diff --git a/docs/README.md b/docs/README.md
index 7fbaa78f6..3471d1beb 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -62,5 +62,3 @@ Code samples for the documentation website reside in [core/.../test/.../samples/
and [tests/.../samples/api](../tests/src/test/kotlin/org/jetbrains/kotlinx/dataframe/samples/api) (for samples can depend on other I/O modules)
and they are copied over to Markdown files in [docs/StardustDocs/topics](./StardustDocs/topics)
by [Korro](https://github.com/devcrocod/korro).
-
-
diff --git a/docs/StardustDocs/topics/ColumnSelectors.md b/docs/StardustDocs/topics/ColumnSelectors.md
index eded79ccf..dceef4254 100644
--- a/docs/StardustDocs/topics/ColumnSelectors.md
+++ b/docs/StardustDocs/topics/ColumnSelectors.md
@@ -49,9 +49,9 @@ or `ColumnSet` that adheres to the optional given condition. If no column adhere
`NoSuchElementException` is thrown.
##### Col {collapsible="true"}
-`col(name)`, `col(5)`, `this[5]`
+`col(name)`, `col(5)`
-Creates a [ColumnAccessor](DataColumn.md#column-accessors) (or `SingleColumn`) for a column with the given
+Creates a [ColumnAccessor](DataColumn.md) (or `SingleColumn`) for a column with the given
argument from the top-level or specified [column group](DataColumn.md#columngroup). The argument can be either an
index (`Int`) or a reference to a column (`String`, `ColumnPath`, `KProperty`, or `ColumnAccessor`;
any [AccessApi](apiLevels.md)).
@@ -59,7 +59,7 @@ any [AccessApi](apiLevels.md)).
##### Value Col, Frame Col, Col Group {collapsible="true"}
`valueCol(name)`, `valueCol(5)`, `frameCol(name)`, `frameCol(5)`, `colGroup(name)`, `colGroup(5)`
-Creates a [ColumnAccessor](DataColumn.md#column-accessors) (or `SingleColumn`) for a
+Creates a [ColumnAccessor](DataColumn.md) (or `SingleColumn`) for a
[value column](DataColumn.md#valuecolumn) / [frame column](DataColumn.md#framecolumn) /
[column group](DataColumn.md#columngroup) with the given argument from the top-level or
specified [column group](DataColumn.md#columngroup). The argument can be either an index (`Int`) or a reference
diff --git a/docs/StardustDocs/topics/Compiler-Plugin.md b/docs/StardustDocs/topics/Compiler-Plugin.md
index dbf0bf364..5cd1dbfa3 100644
--- a/docs/StardustDocs/topics/Compiler-Plugin.md
+++ b/docs/StardustDocs/topics/Compiler-Plugin.md
@@ -3,7 +3,9 @@
Kotlin DataFrame compiler plugin: available in Gradle projects, is coming to Kotlin Notebook and Maven projects soon.
Check out this video that shows how expressions update the schema of a dataframe:
-
+
+
+
## Setup
diff --git a/docs/StardustDocs/topics/_shadow_resources.md b/docs/StardustDocs/topics/_shadow_resources.md
index aac022ad4..954797634 100644
--- a/docs/StardustDocs/topics/_shadow_resources.md
+++ b/docs/StardustDocs/topics/_shadow_resources.md
@@ -164,4 +164,4 @@
-
\ No newline at end of file
+
diff --git a/docs/StardustDocs/topics/gettingStarted/gettingStartedGradleAdvanced.md b/docs/StardustDocs/topics/gettingStarted/gettingStartedGradleAdvanced.md
index 8ce8a2daa..4239ec9f2 100644
--- a/docs/StardustDocs/topics/gettingStarted/gettingStartedGradleAdvanced.md
+++ b/docs/StardustDocs/topics/gettingStarted/gettingStartedGradleAdvanced.md
@@ -224,7 +224,7 @@ tasks.withType(org.jmailen.gradle.kotlinter.tasks.LintTask).all {
-```.editorconfig
+```editorconfig
[{**/*.Generated.kt,**/*$Extensions.kt}]
ktlint = disabled
```
diff --git a/docs/StardustDocs/topics/guides/Kotlin-DataFrame-Features-in-Kotlin-Notebook.md b/docs/StardustDocs/topics/guides/Kotlin-DataFrame-Features-in-Kotlin-Notebook.md
index 3cda416c8..cc75119ca 100644
--- a/docs/StardustDocs/topics/guides/Kotlin-DataFrame-Features-in-Kotlin-Notebook.md
+++ b/docs/StardustDocs/topics/guides/Kotlin-DataFrame-Features-in-Kotlin-Notebook.md
@@ -22,7 +22,7 @@ Here are the key features:
You can quickly load data into `DataFrame` into a notebook by simply dragging and dropping a file
(.csv/.json/.xlsx and .geojson/.shp) directly into the notebook editor:
-
+
### Visual Data Exploration
**Page through your data**:
@@ -35,18 +35,26 @@ This is a convenient alternative to using `sortBy` in separate cells.
**Go straight to the data you need**:
You can jump directly to a particular row or column if you want something specific.
This makes working with large datasets more straightforward.
-
+
+
+
+
### Drill down into nested data
When your data has multiple layers, like a table within a table,
you can now click on a cell containing a nested table to view these details directly.
This makes it easy to go deeper into your data and then return to where you were.
-
+
+
+
+
### Visualize multiple tables via tabs
You can open and visualize multiple tables in separate tabs.
This feature is tailored to those who need to compare, contrast, or monitor different datasets simultaneously.
-
+
+
+
### Exporting to files
@@ -55,7 +63,9 @@ You can export data directly from the dataframe into various file formats.
This simplifies sharing and further analysis.
The interface supports exporting data to JSON for web applications,
CSV for spreadsheet tools, and XML for data interchange.
-
+
+
+
### Convenient copying of data from tables
@@ -64,7 +74,9 @@ or you can use keyboard shortcuts for quicker selection
and then copy what’s needed with a simple right-click or another shortcut.
It’s designed to feel intuitive,
like copying text from a document, but with the structure and format of your data preserved.
-
+
+
+
To get started, ensure you have the latest version of the Kotlin Notebook Plugin installed in IntelliJ IDEA,
diff --git a/docs/StardustDocs/topics/median.md b/docs/StardustDocs/topics/median.md
index 97c91333f..ab1fcd05f 100644
--- a/docs/StardustDocs/topics/median.md
+++ b/docs/StardustDocs/topics/median.md
@@ -58,13 +58,13 @@ See [column selectors](ColumnSelectors.md) for how to select the columns for thi
The following automatic type conversions are performed for the `median` operation.
(Note that `null` only appears in the return type when using `-orNull` overloads).
-| Conversion | Result for Empty Input |
-|--------------------------------|------------------------|
-| T -> T where T : Comparable | null |
-| Int -> Double | null |
-| Byte -> Double | null |
-| Short -> Double | null |
-| Long -> Double | null |
-| Double -> Double | null |
-| Float -> Double | null |
-| Nothing -> Nothing | null |
+| Conversion | Result for Empty Input |
+|----------------------------------|------------------------|
+| T -> T where T : Comparable\ | null |
+| Int -> Double | null |
+| Byte -> Double | null |
+| Short -> Double | null |
+| Long -> Double | null |
+| Double -> Double | null |
+| Float -> Double | null |
+| Nothing -> Nothing | null |
diff --git a/docs/StardustDocs/topics/minmax.md b/docs/StardustDocs/topics/minmax.md
index e246c1c20..4c096e6c0 100644
--- a/docs/StardustDocs/topics/minmax.md
+++ b/docs/StardustDocs/topics/minmax.md
@@ -49,13 +49,13 @@ See [column selectors](ColumnSelectors.md) for how to select the columns for thi
The following automatic type conversions are performed for the `min` and `max` operations.
(Note that `null` only appears in the return type when using `-orNull` overloads).
-| Conversion | Result for Empty Input |
-|--------------------------------|------------------------|
-| T -> T where T : Comparable | null |
-| Int -> Int | null |
-| Byte -> Byte | null |
-| Short -> Short | null |
-| Long -> Long | null |
-| Double -> Double | null |
-| Float -> Float | null |
-| Nothing -> Nothing | null |
+| Conversion | Result for Empty Input |
+|----------------------------------|------------------------|
+| T -> T where T : Comparable\ | null |
+| Int -> Int | null |
+| Byte -> Byte | null |
+| Short -> Short | null |
+| Long -> Long | null |
+| Double -> Double | null |
+| Float -> Float | null |
+| Nothing -> Nothing | null |
diff --git a/docs/StardustDocs/topics/parse.md b/docs/StardustDocs/topics/parse.md
index c7091f41c..f76a7c296 100644
--- a/docs/StardustDocs/topics/parse.md
+++ b/docs/StardustDocs/topics/parse.md
@@ -96,3 +96,42 @@ DataFrame.parser.addDateTimePattern("dd.MM.uuuu HH:mm:ss")
```
+
+For `locale`, this means that the one being used by the parser is defined as:
+
+↪ The locale given as function argument directly, or in `parserOptions`, if it is not `null`, else
+
+ ↪ The locale set by `DataFrame.parser.locale = ...`, if it is not `null`, else
+
+ ↪ `Locale.getDefault()`, which is the system's default locale that can be changed with `Locale.setDefault()`.
+
+### Parsing Doubles
+
+DataFrame has a new fast and powerful double parser enabled by default.
+It is based on [the FastDoubleParser library](https://github.com/wrandelshofer/FastDoubleParser) for its
+high performance and configurability
+(in the future, we might expand this support to `Float`, `BigDecimal`, and `BigInteger` as well).
+
+The parser is locale-aware; it will use the locale set by the
+[(global)](#global-parser-options) [parser options](#parser-options) to parse the doubles.
+It also has a fallback mechanism built in, meaning it can recognize characters from
+all other locales (and some from [Wikipedia](https://en.wikipedia.org/wiki/Decimal_separator))
+and parse them correctly as long as they don't conflict with the current locale.
+
+For example, if your locale uses ',' as decimal separator, it will not recognize ',' as thousands separator, but it will
+recognize ''', ' ', '٬', '_', ' ', etc. as such.
+The same holds for characters like "e", "inf", "×10^", "NaN", etc. (ignoring case).
+
+This means you can safely parse `"123'456 789,012.345×10^6"` with a US locale but not `"1.234,5"`.
+
+Aside from this, DataFrame also explicitly recognizes "∞", "inf", "infinity", and "infty" as `Double.POSITIVE_INFINITY`
+(as well as their negative counterparts), "nan", "na", and "n/a" as `Double.NaN`,
+and all forms of whitespace are treated equally.
+
+If `FastDoubleParser` fails to parse a `String` as `Double`, DataFrame will try
+to parse it using the standard `NumberFormat.parse()` function as a last resort.
+
+If you experience any issues with the new parser, you can turn it off by setting
+`useFastDoubleParser = false`, which will use the old `NumberFormat.parse()` function instead.
+
+Please [report](https://github.com/Kotlin/dataframe/issues) any issues you encounter.
diff --git a/docs/StardustDocs/topics/percentile.md b/docs/StardustDocs/topics/percentile.md
index bef6daa08..5fe3905fd 100644
--- a/docs/StardustDocs/topics/percentile.md
+++ b/docs/StardustDocs/topics/percentile.md
@@ -80,13 +80,13 @@ See [column selectors](ColumnSelectors.md) for how to select the columns for thi
The following automatic type conversions are performed for the `percentile` operation.
(Note that `null` only appears in the return type when using `-orNull` overloads).
-| Conversion | Result for Empty Input |
-|--------------------------------|------------------------|
-| T -> T where T : Comparable | null |
-| Int -> Double | null |
-| Byte -> Double | null |
-| Short -> Double | null |
-| Long -> Double | null |
-| Double -> Double | null |
-| Float -> Double | null |
-| Nothing -> Nothing | null |
+| Conversion | Result for Empty Input |
+|----------------------------------|------------------------|
+| T -> T where T : Comparable\ | null |
+| Int -> Double | null |
+| Byte -> Double | null |
+| Short -> Double | null |
+| Long -> Double | null |
+| Double -> Double | null |
+| Float -> Double | null |
+| Nothing -> Nothing | null |