NEWS.md

DataFrames.jl v1.8.0 Release Notes

Ecosystem compatibility changes

• Make DataFrames.jl hashing consistent with Julia 1.13 and take into account column names when hashing AbstractDataFrame (#3507)
• Require Julia 1.10 and add PrettyTables.jl v3 support (#3510)

DataFrames.jl v1.7.1 Release Notes

Julia compatibility change

• Make DataFrames.jl support DataStructures.jl version 0.19 (#3503)

DataFrames.jl v1.7.0 Release Notes

New functionalities

• Allow passing multiple values to add in push!, pushfirst!, append!, and prepend! (#3372)
• rename and rename! now allow to apply a function transforming column names only to a subset of the columns specified by the cols keyword argument (#3380)
• mapcols and mapcols! now allow to apply a function transforming columns only to a subset of the columns specified by the cols keyword argument (#3386)

Bug fixes

• Correctly throw an error if negative number of rows is passed to first or last (#3402)
• Always use the default thread pool for multithreaded operations, instead of using the interactive thread pool when Julia was started with -tM,N with N > 0 (#3385)
• Correctly return Bool[] in the nonunique function applied to a data frame with a pulled column that has zero levels in the pool (#3393)
• Correctly index eachrow and eachcol with CartesianIndex (#3413)
• Correctly handle non-standard integers when converting them to BigInt (#3419)

Removed deprecations

• The by and aggregate functions that were deprecated before 1.0 release are now removed. (#3422)

Julia compatibility change

• Ensure that allunique(::AbstractDataFrame, ::Any) always gets interpreted as test for uniqueness of rows in the first positional argument (#3434)
• Make sure that an empty vector of Any or of AbstractVector is treated as having no columns when a data frame is being processed with combine/select/transform. (#3435)

DataFrames.jl v1.6.1 Release Notes

Bug fixes

• Fix error in specification of dependency on DataStructures.jl (#3359)

Minor improvements

• Improved error messages in only, and push!, append! and related functions (#3356, #3357)

DataFrames.jl v1.6 Release Notes

Breaking changes

• Objects inheriting from Tables.AbstractRow are now treated in the same way as DataFrameRow by select/transform/combine functions. In previous versions they were treated as a scalar, but this was inconsistent with the intention of Tables.AbstractRow definition (#3348)

New functionalities

• Add Iterators.partition support for DataFrameRows (#3299)
• Add support for renamecols keyword argument in crossjoin (#3314)
• DataFrameRows and DataFrameColumns now support nrow, ncol, and Tables.subset (#3311)
• Not allows passing multiple positional arguments that are treated as if they were wrapped in Cols and does not throw an error when a vector of duplicate indices is passed when doing column selection (#3302)
• Added the kwarg checkunique to sorting related functions (issorted, sort, sort! and sortperm) that throws an error when duplicate elements make multiple sort orders valid (#3312)
• reduce performing vcat on a collection of data frames now accepts init keyword argument (#3310)
• Allow to pass column names in DataFrame constructor that replace the names generated by default (#3320)
• describe now has :sum available as a descriptive statistic. (#3303)

Bug fixes

• deleteat! correctly handles the situation when vector of rows to be dropped from a data frame is its column or might alias with some of its columns (#3304)

DataFrames.jl v1.5 Release Notes

New functionalities

• Add Iterators.partition support (#3212)
• Add allunique and allow transformations in cols argument of describe and nonunique when working with SubDataFrame (3232)
• Add support for Tables.AbstractRow for push!, pushfirst!, and insert! (#3245)
• Add support for operator keyword argument in Cols to take a set operation to apply to passed selectors (union by default) (3224)
• Allow to pass multiple predicates in Cols and mix them with other selectors (3279)
• Improve support for setting group order in groupby (3253)
• Joining functions now support order keyword argument allowing the user to specify the order of the rows in the produced table (#3233)
• Add keep keyword argument to nonunique, unique, and unique! allowing to specify which duplicate rows should be kept (#3260)
• Add haskey and get methods to DataFrameColumns to make it support dictionary interface more completely (#3282)
• Allow passing scalar keyword argument in flatten (#3283)

Bug fixes

• passing very many data frames to innerjoin and outerjoin does not lead to stack overflow (#3233)
• fixed incorrect handling of passing no conditions in subset and subset! (#3264)
• fixed error in fast aggregation in sum and mean of columns only having missing values (#3268)
• fixed error in indexing of SubDataFrame that has no columns selected from its parent (#3273)

Performance improvements

• dropmissing creates new columns in a single pass if disallowmissing=true (#3256)

DataFrames.jl v1.4.4 Patch Release Notes

Bug fixes

• Fix bug in select and transform with copycols=false on SubDataFrame that incorrectly allowed passing transformations (#3231)

DataFrames.jl v1.4.3 Patch Release Notes

Bug fixes

• Fix incorrect handling of column metadata in insertcols! and insertcols (#3220)
• Correctly handle GroupedDataFrame with no groups in multi-column operation specification syntax (#3122)

Display improvements

• Improve printing of grouping keys when displaying GroupedDataFrame (#3213)

Integration changes

• Support updates of metadata API introduced in DataAPI.jl 1.13.0 (3216)

DataFrames.jl v1.4.2 Patch Release Notes

Bug fixes

• Make sure flatten works correctly on a data frame with zero rows (#3198)

DataFrames.jl v1.4.1 Patch Release Notes

Bug fixes

• Make sure we always copy the indexing value when calling getindex on DataFrameRows object (#3192)

DataFrames.jl v1.4 Release Notes

Julia compatibility change

• DataFrames.jl 1.4 requires Julia 1.6 (#3145)

New functionalities

• subset and subset! now allow passing zero column selectors (#3025)
• subset and subset! processing GroupedDataFrame allow using a scalar as a subsetting condition (this will result in including/excluding a whole group); for AbstractDataFrame processing only AbstractVector subsetting condition is allowed as accepting scalars can lead to hard to catch bugs in users' code (#3032)
• permutedims now supports a strict keyword argument that allows for a more flexible handling of values stored in a column that will become a new header (#3004)
• unstack now allows passing a function in combine keyword argument; this allows for a convenient creation of two dimensional pivot tables (#2998, #3185)
• filter for GroupedDataFrame now accepts ungroup keyword argument (#3021)
• Add special syntax for eachindex, groupindices, and proprow to transformation mini-language (#3001).
• Add support for reverse!, permute!, invpermute!, shuffle, and shuffle! functions. Improve functionality of reverse. (#3010).
• first and last for GroupedDataFrame now support passing number of elements to get (#3006)
• Add insertcols, which is a version of insertcols! that creates a new data frame (#3020)
• Add fillcombinations function that generates all combinations of levels of selected columns of a data frame (#3012)
• Guarantee that permute! and invpermute! throw on invalid input (#3035)
• Add allcombinations function that returns a data frame created from all combinations of the passed vectors (#3031)
• Add resize!, keepat!, pop!, popfirst!, and popat!, make deleteat! signature more precise (#3047)
• Add pushfirst! and insert! (#3072)
• New threads argument allows disabling multithreading in combine, select, select!, transform, transform!, subset and subset! (#3030)
• Add support for table-level and column-level metadata using DataAPI.jl interface (#3055)
• completecases and nonunique no longer throw an error when data frame with no columns is passed (#3055)
• describe now accepts two predefined arguments: :nnonmissing and :nuniqueall (#3146)

Previously announced breaking changes

• On Julia 1.7 or newer broadcasting assignment into an existing column of a data frame replaces it. Under Julia 1.6 or older it is an in place operation. (#3022)

Deprecations

• allowduplicates keyword argument in unstack is deprecated, combine keyword argument should be used instead (#3185)

Internal changes

• DataFrame is now a mutable struct and has three new fields metadata, colmetadata, and allnotemetadata; this change makes DataFrame objects serialized under earlier versions of DataFrames.jl incompatible with version 1.4 (#3055)

Bug fixes

• fix dispatch ambiguity in rename and rename! when only source data frame is passed (#3055)
• Make sure that AsTable accepts only valid argument (#3064)
• Make sure we avoid aliasing when repeating the same column in select[!] and transform[!] on GroupedDataFrame (#3070)
• Make vcat correctly handle cols keyword argument if only data frames having no columns are passed (#3081)
• Make subset preserves group ordering when ungroup=false like subset! already does (#3094)
• Fix incorrect behavior of GroupDataFrame indexing in corner cases (#3179)
• Fix errors in insertcols! when no columns to add are passed (#3179)
• Fix errors in minimum and maximum aggregates when processing GroupedDataFrame with combine in corner cases (#3179)

Performance

• Speed up permute! and invpermute! (and therefore sorting) 2x-8x for large tables by using cycle notation (#3035)
• Make one-dimensional multi-element indexing of DataFrameRows return DataFrameRows (#3037)
• Make transform! on SubDataFrame faster (#3070)

Integration changes

• Support Tables.subset and move ByRow definition to Tables.jl (#3158)

DataFrames.jl v1.3.6 Patch Release Notes

Bug fixes

• Fix overly restrictive type assertion in filter and filter! (#3155)

DataFrames.jl v1.3.5 Patch Release Notes

Integration change

• Allow version 4 of Compat.jl

DataFrames.jl v1.3.4 Patch Release Notes

Bug fixes

• Fix handling of variable_eltype in stack (#3043)

DataFrames.jl v1.3.3 Patch Release Notes

Bug fixes

• Fix handling of matchmissing keyword argument in joins (#3040)

DataFrames.jl v1.3.2 Patch Release Notes

Bug fixes

• Make sure that select!/transform! and select/transform (with copycols=false) do not produce aliases of the same source column consistently (currently only transform[!] ensured it for an unwrapped column renaming operation) (#2983)
• Fix aliasing detection in sort! (now only identical columns passing === test are considered aliases) (#2981)
• Make sure ByRow calls wrapped function exactly once for each element in all cases (#2982)

DataFrames.jl v1.3.1 Patch Release Notes

Bug fixes

• Fix getindex that incorrectly allowed vectors of Pairs (#2970)

DataFrames.jl v1.3 Release Notes

New functionalities

• Improve sort keyword argument in groupby (#2812).

  In the groupby function the sort keyword argument now allows three values:

  • nothing (the default) leaves the order of groups undefined and allows groupby to pick the fastest available grouping algorithm;
  • true sorts groups by key columns;
  • false creates groups in the order of their appearance in the parent data frame;

  In previous versions, the sort keyword argument allowed only Bool values and false (which was the default) corresponded to the new behavior when nothing is passed. Therefore only the user visible change affecting existing code is when sort=false is passed explicitly. The order of groups was undefined in that case, but in practice groups were already created in their order of appearance, except when grouping columns implemented the DataAPI.refpool API (notably PooledArray and CategoricalArray) or when they contained only integers in a small range. (#2812)

• the unstack function receives new keyword argument fill (with missing default) that is used to fill combinations of not encountered rows and columns. This feature allows to distinguish between missings in value column and just missing row/column combinations and to easily fill with zeros non existing combinations in case of counting. (#2828)

• Allow adding new columns to a SubDataFrame created with : as column selector (#2794).

  If sdf is a SubDataFrame created with : as a column selector then insertcols!, setindex!, and broadcasted assignment allow for creation of new columns, automatically filling filtered-out rows with missing values;

• Allow replacing existing columns in a SubDataFrame with ! as row selector in assignment and broadcasted assignment (#2794).

  Assignment to existing columns allocates a new column. Values already stored in filtered-out rows are copied.

• Allow SubDataFrame to be passed as an argument to select! and transform! (also on GroupedDataFrame created from a SubDataFrame) (#2794).

  Assignment to existing columns allocates a new column. Values already stored in filtered-out rows are copied. In case of creation of new columns, filtered-out rows are automatically filled with missing values. If SubDataFrame was not created with : as column selector the resulting operation must produce the same column names as stored in the source SubDataFrame or an error is thrown.

• Tables.materializer when passed the following types or their subtypes: AbstractDataFrame, DataFrameRows, DataFrameColumns returns DataFrame. (#2839)

• the insertcols! function receives new keyword argument after (with false default) that specifies if columns should be inserted after or before col. (#2829)

• Added support for deleteat! (#2854)

• leftjoin! performing a left join of two data frame objects by updating the left data frame with the joined columns from right data frame. (#2843)

• the DataFrame constructor when column names are passed to it as a second argument now determines if a passed vector of column names is valid based on its contents and not element type (#2859)

• the DataFrame constructor when matrix is passed to it as a first argument now allows copycols keyword argument (#2859)

• Cols now accepts a predicate accepting column names as strings. (#2881)

• In source => transformation => destination transformation specification minilanguage now destination can be also a Function generating target column names and taking column names specified by source as an argument. (#2897)

• subset and subset! now allow passing multiple column selectors and vectors or matrices of Pairs as specifications of selection conditions (#2926)

• When using broadcasting in source .=> transformation .=> destination transformation specification minilanguage now All, Cols, Between, and Not selectors when used as source or destination are properly expanded to selected column names within the call data frame scope. (#2918)

• describe now accepts :detailed as the stats argument to compute standard deviation and quartiles in addition to statistics that are reported by default. (#2459)

• sort! now supports general AbstractDataFrame (#2946)

• filter now supports view keyword argument (#2951)

Bug fixes

• fix a problem with unstack on empty data frame (#2842)
• fix a problem with not specialized Pair arguments passed as transformations (#2889)
• sorting related functions now more carefully check passed arguments for correctness. Now all keyword arguments are correctly checked to be either scalars of vectors of scalars. (#2946)

Performance improvements

• for selected common transformation specifications like e.g. AsTable(...) => ByRow(sum) use a custom implementations that lead to lower compilation latency and faster computation (#2869), (#2919)

Deprecations

• delete! is deprecated in favor of deleteat! (#2854)
• In sort, sort!, issorted and sortperm it is now documented that the result of passing an empty column selector uses lexicographic ordering of all columns, but this behavior is deprecated. (#2941)

Planned changes

• In DataFrames.jl 1.4 release on Julia 1.7 or newer broadcasting assignment into an existing column of a data frame will replace it. Under Julia 1.6 or older it will be an in place operation. (#2937

DataFrames.jl v1.2.2 Patch Release Notes

Bug fixes

• fix a bug in crossjoin if the first argument is SubDataFrame and makeunique=true (#2826)

DataFrames.jl v1.2.1 Patch Release Notes

Bug fixes

• Add workaround for deleteat! bug in Julia Base in delete! function (#2820)

DataFrames.jl v1.2 Release Notes

New functionalities

• add option matchmissing=:notequal in joins; in leftjoin, semijoin and antijoin missings are dropped in right data frame, but preserved in left; in rightjoin missings are dropped in left data frame, but preserved in right; in innerjoin missings are dropped in both data frames; in outerjoin this value of keyword argument is not supported (#2724)
• correctly handle selectors of the form :col => AsTable and :col => cols by expanding a single column into multiple columns (#2780)
• if subset! is passed a GroupedDataFrame the grouping in the passed object gets updated to reflect rows removed from the parent data frame (#2809)

Bug fixes

• fix bug in how groupby handles grouping of float columns; now -0.0 is treated as not integer when deciding on which grouping algorithm should be used (#2791)
• fix bug in how issorted handles custom orderings and improve performance of sorting when complex custom orderings are passed (#2746)
• fix bug in combine, select, select!, transform, and transform! that incorrectly disallowed matrices of Pairs in GroupedDataFrame processing (#2782)
• fix location of summary in text/html output (#2801)

Performance improvements

• SubDataFrame, filter!, unique!, getindex, delete!, leftjoin, rightjoin, and outerjoin are now more efficient if rows selected in internal operations form a continuous block (#2727, #2769)

Deprecated

• hcat of a data frame with a vector is now deprecated to allow consistent handling of horizontal concatenation of data frame with Tables.jl tables in the future (#2777)

Other changes

• text/plain rendering of columns containing complex numbers is now improved (#2756)
• in text/html display of a data frame show full type information when hovering over the shortened type with a mouse (#2774)

DataFrames.jl v1.1.1 Patch Release Notes

Performance improvements

• fix performance issue when aggregation function produces multiple rows in split-apply-combine (2749)
• completecases is now optimized and only processes columns that can contain missing values; additionally it is now type stable and always returns a BitVector (#2726)
• fix performance bottleneck when displaying wide tables (#2750)

DataFrames.jl v1.1 Release Notes

Functionality changes

• make sure subset checks if the passed condition function returns a vector of values (in the 1.0 release also returning scalar true, false, or missing was allowed which was unintended and error prone) (#2744)

DataFrames.jl v1.0.2 Patch Release Notes

Performance improvements

• fix of performance issue of groupby when using multi-threading (#2736)
• fix of performance issue of groupby when using PooledVector (2733)

DataFrames.jl v1.0 Release Notes

Breaking changes

• No breaking changes are planned for v1.0 release

Bug fixes

• DataFrames.jl now checks that passed columns are 1-based as this is a current design assumption (#2594)
• mapcols! makes sure not to create columns being AbstractRange consistently with other methods that add columns to a DataFrame (#2594)
• transform and transform! always copy columns when column renaming transformation is passed. If similar issues are identified after 1.0 release (i.e. that a copy of data is not made in scenarios where it normally should be made these will be considered bugs and fixed as non-breaking changes) (#2721)

New functionalities

• firstindex, lastindex, size, ndims, and axes are now consistently defined and documented in the manual for AbstractDataFrame, DataFrameRow, DataFrameRows, DataFrameColumns, GroupedDataFrame, GroupKeys, and GroupKey (#2573)
• add subset and subset! functions that allow to subset rows (#2496)
• names now allows passing a predicate as a column selector (#2417)
• vcat now allows a source keyword argument that specifies the additional column to be added in the last position in the resulting data frame that will identify the source data frame. (#2649)
• GroupKey and DataFrameRow are consistently behaving like NamedTuple in comparisons and they now implement: hash, ==, isequal, <, isless (#2669])
• since Julia 1.7 using broadcasting assignment on a DataFrame column selected as a property (e.g. df.col .= 1) is allowed when column does not exist and it allocates a fresh column (#2655)
• delete! now correctly handles the case when columns of a data frame are aliased (#2690)

Deprecated

• in leftjoin, rightjoin, and outerjoin the indicator keyword argument is deprecated in favor of source keyword argument; indicator will be removed in 2.0 release (2649)
• Using broadcasting assignment on a SubDataFrames column selected as a property (e.g. sdf.col .= 1) is deprecated; it will be disallowed in the future. (#2655)
• Broadcasting assignment to an existing column of a DataFrame selected as a property (e.g. df.col .= 1) being an in-place operation is deprecated. It will allocate a fresh column in the future (#2655)
• all deprecations present in 0.22 release now throw an error (#2554); in particular convert methods, map on GroupedDataFrame that were deprecated in 0.22.6 release now throw an error (#2679)

Other relevant changes

• innerjoin, leftjoin, rightjoin, outerjoin, semijoin, and antijoin are now much faster and check if passed data frames are sorted by the on columns and take into account if shorter data frame that is joined has unique values in on columns. These aspects of input data frames might affect the order of rows produced in the output (#2612, #2622)
• DataFrame constructor, copy, getindex, select, select!, transform, transform!, combine, sort, and join functions now use multiple threads in selected operations (#2647, #2588, #2574, #2664)

DataFrames.jl v0.22.7 Release notes

• convert methods from AbstractDataFrame, DataFrameRow and GroupKey to Array, Matrix, Vector and Tuple, as well as from AbstractDict to DataFrame, are now deprecated: use corresponding constructors instead. The only conversions that are retained are convert(::Type{NamedTuple}, dfr::DataFrameRow), convert(::Type{NamedTuple}, key::GroupKey), and convert(::Type{DataFrame}, sdf::SubDataFrame); the deprecated methods will be removed in 1.0 release
• as a bug fix eltype of vector returned by eachrow is now DataFrameRow (#2662)
• applying map to GroupedDataFrame is now deprecated. It will be an error in 1.0 release. (#2662)
• copycols keyword argument is now respected when building a DataFrame from Tables.CopiedColumns (#2656)

DataFrames.jl v0.22 Release Notes

Breaking changes

• the rules for transformations passed to select/select!, transform/transform!, and combine have been made more flexible; in particular now it is allowed to return multiple columns from a transformation function (#2461 and #2481)
• CategoricalArrays.jl is no longer reexported: call using CategoricalArrays to use it #2404. In the same vein, the categorical and categorical! functions have been deprecated in favor of transform(df, cols .=> categorical .=> cols) and similar syntaxes #2394. stack now creates a PooledVector{String} variable column rather than a CategoricalVector{String} column by default; pass variable_eltype=CategoricalValue{String} to get the previous behavior (#2391)
• isless for DataFrameRows now checks column names (#2292)
• DataFrameColumns is now not a subtype of AbstractVector (#2291)
• nunique is not reported now by describe by default (#2339)
• stop reordering columns of the parent in transform and transform!; always generate columns that were specified to be computed even for GroupedDataFrame with zero rows (#2324)
• improve the rule for automatically generated column names in combine/select(!)/transform(!) with composed functions (#2274)
• :nmissing in describe now produces 0 if the column does not allow missing values; earlier nothing was produced in this case (#2360)
• fast aggregation functions in for GroupedDataFrame now correctly choose the fast path only when it is safe; this resolves inconsistencies with what the same functions not using fast path produce (#2357)
• joins now return PooledVector not CategoricalVector in indicator column (#2505)
• GroupKeys now supports in for GroupKey, Tuple, NamedTuple and dictionaries (2392)
• in describe the specification of custom aggregation is now function => name; old name => function order is now deprecated (#2401)
• in joins passing NaN or real or imaginary -0.0 in on column now throws an error; passing missing throws an error unless matchmissing=:equal keyword argument is passed (#2504)
• unstack now produces row and column keys in the order of their first appearance and has two new keyword arguments allowmissing and allowduplicates (#2494)
• PrettyTables.jl is now the default back-end to print DataFrames to text/plain; the print option splitcols was removed and the output format was changed (#2429)

New functionalities

• add filter to GroupedDataFrame (#2279)
• add empty and empty! function for DataFrame that remove all rows from it, but keep columns (#2262)
• make indicator keyword argument in joins allow passing a string (#2284, #2296)
• add new functions to GroupKey API to make it more consistent with DataFrameRow (#2308)
• allow column renaming in joins (#2313 and (#2398)
• add rownumber to DataFrameRow (#2356)
• allow passing column name to specify the position where a new columns should be inserted in insertcols! (#2365)
• allow GroupedDataFrames to be indexed using a dictionary, which can use Symbol or string keys and are not dependent on the order of keys. (#2281)
• add isapprox method to check for approximate equality between two dataframes (#2373)
• add columnindex for DataFrameRow (#2380)
• names now accepts Type as a column selector (#2400)
• select, select!, transform, transform! and combine now allow renamecols keyword argument that makes it possible to avoid adding transformation function name as a suffix in automatically generated column names (#2397)
• filter, sort, dropmissing, and unique now support a view keyword argument which if set to true makes them return a SubDataFrame view into the passed data frame.
• add only method for AbstractDataFrame (#2449)
• passing empty sets of columns in filter/filter! and in select/transform/combine with ByRow is now accepted (#2476)
• add permutedims method for AbstractDataFrame (#2447)
• add support for Cols from DataAPI.jl (#2495)
• add reverse function for AbstractDataFrame that reverses the rows (#2944)

Deprecated

• DataFrame! is now deprecated (#2338)
• several in-standard DataFrame constructors are now deprecated (#2464)
• all old deprecations now throw an error (#2350)

Dependency changes

• Tables.jl version 1.2 is now required.
• DataAPI.jl version 1.4 is now required. It implies that All(args...) is deprecated and Cols(args...) is recommended instead. All() is still supported.

Other relevant changes

• Documentation is now available also in Dark mode (#2315)
• add rich display support for Markdown cell entries in HTML and LaTeX (#2346)
• limit the maximal display width the output can use in text/plain before being truncated (in the textwidth sense, excluding …) to 32 per column by default and fix a corner case when no columns are printed in situations when they are too wide (#2403)
• Common methods are now precompiled to improve responsiveness the first time a method is called in a Julia session. Precompilation takes up to 30 seconds after installing the package (#2456).