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Implement dask.dataframe.iterrows and dask.dataframe.itertuples#882

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Implement dask.dataframe.iterrows and dask.dataframe.itertuples#882
mrocklin merged 1 commit intodask:masterfrom
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@vikhyat vikhyat commented Dec 17, 2015

Implement dataframe.iterrows() and dataframe.itertuples() for iterating over each row of a Dask DataFrame, similar to the corresponding methods in pandas.DataFrame.

@vikhyat vikhyat force-pushed the master branch 2 times, most recently from c4ea8e6 to b01f560 Compare December 17, 2015 05:40
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Should these be removed?

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mrocklin commented Dec 17, 2015

This is an interesting problem. In the common case this should work great (and be really really useful).

In some cases however, when one output partition depends on many input partitions then this will trigger a lot of redundant computation.

I think that we should merge this but watch to see how it's used.

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Also, we may want to use the normal computation machinery. This will allow people to use other schedulers if they desire (for example to avoid threads) and will send the graph through the appropriate optimizations.

for i in range(self.npartitions):
    df = self.get_division(i).compute()
    for row in df.itertuples():
        ...

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This is somewhat important. We probably shouldn't use _default_get internally because it doesn't go through the normal optimization paths. The suggestion above should work well.

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Done.

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vikhyat commented Dec 17, 2015

I've updated the tests.

If we do want to avoid redundant computations, how would we go about doing that? Is it possible to represent the generator as the result of a dask graph or would we manually execute the graph and retain results that can be reused? I guess it would also lead to an increase in memory usage in some cases?

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mrocklin commented Dec 17, 2015

The tests look good to me. I don't think that there is a way to avoid redundant computations in the complex case. This is still very useful in the common case though, so I think that it still has a lot of value.

One approach to avoiding redundant computations would be to use the (experimental) opportunistic caching module.

Really though, I think that we shouldn't worry about this until someone runs into the issue. I was optimizing prematurely.

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mrocklin commented Dec 17, 2015

Do we want to extend this to Series and Index as well?

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jcrist commented Dec 17, 2015

There's also the to_bag method on dask.DataFrame and dask.Series objects, which converts the dataframe to a bag of tuples (with the index optional). For many cases I'd argue that this might be more useful, as map/reduce/filter/others-stuff can then be done in parallel.

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mrocklin commented Dec 17, 2015

I think that this implementatino of itertuples is particularly relevant because it's streaming

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vikhyat commented Dec 18, 2015

Pandas only implements this for DataFrame, so I'm not sure it makes sense to support this for Series and Index as well here.

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mrocklin commented Dec 18, 2015

Series has pd.Series.iteritems

@vikhyat vikhyat force-pushed the master branch 2 times, most recently from c276f86 to f00a1fa Compare December 21, 2015 08:27
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vikhyat commented Dec 21, 2015

I've updated this to not use _default_get and implement Series.iteritems().

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mrocklin commented Dec 21, 2015

Looks good to me. Merging.

mrocklin added a commit that referenced this pull request Dec 21, 2015
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Merge pull request #882 from vikhyat/master
495e92a 
Implement dask.dataframe.iterrows and dask.dataframe.itertuples
@mrocklin mrocklin merged commit 495e92a into dask:master Dec 21, 2015
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mrocklin commented Dec 21, 2015

Thanks @vikhyat !

@sinhrks sinhrks added this to the 0.7.6 milestone Jan 7, 2016
phofl added a commit to phofl/dask that referenced this pull request Dec 23, 2024
@fjetter @phofl
Parquet reader using Pyarrow FileSystem (dask#882)
ed5d051 
Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>
phofl added a commit to phofl/dask that referenced this pull request Dec 23, 2024
@phofl @hendrikmakait
@fjetter @milesgranger @jorisvandenbossche @rjzamora @charlesbluca @jrbourbeau @alex-rakowski @mrocklin @penguinpee @benrutter @guillaumeeb @TomAugspurger
Merge prep (#2)
428842f 
* Make column projections stricter (dask#881)

* Simplify again after lowering (dask#884)

* Visual EXPLAIN (dask#885)

* Fix merge predicate pushdowns with weird predicates (dask#888)

* Handle futures that are put into map_partitions (dask#892)

* Remove eager divisions from indexing (dask#891)

* Add shuffle if objects are not aligned and partitions are unknown in assign (dask#887)

Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Add support for dd.Aggregation (dask#893)

* Fix random_split for series (dask#894)

* Update dask version

* Use Aggregation from dask/dask (dask#895)

* Fix meta calculation error in groupby (dask#897)

* Revert "Use Aggregation from dask/dask" (dask#898)

* Parquet reader using Pyarrow FileSystem (dask#882)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Fix assign for empty indexer (dask#901)

* Add dask.dataframe import at start (dask#903)

* Add indicator support to merge (dask#902)

* Fix detection of parquet filter pushdown (dask#910)

* Speedup init of `ReadParquetPyarrowFS` (dask#909)

* Don't rely on sets in are_co_aligned (dask#908)

* Implement more efficient GroupBy.mean (dask#906)

* Refactor GroupByReduction (dask#920)

* Implement array inference in new_collection (dask#922)

* Add support for convert string option (dask#912)

* P2P shuffle drops partitioning column early (dask#899)

* Avoid culling for SetIndexBlockwise with divisions (dask#925)

* Re-run versioneer install to fix version number (tag_prefix) (dask#926)

* Sort if split_out=1 in value_counts (dask#924)

* Wrap fragments (dask#911)

* Ensure that columns are copied in projection (dask#927)

* Raise in map if pandas < 2.1 (dask#929)

* Add _repr_html_ and updated __repr__ for FrameBase (dask#930)

* Support token for map_partitions (dask#931)

* Fix Copy-on-Write related bug in groupby.transform (dask#933)

* Fix to_dask_dataframe test after switching to dask-expr by default (dask#935)

* Use multi-column assign in groupby apply (dask#934)

* Enable copy on write by default (dask#932)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Avoid fusing from_pandas ops to avoid duplicating data (dask#938)

* Adjust automatic split_out parameter (dask#940)

* Revert "Add _repr_html_ and updated __repr__ for FrameBase (dask#930)" (dask#941)

* Remove repartition from P2P shuffle (dask#942)

* [Parquet] Calculate divisions from statistics (dask#917)

* Accept user arguments for arrow_to_pandas (dask#936)

* Add _repr_html_ and prettier __repr__ w/o graph materialization (dask#943)

* Add dask tokenize for fragment wrapper (dask#948)

* Warn if annotations are ignored (dask#947)

* Require `pyarrow>=7` (dask#949)

* Implement string conversion for from_array (dask#950)

* Add dtype and columns type check for shuffle (dask#951)

* Concat arrow tables before converting to pandas (dask#928)

* MINOR: Avoid confusion around shuffle method (dask#956)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Set pa cpu count (dask#954)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Update for pandas nighlies (dask#953)

* Fix bug with split_out in groupby aggregate (dask#957)

* Fix default observed value (dask#960)

* Ensure that we respect shuffle in context manager (dask#958)

Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Fix 'Empty' prefix to non-empty Series repr (dask#963)

* Update README.md (dask#964)

* Adjust split_out values to be consistent with other methods (dask#961)

* bump version to 1.0

* Raise an error if the optimizer cannot terminate (dask#966)

* Fix non-converging optimizer (dask#967)

* Fixup filter pushdown through merges with ands and column reuse (dask#969)

* Fix unique with shuffle and strings (dask#971)

* Implement custom reductions (dask#970)

* Fixup set_index with one partition but more divisions by user (dask#972)

* Fixup predicate pushdown for query 19 (dask#973)

Co-authored-by: Miles <miles59923@gmail.com>

* Revert enabling pandas cow (dask#974)

* Update changelog for 1.0.2

* Fix set-index preserving divisions for presorted (dask#977)

* Fixup reduction with split_every=False (dask#978)

* Release for dask 2024.3.1

* Raise better error for repartition on divisions with unknown divisions (dask#980)

* Fix concat of series objects with column projection (dask#981)

* Fix some reset_index optimization issues (dask#982)

* Remove keys() (dask#983)

* Ensure wrapping an array when comparing to Series works if columns are empty (dask#984)

* Version v1.0.4

* Visual ANALYZE (dask#889)

Co-authored-by: fjetter <fjetter@users.noreply.github.com>

* Support ``prefix`` argument in  ``from_delayed`` (dask#991)

* Ensure drop matches column names exactly (dask#992)

* Fix SettingWithCopyWarning in _merge.py (dask#990)

* Update pyproject.toml (dask#994)

* Allow passing of boolean index for column index in loc (dask#995)

* Ensure that repr doesn't raise if an operand is a pandas object (dask#996)

* Version v1.0.5

* Reduce coverage target a little bit (dask#999)

* Nicer read_parquet prefix (dask#998)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Set divisions with divisions already known (dask#997)

* Start building and publishing conda nightlies (dask#986)

* Fix zero division error when reading index from parquet (dask#1000)

* Rename overloaded `to/from_dask_dataframe` API (dask#987)

* Register json and orc APIs for "pandas" dispatch (dask#1004)

* Fix pyarrow fs reads for list of directories (dask#1006)

* Release for dask 2024.4.0

* Fix meta caclulation in drop_duplicates (dask#1007)

* Release 1.0.7

* Support named aggregations in groupby.aggregate (dask#1009)

* Make release 1.0.9

* Adjust version number in changes

* Make setattr work (dask#1011)

* Release for dask 2024.4.1

* Fix head for npartitions=-1 and optimizer step (dask#1014)

* Deprecate ``to/from_dask_dataframe`` API (dask#1001)

* Fix projection for rename if projection isn't renamed (dask#1016)

* Fix unique with numeric columns (dask#1017)

* Add changes for new version

* Fix column projections in merge when suffixes are relevant (dask#1019)

* Simplify dtype casting logic for shuffle (dask#1012)

* Use implicit knowledge about divisions for efficient grouping (dask#946)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>
Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Fix assign after set index incorrect projections (dask#1020)

* Fix read_parquet if directory is empty (dask#1023)

* Rename uniuqe_partition_mapping property and add docs (dask#1022)

* Add docs for usefule optimizer methods (dask#1025)

* Fix doc build error (dask#1026)

* Fix error in analyze for scalar (dask#1027)

* Add nr of columns to explain output for projection (dask#1030)

Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Fuse more aggressively if parquet files are tiny (dask#1029)

* Move IO docstrings over (dask#1033)

* Release for dask 2024.4.2

* Add cudf support to ``to_datetime`` and ``_maybe_from_pandas`` (dask#1035)

* Fix backend dispatching for `read_csv` (dask#1028)

* Fix loc accessing index for element wise op (dask#1037)

* Fix loc slicing with Datetime Index (dask#1039)

* Fix shuffle after set_index from 1 partition df (dask#1040)

* Bugfix release

* Fix bug in ``Series`` reductions (dask#1041)

* Fix shape returning integer (dask#1043)

* Fix xarray integration with scalar columns (dask#1046)

* Fix None min/max statistics and missing statistics generally (dask#1045)

* Fix drop with set (dask#1047)

* Fix delayed in fusing with multipled dependencies (dask#1038)

* Add bugfix release

* Optimize when from-delayed is called (dask#1048)

* Fix default name conversion in `ToFrame` (dask#1044)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Add support for ``DataFrame.melt`` (dask#1049)

* Fixup failing test (dask#1052)

* Generalize ``get_dummies`` (dask#1053)

* reduce pickle size of parquet fragments (dask#1050)

* Add a bunch of docs (dask#1051)

Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Release for dask 2024.5.0

* Fix to_parquet in append mode (dask#1057)

* Fix sort_values for unordered categories (dask#1058)

* Fix dropna before merge (dask#1062)

* Fix non-integer divisions in FusedIO (dask#1063)

* Add cache  argument to ``lower_once`` (dask#1059)

* Use ensure_deterministic kwarg instead of config (dask#1064)

* Fix isin with strings (dask#1067)

* Fix isin for head computation (dask#1068)

* Fix read_csv with positional usecols (dask#1069)

* Release for dask 2024.5.1

* Use `is_categorical_dtype` dispatch for `sort_values` (dask#1070)

* Fix meta for string accessors (dask#1071)

* Fix projection to empty from_pandas (dask#1072)

* Release for dask 2024.5.2

* Fix categorize if columns are dropped (dask#1074)

* Fix resample divisions propagation (dask#1075)

* Release for dask 2024.6.0

* Fix get_group for multiple keys (dask#1080)

* Skip distributed tests (dask#1081)

* Fix cumulative aggregations for empty partitions (dask#1082)

* Move another test to distributed folder (dask#1085)

* Release 1.1.4

* Release for dask 2024.6.2

* Add minimal subset of interchange protocol (dask#1087)

* Add from_map docstring (dask#1088)

* Ensure 1 task group per from_delayed (dask#1084)

* Advise against using from_delayed (dask#1089)

* Refactor shuffle method to handle invalid columns (dask#1091)

* Fix freq behavior on  ci (dask#1092)

* Add first array draft (dask#1090)

* Fix array import stuff (dask#1094)

* Add asarray (dask#1095)

* Implement arange (dask#1097)

* Implement linspace (dask#1098)

* Implement zeros and ones (dask#1099)

* Remvoe pandas 2 checks (dask#1100)

* Add unify-chunks draft to arrays (dask#1101)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Release for dask 2024.7.0

* Skip test if optional xarray cannot be imported (dask#1104)

* Fix deepcopying FromPandas class (dask#1105)

* Fix from_pandas with chunksize and empty df (dask#1106)

* Link fix in readme (dask#1107)

* Fix shuffle blowing up the task graph (dask#1108)

Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Release for dask 2024.7.1

* Fix some things for pandas 3 (dask#1110)

* Fixup remaining upstream failures (dask#1111)

* Release for dask 2024.8.0

* Drop support for Python 3.9 (dask#1109)

Co-authored-by: James Bourbeau <jrbourbeau@gmail.com>

* Fix tuples as on argument in merge (dask#1117)

* Fix merging when index name in meta missmatches actual name (dask#1119)

Co-authored-by: Hendrik Makait <hendrik@makait.com>

* Register `read_parquet` and `read_csv` as "dispatchable" (dask#1114)

* Fix projection for Index class in read_parquet (dask#1120)

* Fix result index of merge (dask#1121)

* Introduce `ToBackend` expression (dask#1115)

* Avoid calling ``array`` attribute on ``cudf.Series`` (dask#1122)

* Make split_out for categorical default smarter (dask#1124)

* Release for dask 2024.8.1

* Fix scalar detection of columns coming from sql (dask#1125)

* Bump `pyarrow>=14.0.1` minimum versions (dask#1127)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Fix concat axis 1 bug in divisions (dask#1128)

* Release for dask 2024.8.2

* Use task-based rechunking as default (dask#1131)

* Improve performance of `DelayedsExpr` through caching (dask#1132)

* Import from tokenize (dask#1133)

* Release for dask 2024.9.0

* Add concatenate flag to .compute() (dask#1138)

* Release for dask 2024.9.1

* Fix displaying timestamp scalar (dask#1141)

* Fix alignment issue with groupby index accessors (dask#1142)

* Improve handling of optional dependencies in `analyze` and `explain` (dask#1146)

* Switch from mambaforge to miniforge in CI (dask#1147)

* Fix merge_asof for single partition (dask#1145)

* Raise exception when calculating divisons (dask#1149)

* Fix binary operations with scalar on the left (dask#1150)

* Explicitly list setuptools as a build dependency in conda recipe (dask#1151)

* Version v1.1.16

* Fix ``Merge`` divisions after filtering partitions (dask#1152)

* Fix meta calculation for to_datetime (dask#1153)

* Internal cleanup of P2P code (dask#1154)

* Migrate P2P shuffle and merge to TaskSpec (dask#1155)

* Improve Aggregation docstring explicitly mentionning SeriesGroupBy (dask#1156)

* Migrate shuffle and merge to `P2PBarrierTask` (dask#1157)

* Migrate Blockwise to use taskspec (dask#1159)

* Add support for Python 3.13 (dask#1160)

* Release for dask 2024.11.0

* Fix fusion calling things multiple times (dask#1161)

* Version 1.1.18

* Version 1.1.19

* Fix orphaned dependencies in Fused expression (dask#1163)

* Use Taskspec fuse implementation (dask#1162)

Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

* Introduce more caching when walking the expression (dask#1165)

* Avoid exponentially growing graph for Assign-Projection combinations (dask#1164)

* Remove ``from_dask_dataframe`` (dask#1167)

* Deprecated and remove from_legacy_dataframe usage (dask#1168)

Co-authored-by: James Bourbeau <jrbourbeau@users.noreply.github.com>

* Remove recursion in task spec (dask#1158)

* Fix value_counts with split_out != 1 (dask#1170)

* Release 2024.12.0

* Use new blockwise unpack collection in array (dask#1173)

* Propagate group_keys in DataFrameGroupBy (dask#1174)

* Fix assign optimization when overwriting columns (dask#1176)

* Remove custom read-csv stuff (dask#1178)

* Fixup install paths (dask#1179)

* Version 1.1.21

* Remove legacy conversion functions (dask#1177)

* Remove duplicated files

* Move repository

* Clean up docs and imports

* Clean up docs and imports

---------

Co-authored-by: Hendrik Makait <hendrik@makait.com>
Co-authored-by: Florian Jetter <fjetter@users.noreply.github.com>
Co-authored-by: Miles <miles59923@gmail.com>
Co-authored-by: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Co-authored-by: Richard (Rick) Zamora <rzamora217@gmail.com>
Co-authored-by: Charles Blackmon-Luca <20627856+charlesbluca@users.noreply.github.com>
Co-authored-by: James Bourbeau <jrbourbeau@gmail.com>
Co-authored-by: alex-rakowski <alexrakowski90@gmail.com>
Co-authored-by: Matthew Rocklin <mrocklin@gmail.com>
Co-authored-by: Sandro <shfu29r4bu@liamekaens.com>
Co-authored-by: Ben <55319792+benrutter@users.noreply.github.com>
Co-authored-by: James Bourbeau <jrbourbeau@users.noreply.github.com>
Co-authored-by: Guillaume Eynard-Bontemps <g.eynard.bontemps@gmail.com>
Co-authored-by: Tom Augspurger <tom.augspurger88@gmail.com>
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@vikhyat @mrocklin @jcrist @sinhrks