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Fix admonitions
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@nathanrboyer
nathanrboyer committed May 30, 2024
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132 changes: 69 additions & 63 deletions docs/src/man/basics.md
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Expand Up @@ -1752,11 +1752,12 @@ a `Not`, `Between`, `All`, or `Cols` expression,
or a `:`.
See the [Indexing](@ref) API for the full list of possible values with references.

!!! Note
The Julia parser sometimes prevents `:` from being used by itself.
If you get
`ERROR: syntax: whitespace not allowed after ":" used for quoting`,
try using `All()`, `Cols(:)`, or `(:)` instead to select all columns.
!!! note

The Julia parser sometimes prevents `:` from being used by itself.
If you get
`ERROR: syntax: whitespace not allowed after ":" used for quoting`,
try using `All()`, `Cols(:)`, or `(:)` instead to select all columns.

```julia
julia> df = DataFrame(
Expand Down Expand Up @@ -1831,14 +1832,15 @@ julia> subset(df2, [:minor, :male])
1 │ Jimmy true true
```

!!! Note
Using `Symbol` in `source_column_selector` will perform slightly faster than using `String`.
However, `String` is convenient when column names contain spaces.
!!! note

Using `Symbol` in `source_column_selector` will perform slightly faster than using `String`.
However, `String` is convenient when column names contain spaces.

All elements of `source_column_selector` must be the same type
(unless wrapped in `Cols`),
e.g. `subset(df2, [:minor, "male"])` will error
since `Symbol` and `String` are used simultaneously.)
All elements of `source_column_selector` must be the same type
(unless wrapped in `Cols`),
e.g. `subset(df2, [:minor, "male"])` will error
since `Symbol` and `String` are used simultaneously.

#### `operation_function`
Inside an `operation` pair, `operation_function` is a function
Expand Down Expand Up @@ -1996,7 +1998,8 @@ julia> subset(df, :b => ByRow(<(5))) # shorter version of the previous
2 │ 3 4
```

!!! Note
!!! note

`operation_functions` within `subset` or `subset!` function calls
must return a Boolean vector.
`true` elements in the Boolean vector will determine
Expand Down Expand Up @@ -2349,31 +2352,31 @@ julia> transform(df, :a => (x -> 10 .* x) => (s -> "new_" * s)) # with anonymous
4 │ 4 8 40
```

!!! Note
It is a good idea to wrap anonymous functions in parentheses
to avoid the `=>` operator accidently becoming part of the anonymous function.
The examples above do not work correctly without the parentheses!
```julia
julia> transform(df, :a => x -> 10 .* x => add_prefix) # Not what we wanted!
4×3 DataFrame
Row │ a b a_function
│ Int64 Int64 Pair…
─────┼────────────────────────────────────────────
1 │ 1 5 [10, 20, 30, 40]=>add_prefix
2 │ 2 6 [10, 20, 30, 40]=>add_prefix
3 │ 3 7 [10, 20, 30, 40]=>add_prefix
4 │ 4 8 [10, 20, 30, 40]=>add_prefix

julia> transform(df, :a => x -> 10 .* x => s -> "new_" * s) # Not what we wanted!
4×3 DataFrame
Row │ a b a_function
│ Int64 Int64 Pair…
─────┼─────────────────────────────────────
1 │ 1 5 [10, 20, 30, 40]=>#18
2 │ 2 6 [10, 20, 30, 40]=>#18
3 │ 3 7 [10, 20, 30, 40]=>#18
4 │ 4 8 [10, 20, 30, 40]=>#18
```
!!! note

It is a good idea to wrap anonymous functions in parentheses
to avoid the `=>` operator accidently becoming part of the anonymous function.
The examples above do not work correctly without the parentheses!
```julia
julia> transform(df, :a => x -> 10 .* x => add_prefix) # Not what we wanted!
4×3 DataFrame
Row │ a b a_function
│ Int64 Int64 Pair…
─────┼────────────────────────────────────────────
1 │ 1 5 [10, 20, 30, 40]=>add_prefix
2 │ 2 6 [10, 20, 30, 40]=>add_prefix
3 │ 3 7 [10, 20, 30, 40]=>add_prefix
4 │ 4 8 [10, 20, 30, 40]=>add_prefix
julia> transform(df, :a => x -> 10 .* x => s -> "new_" * s) # Not what we wanted!
4×3 DataFrame
Row │ a b a_function
│ Int64 Int64 Pair…
─────┼─────────────────────────────────────
1 │ 1 5 [10, 20, 30, 40]=>#18
2 │ 2 6 [10, 20, 30, 40]=>#18
3 │ 3 7 [10, 20, 30, 40]=>#18
4 │ 4 8 [10, 20, 30, 40]=>#18
```

A renaming function will not work in the
`source_column_selector => new_column_names` operation form
Expand Down Expand Up @@ -2481,11 +2484,12 @@ julia> transform(df, :data => AsTable) # keeps names from named tuples
2 │ (a = 3, b = 4) 3 4
```

!!! Note
To pack multiple columns into a single column of `NamedTuple`s
(reverse of the above operation)
apply the `identity` function `ByRow`, e.g.
`transform(df, AsTable([:a, :b]) => ByRow(identity) => :data)`.
!!! note

To pack multiple columns into a single column of `NamedTuple`s
(reverse of the above operation)
apply the `identity` function `ByRow`, e.g.
`transform(df, AsTable([:a, :b]) => ByRow(identity) => :data)`.

Renaming functions also work for multi-column transformations,
but they must operate on a vector of strings.
Expand Down Expand Up @@ -2756,18 +2760,19 @@ julia> ["x" => "a", "y" => "b"] == (["x", "y"] .=> ["a", "b"])
true
```

!!! Note
These operation pairs (or vector of pairs) can be given variable names.
This is uncommon in practice but could be helpful for intermediate
inspection and testing.
```julia
df = DataFrame(x = 1:3, y = 4:6) # create data frame
operation = ["x", "y"] .=> ["a", "b"] # save operation to variable
typeof(operation) # check type of operation
first(operation) # check first pair in operation
last(operation) # check last pair in operation
select(df, operation) # manipulate `df` with `operation`
```
!!! note

These operation pairs (or vector of pairs) can be given variable names.
This is uncommon in practice but could be helpful for intermediate
inspection and testing.
```julia
df = DataFrame(x = 1:3, y = 4:6) # create data frame
operation = ["x", "y"] .=> ["a", "b"] # save operation to variable
typeof(operation) # check type of operation
first(operation) # check first pair in operation
last(operation) # check last pair in operation
select(df, operation) # manipulate `df` with `operation`
```

In Julia,
a non-vector broadcasted with a vector will be repeated in each resultant pair element.
Expand Down Expand Up @@ -2932,14 +2937,15 @@ julia> select(
4 │ 4 301 317 273
```

!!! Note Notes
* `Not("Time")` or `2:4` would have been equally good choices for `source_column_selector` in the above operations.
* Don't forget `ByRow` if your function is to be applied to elements rather than entire column vectors.
Without `ByRow`, the manipulations above would have thrown
`ERROR: MethodError: no method matching +(::Vector{Int64}, ::Int64)`.
* Regular expression (`r""`) and `:` `source_column_selectors`
must be wrapped in `Cols` to be properly broadcasted
because otherwise the broadcasting occurs before the expression is expanded into a vector of matches.
!!! note "Notes"

* `Not("Time")` or `2:4` would have been equally good choices for `source_column_selector` in the above operations.
* Don't forget `ByRow` if your function is to be applied to elements rather than entire column vectors.
Without `ByRow`, the manipulations above would have thrown
`ERROR: MethodError: no method matching +(::Vector{Int64}, ::Int64)`.
* Regular expression (`r""`) and `:` `source_column_selectors`
must be wrapped in `Cols` to be properly broadcasted
because otherwise the broadcasting occurs before the expression is expanded into a vector of matches.

You could also broadcast different columns to different functions
by supplying a vector of functions.
Expand Down

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