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Version 0.7.18

Features

  • Add byrow(allequal) as a special case of byrow(isequal). (This feature need at least Julia 1.8)

Fixes

  • Fix bug in stat routines - some corner cases
  • Fix unnecessary allocations in stat routins

Version 0.7.17

Fixes

  • Fix a performance issue in sort due to the recent change in Threads.@threads.
  • Fix the allocation problem in computing var and std in fast path of gatherby.
  • Fix an issue with Julia-latest.

Performance

  • Now we exploit multithreading during gathering observation for huge data sets.

Version 0.7.16

Fixes

  • Fix a problem that was causing tests fail in Julia 1.9
  • Fix an issue with eltype and the output of eachcol. Now eltype(::Type{<:DatasetColumns}) properly returns AbstractDatasetColumn instead of AbstractVector.
  • Fix a problem with nonmissingtype with Union{} output.
  • Fix an issue that was causing the join functions sort already-sorted data sets, issue #108
  • Remove precompilation for Julia 1.9 - it causes enormous amount of allocation in precompiling and loading

Features

  • Now IMD throws errors when accesses a grouped data set which its parent is modified.

Version 0.7.15

Fixes

  • Functions searchsorted, searchsortedfirst, and searchsortedlast now works with DatasetColumn
  • Fix a bug in byrow(nunique)

Version 0.7.14

Fixes

  • Fix a bug which caused stable=true being ignored in gatherby, issue #100

Documentation

  • Add docstring for groupby!, groupby, and gatherby.

Version 0.7.13

Fixes

  • Fix issue with QuickSortAlg in future version of Julia
  • Empty the rows of a SubDataset without columns
  • Fix a bug which causes modify/combine throw errors on columns with Vector{Vector} type

Version 0.7.12

Features

  • Users can use resize! to resize a data set

Fixes

  • Fix function signature for some stat functions

Version 0.7.11

Features

  • Update to PrettyTables version 2

Fixes

  • Fix a but in byrow for writing values of type BigInt
  • Update for Julia VERSION >= v"1.9.0-DEV.1635"
  • Fix a bug in modify which causes an error to show an error!
  • Fix a bug in sort which causes to treat Bool as a vector with length 1

Version 0.7.10

Fixes

  • topk and topkperm use isless by default for comparing values.
  • Fix a bug in show which causes ignoring format of a column when calculating the max width.
  • Better show for GroupBy/GatherBy in Jupyter
  • hcat! keeps the format of the second data set.
  • Fix an issue in show with HTML MIME, issue #91

Performance

  • Now Jupyter shows very wide data sets much faster, issue #82
  • Add precompilation for Julia > 1.8

Version 0.7.8

New features

  • The topk and topkperm functions supports two extra arguments: lt and by which by default are set as < and identity, respectively
  • topkperm is a new function for outputting the indices of top(bottom) k values issue #67.
  • topk now supports any DataType, see issue #67.
  • filter, filter!, delete and delete! have a new keyword argument for controlling how the missing values should be interpreted issue #69

Fixes

  • topk now works on DatasetColumn / SubDatasetColumn.

  • Stats functions throw ArgumentError when an empty vector is passed to them.

Performance

  • The topk and topkperm functions are multithreaded ready, i.e. users can pass threads = true to these functions.

    • Now we use binary search for large values of k. This improves the performance of the functions in the worst case scenarios.

  • row_join! allocates less when mapformats=true, thus, performs better. This directly affects filewriter performance in DLMReader.

  • Version 0.7.7

New features

  • A new functionality has been added to byrow for passing a Tuple of column indices. byrow(ds, fun, cols) calls fun.(ds[:, cols[1]], ds[:, cols[2]], ...) when cols is a NTuple of column indices.

Fixes

  • Fix type ambiguity in filter/!

Version 0.7.6

New features

  • Two new functions: delete and delete!. They should be compared to filter and filter!, respectively - issue #63
  • Add DLMReader to sysimage in IMD.create_sysimage.

Fixes

  • Fix mistakes in byrow(argmin) and byrow(argmax) - pull #62

Version 0.7.4 - 0.7.5

New features

  • byrow(ds, t::DataType, col) convert values of col to t.

Fixes

  • Fix an issue in flatten/! - columns with type Any.
  • Fix an issue with IMD.create_sysimage - issue #59
  • Improve eachgroup
  • Drop support of UInt16 in Characters - Characters now only supports length

Version 0.7.3

New features

  • Users now can choose between having the observations ids for the left data set and/or the right data set as part of the output data set.
  • Add a new function eachgroup. It allows iteration over each group of a grouped data set.
  • op is a new keyword argument for the update/! functions which allows passing a user defined function to control how the value of the main data set should be updated by the values from the transaction data set. (issue #55)
  • Supporting of the mapformats keyword argument in flatten/!. Now users can flatten a data set based on the formatted values. (issue #57)
  • Support of the threads keyword argument in flatten/!.

Fixes

  • The combine function will now work fine when a view of data set is passed
  • For the join functions the makeunique argument is now passed correctly to the inside functions.
  • update and update! have the same mode option by default.
  • Fix the problem with preserving format of SubDataset in flatten/!
  • Fix the problem that caused flatten! to produce a copy of data when an empty data set were passed to it.
  • Fix the bug in flatten! related to flatten the first column.
  • Fix the bug in flatten that caused Segmentation fault for view of data sets.

Performance

  • Faster flatten/!

Version 0.7.0

New features

  • The outerjoin function accepts the source keyword argument.
  • All join functions support obs_id option. This allows to output obs id for the matched pairs.
    • All join functions support obs_id_name for assigning column names for obs_id.
  • The leftjoin/!, innerjoin and outerjoin functions support multiple_match option. This indicates the rows in the left data set that has been repeated in the output data set due to multiple matches in the right data set.
    • All join functions support multiple_match_name for assigning the column name for multiple_match.
  • The compare function is updated to support more complex comparisons(issue #53).
    • [BREAKING] the on keyword argument in previous versions is equivalent to the cols keyword argument in version 0.7.0+.
    • The compare function can compare two data sets with different number of rows.
    • User can pass key columns to compare, via the on keyword argument, for matching observations before comparing.
    • Few keyword arguments are added to compare for supporting new functionalities.

Fixes

  • The maximum and minimum functions now work properly with String columns.