doc: misc updates for missing.md (#42500)

doc/src/manual/missing.md

@@ -1,7 +1,7 @@
 # [Missing Values](@id missing)
 
-Julia provides support for representing missing values in the statistical sense,
-that is for situations where no value is available for a variable in an observation,
+Julia provides support for representing missing values in the statistical sense.
+This is for situations where no value is available for a variable in an observation,
 but a valid value theoretically exists.
 Missing values are represented via the [`missing`](@ref) object, which is the
 singleton instance of the type [`Missing`](@ref). `missing` is equivalent to
@@ -15,7 +15,7 @@ and behaves like them in most situations.
 operators and functions.
 For these functions, uncertainty about the value of one of the operands
 induces uncertainty about the result. In practice, this means a math operation
-involving a `missing` value generally returns `missing`
+involving a `missing` value generally returns `missing`:
 ```jldoctest
 julia> missing + 1
 missing
@@ -27,14 +27,16 @@ julia> abs(missing)
 missing
 ```
 
-As `missing` is a normal Julia object, this propagation rule only works
+Since `missing` is a normal Julia object, this propagation rule only works
 for functions which have opted in to implement this behavior. This can be
-achieved either via a specific method defined for arguments of type `Missing`,
-or simply by accepting arguments of this type, and passing them to functions
-which propagate them (like standard math operators). Packages should consider
+achieved by:
+ - adding a specific method defined for arguments of type `Missing`,
+ - accepting arguments of this type, and passing them to functions
+   which propagate them (like standard math operators).
+Packages should consider
 whether it makes sense to propagate missing values when defining new functions,
-and define methods appropriately if that is the case. Passing a `missing` value
-to a function for which no method accepting arguments of type `Missing` is defined
+and define methods appropriately if this is the case. Passing a `missing` value
+to a function which does not have a method accepting arguments of type `Missing`
 throws a [`MethodError`](@ref), just like for any other type.
 
 Functions that do not propagate `missing` values can be made to do so by wrapping
@@ -46,7 +48,8 @@ For example, `f(x)` becomes `passmissing(f)(x)`.
 
 Standard equality and comparison operators follow the propagation rule presented
 above: if any of the operands is `missing`, the result is `missing`.
-Here are a few examples
+Here are a few examples:
+
 ```jldoctest
 julia> missing == 1
 missing
@@ -66,9 +69,10 @@ be used to test whether a value is missing. To test whether `x` is `missing`,
 use [`ismissing(x)`](@ref).
 
 Special comparison operators [`isequal`](@ref) and [`===`](@ref) are exceptions
-to the propagation rule: they always return a `Bool` value, even in the presence
+to the propagation rule. They will always return a `Bool` value, even in the presence
 of `missing` values, considering `missing` as equal to `missing` and as different
-from any other value. They can therefore be used to test whether a value is `missing`
+from any other value. They can therefore be used to test whether a value is `missing`:
+
 ```jldoctest
 julia> missing === 1
 false
@@ -85,7 +89,8 @@ true
 
 The [`isless`](@ref) operator is another exception: `missing` is considered
 as greater than any other value. This operator is used by [`sort`](@ref),
-which therefore places `missing` values after all other values.
+which therefore places `missing` values after all other values:
+
 ```jldoctest
 julia> isless(1, missing)
 true
@@ -100,18 +105,19 @@ false
 ## Logical operators
 
 Logical (or boolean) operators [`|`](@ref), [`&`](@ref) and [`xor`](@ref) are
-another special case, as they only propagate `missing` values when it is logically
-required. For these operators, whether or not the result is uncertain depends
-on the particular operation, following the well-established rules of
+another special case since they only propagate `missing` values when it is logically
+required. For these operators, whether or not the result is uncertain, depends
+on the particular operation. This follows the well-established rules of
 [*three-valued logic*](https://en.wikipedia.org/wiki/Three-valued_logic) which are
-also implemented by `NULL` in SQL and `NA` in R. This abstract definition actually
+implemented by e.g. `NULL` in SQL and `NA` in R. This abstract definition
 corresponds to a relatively natural behavior which is best explained
 via concrete examples.
 
 Let us illustrate this principle with the logical "or" operator [`|`](@ref).
 Following the rules of boolean logic, if one of the operands is `true`,
 the value of the other operand does not have an influence on the result,
-which will always be `true`
+which will always be `true`:
+
 ```jldoctest
 julia> true | true
 true
@@ -123,12 +129,13 @@ julia> false | true
 true
 ```
 
-Based on this observation, we can conclude that if one of the operands is `true`
+Based on this observation, we can conclude if one of the operands is `true`
 and the other `missing`, we know that the result is `true` in spite of the
 uncertainty about the actual value of one of the operands. If we had
 been able to observe the actual value of the second operand, it could only be
 `true` or `false`, and in both cases the result would be `true`. Therefore,
-in this particular case, missingness does *not* propagate
+in this particular case, missingness does *not* propagate:
+
 ```jldoctest
 julia> true | missing
 true
@@ -139,7 +146,8 @@ true
 
 On the contrary, if one of the operands is `false`, the result could be either
 `true` or `false` depending on the value of the other operand. Therefore,
-if that operand is `missing`, the result has to be `missing` too
+if that operand is `missing`, the result has to be `missing` too:
+
 ```jldoctest
 julia> false | true
 true
@@ -160,7 +168,8 @@ missing
 The behavior of the logical "and" operator [`&`](@ref) is similar to that of the
 `|` operator, with the difference that missingness does not propagate when
 one of the operands is `false`. For example, when that is the case of the first
-operand
+operand:
+
 ```jldoctest
 julia> false & false
 false
@@ -173,7 +182,8 @@ false
 ```
 
 On the other hand, missingness propagates when one of the operands is `true`,
-for example the first one
+for example the first one:
+
 ```jldoctest
 julia> true & true
 true
@@ -188,16 +198,17 @@ missing
 Finally, the "exclusive or" logical operator [`xor`](@ref) always propagates
 `missing` values, since both operands always have an effect on the result.
 Also note that the negation operator [`!`](@ref) returns `missing` when the
-operand is `missing` just like other unary operators.
+operand is `missing`, just like other unary operators.
 
 ## Control Flow and Short-Circuiting Operators
 
 Control flow operators including [`if`](@ref), [`while`](@ref) and the
 [ternary operator](@ref man-conditional-evaluation) `x ? y : z`
 do not allow for missing values. This is because of the uncertainty about whether
-the actual value would be `true` or `false` if we could observe it,
-which implies that we do not know how the program should behave. A [`TypeError`](@ref)
-is thrown as soon as a `missing` value is encountered in this context
+the actual value would be `true` or `false` if we could observe it.
+This implies we do not know how the program should behave. In this case, a
+[`TypeError`](@ref) is thrown as soon as a `missing` value is encountered in this context:
+
 ```jldoctest
 julia> if missing
            println("here")
@@ -208,7 +219,8 @@ ERROR: TypeError: non-boolean (Missing) used in boolean context
 For the same reason, contrary to logical operators presented above,
 the short-circuiting boolean operators [`&&`](@ref) and [`||`](@ref) do not
 allow for `missing` values in situations where the value of the operand
-determines whether the next operand is evaluated or not. For example
+determines whether the next operand is evaluated or not. For example:
+
 ```jldoctest
 julia> missing || false
 ERROR: TypeError: non-boolean (Missing) used in boolean context
@@ -220,10 +232,11 @@ julia> true && missing && false
 ERROR: TypeError: non-boolean (Missing) used in boolean context
 ```
 
-On the other hand, no error is thrown when the result can be determined without
+In contrast, there is no error thrown when the result can be determined without
 the `missing` values. This is the case when the code short-circuits
 before evaluating the `missing` operand, and when the `missing` operand is the
-last one
+last one:
+
 ```jldoctest
 julia> true && missing
 missing
@@ -234,7 +247,8 @@ false
 
 ## Arrays With Missing Values
 
-Arrays containing missing values can be created like other arrays
+Arrays containing missing values can be created like other arrays:
+
 ```jldoctest
 julia> [1, missing]
 2-element Vector{Union{Missing, Int64}}:
@@ -243,7 +257,7 @@ julia> [1, missing]
 ```
 
 As this example shows, the element type of such arrays is `Union{Missing, T}`,
-with `T` the type of the non-missing values. This simply reflects the fact that
+with `T` the type of the non-missing values. This reflects the fact that
 array entries can be either of type `T` (here, `Int64`) or of type `Missing`.
 This kind of array uses an efficient memory storage equivalent to an `Array{T}`
 holding the actual values combined with an `Array{UInt8}` indicating the type
@@ -252,6 +266,7 @@ of the entry (i.e. whether it is `Missing` or `T`).
 Arrays allowing for missing values can be constructed with the standard syntax.
 Use `Array{Union{Missing, T}}(missing, dims)` to create arrays filled with
 missing values:
+
 ```jldoctest
 julia> Array{Union{Missing, String}}(missing, 2, 3)
 2×3 Matrix{Union{Missing, String}}:
@@ -264,10 +279,12 @@ julia> Array{Union{Missing, String}}(missing, 2, 3)
     `missing`, but this is not the correct way to obtain such an array.
     Use a `missing` constructor as shown above instead.
 
-An array allowing for `missing` values but which does not contain any such value
-can be converted back to an array which does not allow for missing values using
+An array with element type allowing `missing` entries (e.g. `Vector{Union{Missing, T}}`)
+which does not contain any `missing` entries can be converted to an array type that does
+not allow for `missing` entries (e.g. `Vector{T}`) using
 [`convert`](@ref). If the array contains `missing` values, a `MethodError` is thrown
-during conversion
+during conversion:
+
 ```jldoctest
 julia> x = Union{Missing, String}["a", "b"]
 2-element Vector{Union{Missing, String}}:
@@ -287,23 +304,27 @@ julia> y = Union{Missing, String}[missing, "b"]
 julia> convert(Array{String}, y)
 ERROR: MethodError: Cannot `convert` an object of type Missing to an object of type String
 ```
+
 ## Skipping Missing Values
 
 Since `missing` values propagate with standard mathematical operators, reduction
-functions return `missing` when called on arrays which contain missing values
+functions return `missing` when called on arrays which contain missing values:
+
 ```jldoctest
 julia> sum([1, missing])
 missing
 ```
 
-In this situation, use the [`skipmissing`](@ref) function to skip missing values
+In this situation, use the [`skipmissing`](@ref) function to skip missing values:
+
 ```jldoctest
 julia> sum(skipmissing([1, missing]))
 1
 ```
 
 This convenience function returns an iterator which filters out `missing` values
-efficiently. It can therefore be used with any function which supports iterators
+efficiently. It can therefore be used with any function which supports iterators:
+
 ```jldoctest skipmissing; setup = :(using Statistics)
 julia> x = skipmissing([3, missing, 2, 1])
 skipmissing(Union{Missing, Int64}[3, missing, 2, 1])
@@ -320,8 +341,9 @@ julia> mapreduce(sqrt, +, x)
 
 Objects created by calling `skipmissing` on an array can be indexed using indices
 from the parent array. Indices corresponding to missing values are not valid for
-these objects and an error is thrown when trying to use them (they are also skipped
-by `keys` and `eachindex`)
+these objects, and an error is thrown when trying to use them (they are also skipped
+by `keys` and `eachindex`):
+
 ```jldoctest skipmissing
 julia> x[1]
 3
@@ -332,9 +354,10 @@ ERROR: MissingException: the value at index (2,) is missing
 ```
 
 This allows functions which operate on indices to work in combination with `skipmissing`.
-This is notably the case for search and find functions, which return indices
-valid for the object returned by `skipmissing` which are also the indices of the
-matching entries *in the parent array*
+This is notably the case for search and find functions. These functions return indices
+valid for the object returned by `skipmissing`, and are also the indices of the
+matching entries *in the parent array*:
+
 ```jldoctest skipmissing
 julia> findall(==(1), x)
 1-element Vector{Int64}:
@@ -347,7 +370,8 @@ julia> argmax(x)
 1
 ```
 
-Use [`collect`](@ref) to extract non-`missing` values and store them in an array
+Use [`collect`](@ref) to extract non-`missing` values and store them in an array:
+
 ```jldoctest skipmissing
 julia> collect(x)
 3-element Vector{Int64}:
@@ -362,9 +386,10 @@ The three-valued logic described above for logical operators is also used
 by logical functions applied to arrays. Thus, array equality tests using
 the [`==`](@ref) operator return `missing` whenever the result cannot be
 determined without knowing the actual value of the `missing` entry. In practice,
-this means that `missing` is returned if all non-missing values of the compared
+this means `missing` is returned if all non-missing values of the compared
 arrays are equal, but one or both arrays contain missing values (possibly at
-different positions)
+different positions):
+
 ```jldoctest
 julia> [1, missing] == [2, missing]
 false
@@ -377,7 +402,8 @@ missing
 ```
 
 As for single values, use [`isequal`](@ref) to treat `missing` values as equal
-to other `missing` values but different from non-missing values
+to other `missing` values, but different from non-missing values:
+
 ```jldoctest
 julia> isequal([1, missing], [1, missing])
 true
@@ -387,7 +413,8 @@ false
 ```
 
 Functions [`any`](@ref) and [`all`](@ref) also follow the rules of
-three-valued logic, returning `missing` when the result cannot be determined
+three-valued logic. Thus, returning `missing` when the result cannot be determined:
+
 ```jldoctest
 julia> all([true, missing])
 missing