alpha9

CHANGELOG.md

@@ -1,5 +1,22 @@
 # Change Log
 
+## [1.0.0-pre-alpha9]
+
+`tech.ml.dataset` version 4.03
+
+### Added
+
+* some operations on grouped dataset can be parallel (`parallel?` option set to `true`). These are: `aggregate`, `unique-by`, `order-by`, `join-columns`, `separate-columns`, `ungroup`
+
+### Fixed
+
+* #2 - docs typo
+* #3 - recover datatypes after ungrouping
+
+### Changed
+
+* `aggregation` uses now in-place ungrouping which is much faster
+
 ## [1.0.0-pre-alpha8]
 
 `tech.ml.dataset` version 3.06

README.md

@@ -1,34 +1,55 @@
-[![](https://img.shields.io/clojars/v/scicloj/tablecloth)](https://clojars.org/scicloj/tablecloth) [![](https://api.travis-ci.org/scicloj/tablecloth.svg?branch=master)](https://travis-ci.org/github/scicloj/tablecloth) [![](https://img.shields.io/badge/zulip-discussion-yellowgreen)](https://clojurians.zulipchat.com/#narrow/stream/236259-tech.2Eml.2Edataset.2Edev/topic/api)
+[![](https://img.shields.io/clojars/v/scicloj/tablecloth)](https://clojars.org/scicloj/tablecloth)
+[![](https://api.travis-ci.org/scicloj/tablecloth.svg?branch=master)](https://travis-ci.org/github/scicloj/tablecloth)
+[![](https://img.shields.io/badge/zulip-discussion-yellowgreen)](https://clojurians.zulipchat.com/#narrow/stream/236259-tech.2Eml.2Edataset.2Edev/topic/api)
 
 Introduction
 ------------
 
-[tech.ml.dataset](https://github.com/techascent/tech.ml.dataset) is a great and fast library which brings columnar dataset to the Clojure. Chris Nuernberger has been working on this library for last year as a part of bigger `tech.ml` stack.
-
-I've started to test the library and help to fix uncovered bugs. My main goal was to compare functionalities with the other standards from other platforms. I focused on R solutions: [dplyr](https://dplyr.tidyverse.org/), [tidyr](https://tidyr.tidyverse.org/) and [data.table](https://rdatatable.gitlab.io/data.table/).
-
-During conversions of the examples I've come up how to reorganized existing `tech.ml.dataset` functions into simple to use API. The main goals were:
-
--   Focus on dataset manipulation functionality, leaving other parts of `tech.ml` like pipelines, datatypes, readers, ML, etc.
--   Single entry point for common operations - one function dispatching on given arguments.
--   `group-by` results with special kind of dataset - a dataset containing subsets created after grouping as a column.
--   Most operations recognize regular dataset and grouped dataset and process data accordingly.
+[tech.ml.dataset](https://github.com/techascent/tech.ml.dataset) is a
+great and fast library which brings columnar dataset to the Clojure.
+Chris Nuernberger has been working on this library for last year as a
+part of bigger `tech.ml` stack.
+
+I’ve started to test the library and help to fix uncovered bugs. My main
+goal was to compare functionalities with the other standards from other
+platforms. I focused on R solutions:
+[dplyr](https://dplyr.tidyverse.org/),
+[tidyr](https://tidyr.tidyverse.org/) and
+[data.table](https://rdatatable.gitlab.io/data.table/).
+
+During conversions of the examples I’ve come up how to reorganized
+existing `tech.ml.dataset` functions into simple to use API. The main
+goals were:
+
+-   Focus on dataset manipulation functionality, leaving other parts of
+    `tech.ml` like pipelines, datatypes, readers, ML, etc.
+-   Single entry point for common operations - one function dispatching
+    on given arguments.
+-   `group-by` results with special kind of dataset - a dataset
+    containing subsets created after grouping as a column.
+-   Most operations recognize regular dataset and grouped dataset and
+    process data accordingly.
 -   One function form to enable thread-first on dataset.
 
-Important! This library is not the replacement of `tech.ml.dataset` nor a separate library. It should be considered as a addition on the top of `tech.ml.dataset`.
+Important! This library is not the replacement of `tech.ml.dataset` nor
+a separate library. It should be considered as a addition on the top of
+`tech.ml.dataset`.
 
-If you want to know more about `tech.ml.dataset` and `tech.ml.datatype` please refer their documentation:
+If you want to know more about `tech.ml.dataset` and `tech.ml.datatype`
+please refer their documentation:
 
 -   [Datatype](https://github.com/techascent/tech.datatype/blob/master/docs/cheatsheet.md)
 -   [Date/time](https://github.com/techascent/tech.datatype/blob/master/docs/datetime.md)
 -   [Dataset](https://github.com/techascent/tech.ml.dataset/blob/master/docs/walkthrough.md)
 
-Join the discussion on [Zulip](https://clojurians.zulipchat.com/#narrow/stream/236259-tech.2Eml.2Edataset.2Edev/topic/api)
+Join the discussion on
+[Zulip](https://clojurians.zulipchat.com/#narrow/stream/236259-tech.2Eml.2Edataset.2Edev/topic/api)
 
 Documentation
 -------------
 
-Please refer [detailed documentation with examples](https://scicloj.github.io/tablecloth/index.html)
+Please refer [detailed documentation with
+examples](https://scicloj.github.io/tablecloth/index.html)
 
 Usage example
 -------------
@@ -50,18 +71,18 @@ Usage example
 
 \_unnamed \[10 3\]:
 
-| :symbol | :year |      :summary|
-|---------|-------|-------------:|
-| AAPL    | 2000  |   21.74833341|
-| AAPL    | 2001  |   10.17583323|
-| AAPL    | 2002  |    9.40833330|
-| AAPL    | 2003  |    9.34749989|
-| AAPL    | 2004  |   18.72333336|
-| AAPL    | 2005  |   48.17166678|
-| AAPL    | 2006  |   72.04333369|
-| AAPL    | 2007  |  133.35333379|
-| AAPL    | 2008  |  138.48083242|
-| AAPL    | 2009  |  150.39333344|
+| :symbol | :year | :summary     |
+|---------|-------|--------------|
+| AAPL    | 2000  | 21.74833333  |
+| AAPL    | 2001  | 10.17583333  |
+| AAPL    | 2002  | 9.40833333   |
+| AAPL    | 2003  | 9.34750000   |
+| AAPL    | 2004  | 18.72333333  |
+| AAPL    | 2005  | 48.17166667  |
+| AAPL    | 2006  | 72.04333333  |
+| AAPL    | 2007  | 133.35333333 |
+| AAPL    | 2008  | 138.48083333 |
+| AAPL    | 2009  | 150.39333333 |
 
 TODO
 ----

deps.edn

@@ -1,3 +1,3 @@
 {:extra-paths ["data"]
  :deps {org.clojure/clojure              {:mvn/version "1.10.1"}
-        techascent/tech.ml.dataset       {:mvn/version "3.06"}}}
+        techascent/tech.ml.dataset       {:mvn/version "4.03"}}}

docs/index.Rmd

@@ -1291,7 +1291,7 @@ Additionally you may want to precalculate some values which will be visible for
 
 #### Select
 
-Select fourth row
+Select fifth row
 
 ```{clojure results="asis"}
 (api/select-rows DS 4)
@@ -4466,7 +4466,7 @@ Expression chaining using >
 (-> DS
     (api/group-by [:V4])
     (api/aggregate {:V1sum #(dfn/sum (% :V1))})
-    (api/select-rows #(> (:V1sum %) 5) ))
+    (api/select-rows #(>= (:V1sum %) 5)))
 ```
 
 ```{clojure results="asis"}