CHANGES.md

krangl Release History

v0.18

• Added support for arrow (Thanks to @Kopilov for contributing PR 150)
• Improved support for large Excels tables (Thanks to @ayvazj for contributing PR 126)
• Added second version of unfold() to work with property accessors instead

cars.unfold("cars", listOf(Car::brand, Car::ps))

Minor enhancements

• Fixed #63: Can not print schema() of empty data-frame

v0.17

Released 2021-07-17

• New Jupyter kernel integration with auto-import and improved rendering for DataFrame and DataFrame.schema()
• Added DataFrame.letsPlot() to ease integration with lets-plots
• New tutorial (jupyter notebook): Mammalian Sleep
• Updated to kotlin v1.5 and added supported for value class in List<Any>.toDataFrame() and DataFrame.unfold()
• Added timestamp support for database support API (fixes #124)

v0.16

Released 2021-04-13

krangl is now deployed to maven-central and no no longer ot jcenter

Features

• Added support for fixed-width files with readFixedWidth()
• Added supported for more compact column type specification when reading tsv
• Fixed: NA and emtpy cell handling in excel-reader
• Fixed: Use correct cell types when writing Excel file

v0.15.6

Republished to maven central https://search.maven.org/artifact/com.github.holgerbrandl.krangl/krangl

v0.15.2

• Fixed gather conversion in case of mixed number types
• Indicate guessed column type with prefix Any for basic types in schema and print

v0.15.1

• Fixed asDataFrame to include parent type properties
• Added DataFrame.filterNotNull to remove records will nulls. A column selector can be provided to check only a subset of columns.

v0.15

New Features

• #97 Added Excel read/write support (by LeandroC89)

// read
df = DataFrame.readExcel("data.xlsx", sheetName = "sales")
df = DataFrame.readExcel("data.xlsx", cellRange = CellRangeAddress.valueOf("A1:D10"))

// write
df.writeExcel("results.xslx")

• #95 Improved column type casts

dataFrameOf("foo")(1, 2, 3).addColumn("stringified_foo") { it["foo"].toStrings() }.schema()
> DataFrame with 3 observations
> foo              [Int]  1, 2, 3
> stringified_foo  [Str]  1, 2, 3

dataFrameOf("foo")("1", "2", "3").addColumn("parsed_foo") { it["foo"].toInts() }.schema()

> DataFrame with 3 observations
> foo         [Str]  1, 2, 3
> parsed_foo  [Int]  1, 2, 3

• #99 Added filtering by list (similar to R's %in% operator)

irisData.filter { it["Species"].inList("setosa", "versicolor")  }

Bug Fixes

• #84 Builder now supports mixed numbers in column
• #96 & #94 Fixed bugs in join
• #100 Improved SQL bindings
• #99 Fixed median

v0.14

• Fixed missing by values overhanging RHS in outer join (fixes #94)
• Added addRow (via PR92 by LeandroC89
• Added column type text to sql interface (fixes #72)

v0.13

Released: 2020-06-02

• Added column transformation to calculate cumulative sum cumSum

sales
    .sortedBy("quarter")
    .addColumn("cum_sales" to { it["sold_units"].cumSum()})

• Added column transformation pctChange to calculate percentage change between the current and a prior element. similar to pct_change in pandas (contributed by @amorphous1 in PR85)

sales
    .groupBy("product")
    .addColumn("sales_pct_change" to { it["sold_units"].pctChange() })

• Added lead and lag (contributed by @amorphous1 in PR85)

sales
    .groupBy("product")
    .sortedBy("quarter")
    .addColumn("prev_quarter_sales" to { it["sold_units"].lag() })

• Significantly improved join performance (contributed by @amorphous1 in PR85)

• New: Extended bindRows API to combine data rowwise (see PR #77 by @CrystalLord)

val person1 = mapOf("person" to "James", "year" to 1996)
val person2 = mapOf("person" to "Anne", "year" to 1998)

emptyDataFrame().bindRows(person1, person2).print()

v0.12

internal release

v0.11

• New: Added built-it support for Long columns (PR #69 by @davidpedrosa)

v0.10

Major:

• New: summarizeAt for simplified column aggregations
• New: setNames to replace column headers of a data-frame
• New: Deparse Iterables more conveniently using lambdas in deparseRecords

Minor:

• Fixed: Can not read csv-tables without header
• Added option to skip lines in csv reader.
• Fixed schema() should no throw memory exception (#53: )
• Fixed DataFrame.readTSV default format (#56)
• Added where() for conditional column creation (relates to #54)
• Added writeTSV
• Fixed grouping by Any columns
• Added: toDoubleMatrix() helper extension method

v0.9.1

Major Enhancements

• DataFrame.fromJson will now flatten nested json data

Minor

• Added sum() extension for columns summaries/transformation
• Added dataFrameOf() that accepts Iterable of names
• Added bindRows() alias that accepts data frames as varargs
• Added bindCols() extension for list of DataCol
• Fill missing cells with NA in bindRows and bindCols
• Resolve duplicated column names in bindCols()
• Added new builder to create data-frame from DataFrameRow iterator
• Added addRowNumber to add the row number as column to a data-frame
• Fixed: Incorrect types in gathered columns

v0.9

Released 2018-04-11

Major Enhancements

• Allow index access for column model (fixes #46): irisData[1][2]
• Improved DataFrame.count to respect existing groupings and to simply count rows if no grouping is defined
• Added moveLeft and moveRight to rearrange column order
• Added nest and unnest to wrap columns into sub-tables and back
• Added expand and complete to expand column value-sets into data-frames
• Added function literal support for count and groupBy (fixes #48): irisData.groupByExpr{ it["Sepal.Width"] > 3 }
• Added receiver context for sortBy lambdas with sorting specific API (fixes #44)

Improved data-frame rendering

• Improved print()ing of data-frames and schema()ta to have better alignment and more formatting options
• Print row numbers by default when using print (fixes #49)

Minor Enhancements

• Renamed select2/remove2 to selectIf and removeIF
• Fixed #39: Can not add scalar object as column
• Started submodule for documentation
• Hide columns in print after exceeding maximum line length (fixes #50)
• Fixed #45: sleepData.sortedBy{ "order" } should fail with informative exception

v0.8

Released 2018-03-21

Major Enhancements

• Added property unfolding df.unfold<Person("user", properties=listOf("address"))
• Added text matching helper: irisData.filter{ it["Species"].isMatching{ startsWith("se") }} (fixes #21)
• Added sortedByDescending and desc and added more sorting tests
• Added More elegant object bindings via reflection. Example val objPersons : Iterable<User> = users.rowsAs<User>() (fixes #22)
• Added compressed csv write support, configurable or by filename guessing

Minor Enhancements

• More robust row to object conversion
• Made List<Boolean?>.not() public
• Use regex instead of string as separate separator
• Replaced fixed temporary column names with uuids
• Fixed incorrect coercion of incomplete inplace data to df
• Added concat operator for string column arithmetics
• Fixed arithmetic comparison operators
• Added beakerx display adapter

v0.7

Released 2018-03-14

Major Enhancements

• Allow specifying column types when reading csv data (Thanks to LeanderG for providing the PR)
• Added groupedBy to provide distinct set of grouping tuples as data-frame
• Read support for URLs (Example DataFrame.readCSV("https://git.io/vxks7").glimpse())
• Added basic read/write support for JSON data
• Added generic collection conversion Iterable<Any>.asDataFrame() via reflection (fixes #24)

Incompatible API changes

• Renamed structure to columnTypes
• Renamed all table read function from .from* to .read*
• Fixed #29: mapNonNull should use parameter and not receiver

Minor Enhancements

• Namespace cleanup to hide internal helpers
• Bundled irisData
• Enhanced: DataCol.toDouble() should work for int columns as well (same vv)
• Added MIT License
• Use iterable instead of list for object conversions

v0.6

Released: 2017-11-11

• More idiomatic API mimicking kotlin stdlib where possible
• Added DataFrame.remove to drop columns from data-frames
• Added DataFrame.addColumn to add column from data-frames
• Added DataFrame.sortBy(TableFormula)
• Added DataFrame.filterByRow
• Reworked column selector API
• Changed column expression API from Any to a constrained set of support types
• Fixed issues when combining columns of different types (e.g. DoubleCol + IntCol
• Dropped most unary operators

v0.5

Skipped.

v0.4

released on 2017-4-12

New Features

• spread()-gather() support for elegant data reshaping (fixes #2)
• Improve reshaping functionality by adding unite and separate (fixes #9)
• Added sampleFrac() and sampleN() for random sub-sampling of data-frames (either with or without replacement)

Important Bug Fixes

• mutate() can now change existing columns without altering column positions

Other

• New property accessor DataFrame.cols to access all columns of a data-frame
• Incremented kotlin version to 1.1

v0.3

Initial Release

• Implement all dplyr core verbs
• Implement all join types
• Table write support using csv-commons wrapper
• Extensive unit test coverage =
• TravisCI integration
• Support for count() and distinct()
• Basic benchmarking framework (without jvm usage)