typos (#355)

Author: spaette

docs/src/dplyr.md

@@ -30,7 +30,7 @@ To install DataFramesMeta.jl, which also installs DataFrames.jl:
 
 ```julia
 import Pkg
-Pkg.activate(; temp=true) # activate a temprary environment for this tutorial
+Pkg.activate(; temp=true) # activate a temporary environment for this tutorial
 Pkg.add("DataFramesMeta");
 ```
 
@@ -211,7 +211,7 @@ msleep_1 = @select msleep :name :sleep_total
 msleep_2 = @rsubset msleep_1 :sleep_total > 16
 ```
 
-Now in this case, we will pipe the msleep data frame to the function that will select two columns (`:name` and `:sleep_total`) and then pipe the new data frame to the `@rsubset` opertaion. This method involves awkwardly creating and naming temporary data frames. We can avoid this with `@chain`.
+Now in this case, we will pipe the msleep data frame to the function that will select two columns (`:name` and `:sleep_total`) and then pipe the new data frame to the `@rsubset` operation. This method involves awkwardly creating and naming temporary data frames. We can avoid this with `@chain`.
 
 ```@repl 1
 @chain msleep begin 

docs/src/index.md

@@ -421,7 +421,7 @@ julia> @rtransform df @passmissing :x = parse(Int, :x_str)
 ## Passing keyword arguments to underlying DataFrames.jl functions
 
 All DataFramesMeta.jl macros allow passing of keyword arguments to their DataFrames.jl
-function equivelents. The table below describes the correspondence between DataFramesMeta.jl
+function equivalents. The table below describes the correspondence between DataFramesMeta.jl
 macros and the function that is actually called by the macro. 
 
 | Macro | Base DataFrames.jl function called |
@@ -634,7 +634,7 @@ inside the expression. The command
 
 will fail. 
 
-Finally, note that everyting inside `AsTable` is escaped by default.
+Finally, note that everything inside `AsTable` is escaped by default.
 There is no ned to use `$` inside `AsTable` on the right-hand side.
 For example
 
@@ -821,7 +821,7 @@ Not all functions in DataFrames.jl allow for multi-column selectors, so detailed
 subset(df, [:a, :b])
 ```
 
-will fail in DataFrames.jl, bcause `DataFrames.subset` does not support vectors of column names. Likewise, `@subset df $[:a, :b]` will fail. The macros which support multi-column selectors are 
+will fail in DataFrames.jl, because `DataFrames.subset` does not support vectors of column names. Likewise, `@subset df $[:a, :b]` will fail. The macros which support multi-column selectors are 
 
 * `@select`
 * `@transform` (multi-argument selectors have no effect)

src/macros.jl

@@ -183,7 +183,7 @@ julia> df
 
 ### Comparison with `@.` and Base broadcasting
 
-Base Julia provides the broadasting macro `@.` and in many cases `@.`
+Base Julia provides the broadcasting macro `@.` and in many cases `@.`
 and `@byrow` will give equivalent results. But there are important
 deviations in behavior. Consider the setup
 
@@ -1848,7 +1848,7 @@ using broadcasting.
 
 To avoid writing `@byrow` multiple times when performing multiple
 transformations by row, `@select` allows `@byrow` at the
-beginning of a block of selectations (i.e. `@byrow begin... end`).
+beginning of a block of selections (i.e. `@byrow begin... end`).
 All transformations in the block will operate by row.
 
 $ASTABLE_MACRO_FLAG_DOCS
@@ -2261,7 +2261,7 @@ end
 ##############################################################################
 
 function by_helper(x, what, args...)
-    # Handle keyword arguments initially due the gouping instruction, what
+    # Handle keyword arguments initially due the grouping instruction, what
     if x isa Expr && x.head === :parameters
         # with keyword arguments, everything is shifted to
         # the right
@@ -2440,7 +2440,7 @@ end
 """
     @distinct(d, args...)
 
-Return the first occurence of unique rows in an `AbstractDataFrame` according 
+Return the first occurrence of unique rows in an `AbstractDataFrame` according 
 to given combinations of values in selected columns or their transformation. 
 `args` can be most column selectors or transformation accepted by `select`. 
 Users should note that `@distinct` differs from `unique` in DataFrames.jl,

src/parsing.jl

@@ -231,7 +231,7 @@ call later on.
 
 If `wrap_byrow=true` then the function gets wrapped
 in `ByRow`. If the expression begins with `@byrow`,
-then `get_source_fun` is recurively called on the
+then `get_source_fun` is recursively called on the
 expression that `@byrow` acts on, with `wrap_byrow=true`.
 
 ### Examples

test/astable_flag.jl

@@ -200,7 +200,7 @@ end
 
 @testset "errors with passmissing" begin
     @eval df = DataFrame(y = 1)
-    @test_throws LoadError @eval @transform df @passmising @byrow @astable :x = 2
+    @test_throws LoadError @eval @transform df @passmissing @byrow @astable :x = 2
     @test_throws LoadError @eval @transform df @byrow @astable @passmissing :x = 2
     @test_throws LoadError @eval @transform df @astable @passmissing @byrow :x = 2
     @test_throws LoadError @eval @rtransform df @astable @passmissing :x = 2

test/parsing.jl

@@ -10,7 +10,7 @@ macro protect(x)
     esc(DataFramesMeta.get_column_expr(x))
 end
 
-@testset "Returning columnn identifiers" begin
+@testset "Returning column identifiers" begin
 
     v_sym = @protect $[:a, :b]
     @test v_sym == [:a, :b]