block index
-    i1 = 1 # index of current block beginng in B
+    i1 = 1 # index of current block beginning in B
     i = 1  # index of the _next_ one in I
     c = Bc[1] # current block
 
-    start = -1 # the begining of ones block
+    start = -1 # the beginning of ones block
     stop = -1  # the end of ones block
 
     @inbounds while true # I not materialized
@@ -430,22 +430,22 @@ function _findall(B::BitVector)::Union{UnitRange{Int}, Vector{Int}}
         if c != 0 # mixed ones and zeros in block
             tz = trailing_zeros(c)
             lz = leading_zeros(c)
-            co = c >> tz == (one(UInt64) << (64 - lz - tz)) - 1 # block of countinous ones in c
+            co = c >> tz == (one(UInt64) << (64 - lz - tz)) - 1 # block of continuous ones in c
             if stop != -1  # already found block of ones and zeros, just not materialized
                 I = Vector{Int}(undef, nnzB)
                 for j in 1:i-1
                     I[j] = start + j - 1
                 end
                 break
-            elseif !co # not countinous ones
+            elseif !co # not continuous ones
                 I = Vector{Int}(undef, nnzB)
                 if start != -1
                     for j in 1:i-1
                         I[j] = start + j - 1
                     end
                 end
                 break
-            else # countinous block of ones
+            else # continuous block of ones
                 if start != -1
                     if tz > 0 # like __1111__ or 111111__
                         I = Vector{Int}(undef, nnzB)

test/broadcasting.jl

@@ -1855,7 +1855,7 @@ end
     @test_throws ArgumentError df[!, [:x1, :x3]] .= "a"
 end
 
-@testset "broadcasting over heterogenous columns" begin
+@testset "broadcasting over heterogeneous columns" begin
     df = DataFrame(x=[1, 1.0, big(1), "1"])
     f_identity(x) = x
     @test df == f_identity.(df)