dataframe
A fast, safe, and intuitive DataFrame library.
파일 탐색기
최종 버전 다운로드 (.zip)- bug_report.md
- feature_request.md
- ci-windows-macos.yml
- ci.yml
- haskell-ci.yml
- presubmit.yml
- Benchmark.hs
- LazyBenchmark.hs
- Main.hs
- README.md
- Synthesis.hs
- explorer_benchmark.exs
- group_by.exs
- mix.exs
- group_by.py
- pandas_benchmark.py
- group_by.py
- polars_benchmark.py
- Main.hs
- arrow_abi.h
- blobs.csv
- golden.json
- iris.csv
- iris_binary.csv
- regression.csv
- part-0.parquet
- part-1.parquet
- test.csv
- train.csv
- arbuthnot.csv
- chinook.db
- chipotle.tsv
- city.csv
- confectionary.jsonl
- effects-of-covid-19-on-trade-at-15-december-2021-provisional.csv
- employees.csv
- housing.csv
- iris.parquet
- measurements.txt
- mtcars.parquet
- present.csv
- starwars.csv
- station.csv
- titanic.csv
- arrow_abi.h
- dataframe_arrow.h
- rts_init.c
- FFI.hs
- dataframe-arrow.cabal
- Freeze.hs
- Generic.hs
- Record.hs
- Schema.hs
- Types.hs
- Util.hs
- Core.hs
- Colours.hs
- PrettyPrint.hs
- AggKernel.hs
- AggKernelDirect.hs
- AggKernelPar.hs
- AggPlan.hs
- Column.hs
- ColumnBuilder.hs
- ColumnMerge.hs
- DataFrame.hs
- DictEncode.hs
- Expression.hs
- Grouping.hs
- GroupingDirect.hs
- GroupingPar.hs
- Hash.hs
- HashTable.hs
- Interpreter.hs
- Nullable.hs
- PackedText.hs
- ParRadixSort.hs
- Pretty.hs
- RadixRank.hs
- Row.hs
- RowHash.hs
- Simplify.hs
- Types.hs
- Utf8.hs
- Errors.hs
- Operators.hs
- dataframe-core.cabal
- LICENSE
- Infer.hs
- Options.hs
- Read.hs
- Scanner.hs
- Sink.hs
- CSV.hs
- CSV.hs
- MutableColumn.hs
- dataframe-csv.cabal
- LICENSE
- CSV.hs
- CSV.hs
- dataframe-csv-th.cabal
- LICENSE
- Serialize.hs
- ExprJson.hs
- dataframe-expr-serializer.cabal
- LICENSE
- process_csv.c
- process_csv.h
- Columns.hs
- Core.hs
- Index.hs
- IndexPar.hs
- Parallel.hs
- Passes.hs
- Slice.hs
- TextMerge.hs
- Workers.hs
- Fast.hs
- all_empty_row.csv
- comma_in_quotes.csv
- crlf.csv
- crlf.tsv
- either_read_mixed.csv
- empty_file.csv
- empty_values.csv
- escaped_quotes.csv
- extra_fields.csv
- header_only.csv
- json_data.csv
- missing_fields.csv
- newlines.csv
- no_trailing_newline.csv
- quotes_and_newlines.csv
- simple.csv
- simple.tsv
- single_col.csv
- temp_escaped_quotes.csv
- temp_json_data.csv
- temp_quotes_and_newlines.csv
- trailing_blank_line.csv
- utf8.csv
- utf8_bom.csv
- whitespace_fields.csv
- ChunkParallel.hs
- Projection.hs
- ReadCsv.hs
- TypedExtraction.hs
- Csv.hs
- Main.hs
- dataframe-fastcsv.cabal
- LICENSE
- dfusion_bridge.h
- lib.rs
- Cargo.toml
- FFI.hs
- Plan.hs
- Typed.hs
- Main.hs
- dataframe-fusion.cabal
- Setup.hs
- Hasktorch.hs
- Main.hs
- CHANGELOG.md
- dataframe-hasktorch.cabal
- LICENSE
- HuggingFace.hs
- Main.hs
- dataframe-huggingface.cabal
- LICENSE
- JSON.hs
- dataframe-json.cabal
- LICENSE
- DataFrame.hs
- Executor.hs
- LogicalPlan.hs
- Optimizer.hs
- PhysicalPlan.hs
- Binary.hs
- CSV.hs
- Lazy.hs
- Lazy.hs
- dataframe-lazy.cabal
- LICENSE
- AdaBoost.hs
- GBM.hs
- Model.hs
- Regression.hs
- Logistic.hs
- Regression.hs
- Report.hs
- Kernel.hs
- RFF.hs
- Serialize.hs
- Boosting.hs
- DBSCAN.hs
- DecisionTree.hs
- GMM.hs
- KMeans.hs
- Learn.hs
- LinearModel.hs
- Metrics.hs
- Model.hs
- ModelSelection.hs
- PCA.hs
- Segmented.hs
- SVM.hs
- SymbolicRegression.hs
- Synthesis.hs
- Transform.hs
- Cart.hs
- Categorical.hs
- CondVec.hs
- Fit.hs
- Linear.hs
- Numeric.hs
- Pool.hs
- Predict.hs
- Prune.hs
- Tao.hs
- Types.hs
- Internal.hs
- Eigen.hs
- Solve.hs
- Loss.hs
- Expr.hs
- GP.hs
- Optimize.hs
- Simplify.hs
- LinearAlgebra.hs
- LinearSolver.hs
- Random.hs
- EdgeCases.hs
- NumericalRigor.hs
- Numerics.hs
- Symbolic.hs
- Simplify.hs
- Cart.hs
- DataFrameApi.hs
- DecisionTree.hs
- LinearSolver.hs
- Main.hs
- TreePruning.hs
- Worklist.hs
- dataframe-learn.cabal
- LICENSE
- README.md
- AggregateScatter.hs
- Aggregation.hs
- Core.hs
- Inference.hs
- Join.hs
- JoinPar.hs
- Merge.hs
- Permutation.hs
- SetOps.hs
- Statistics.hs
- Subset.hs
- Transformations.hs
- Typing.hs
- Extra.hs
- Access.hs
- Aggregate.hs
- Apply.hs
- Expr.hs
- Join.hs
- Operations.hs
- Sampling.hs
- Statistics.hs
- Functions.hs
- Monad.hs
- Statistics.hs
- dataframe-operations.cabal
- LICENSE
- Binary.hs
- Decompress.hs
- Dictionary.hs
- Encoding.hs
- Levels.hs
- Page.hs
- Schema.hs
- Seeking.hs
- Thrift.hs
- Time.hs
- Utils.hs
- RandomAccess.hs
- Parquet.hs
- Parquet.hs
- dataframe-parquet.cabal
- LICENSE
- Parquet.hs
- Parquet.hs
- dataframe-parquet-th.cabal
- LICENSE
- FieldParsers.hs
- Schema.hs
- Schema.hs
- Common.hs
- Double.hs
- Int.hs
- Token.hs
- Fast.hs
- Binary.hs
- Parsing.hs
- FastParsing.hs
- FastParsing.hs
- Main.hs
- dataframe-parsing.cabal
- LICENSE
- chinook.db
- base_readme.md
- pg-setup.sh
- pg-teardown.sh
- Columns.hs
- Sqlite.hs
- Common.hs
- Introspect.hs
- Read.hs
- Schema.hs
- TH.hs
- Persistent.hs
- Main.hs
- PersistentTests.hs
- SchemaTHTests.hs
- CHANGELOG.md
- dataframe-persistent.cabal
- LICENSE
- README.md
- TH.hs
- Records.hs
- Records.hs
- dataframe-th.cabal
- LICENSE
- base_readme.md
- Common.hs
- VegaLite.hs
- Plot.hs
- Typed.hs
- Chart.hs
- Plot.hs
- Display.hs
- dataframe-viz.cabal
- LICENSE
- README.md
- aggregation.png
- derive_many.png
- derive_simple.png
- filter_autocomplete.png
- filter_declare.png
- filter_no_declare.png
- filter_wrong_type.png
- first_ten_rows.png
- haskell-logo.svg
- lift_custom_function.png
- opening_screen.png
- plot.png
- select_columns.png
- theme_overrides.css
- haskell_for_data_analysis.md
- base_exploratory_data_analysis_primer.md
- base_readme.md
- California Housing.ipynb
- coming_from_other_implementations.md
- conf.py
- configuration_notes.md
- cookbook.md
- dataframes_in_haskell.md
- exploratory_data_analysis_primer.md
- haskell_for_data_analysis.md
- index.rst
- intro_to_probability_and_data.md
- persistent_integration.md
- quick_start.md
- requirements.txt
- tutorial.md
- using_dataframe_in_a_standalone_script.md
- working_with_nulls.md
- CaliforniaHousing.hs
- Chipotle.hs
- examples.cabal
- Iris.ipynb
- Iris.lhs
- Main.hs
- OneBillionRowChallenge.hs
- README.md
- run_1brc.sh
- setup_torch.sh
- titanic.ipynb
- Arrow.hs
- IR.hs
- flake.lock
- flake.nix
- __init__.py
- __init__.py
- dependency_links.txt
- PKG-INFO
- requires.txt
- SOURCES.txt
- top_level.txt
- build_wheel.sh
- example.py
- lazy_example.py
- MANIFEST.in
- pyproject.toml
- README.md
- setup.py
- benchmark.sh
- check-readmes.sh
- check-should-fail.sh
- coverage.sh
- dataframe.sh
- format.sh
- gen_sklearn_golden.py
- install.sh
- lint.sh
- presubmit.sh
- profile.sh
- release.sh
- repl.ps1
- repl.sh
- TH.hs
- IO.hs
- TH.hs
- Typed.hs
- DataFrame.hs
- example.gif
- texts.txt
- texts_with_empties.txt
- texts_with_empties_and_nullish.txt
- all_empty_row.csv
- comma_in_quotes.csv
- crlf.csv
- crlf.tsv
- either_read_mixed.csv
- empty_file.csv
- empty_values.csv
- escaped_quotes.csv
- extra_fields.csv
- header_only.csv
- json_data.csv
- missing_fields.csv
- newlines.csv
- no_trailing_newline.csv
- quotes_and_newlines.csv
- simple.csv
- simple.tsv
- single_col.csv
- temp_escaped_quotes.csv
- temp_json_data.csv
- temp_quotes_and_newlines.csv
- trailing_blank_line.csv
- utf8.csv
- utf8_bom.csv
- whitespace_fields.csv
- _KEY_MATERIAL_FOR_external_key_material_java.parquet.encrypted.json
- alltypes_dictionary.parquet
- alltypes_plain.parquet
- alltypes_plain.snappy.parquet
- alltypes_tiny_pages.parquet
- alltypes_tiny_pages_plain.parquet
- arbuthnot.csv
- binary.parquet
- binary_truncated_min_max.parquet
- bloom_filter.bin
- bloom_filter.xxhash.bin
- byte_array_decimal.parquet
- byte_stream_split.zstd.parquet
- byte_stream_split_extended.gzip.parquet
- chipotle.tsv
- city.csv
- column_chunk_key_value_metadata.parquet
- concatenated_gzip_members.parquet
- data_index_bloom_encoding_stats.parquet
- data_index_bloom_encoding_with_length.parquet
- datapage_v1-corrupt-checksum.parquet
- datapage_v1-snappy-compressed-checksum.parquet
- datapage_v1-uncompressed-checksum.parquet
- datapage_v2.snappy.parquet
- datapage_v2_empty_datapage.snappy.parquet
- delta_binary_packed.md
- delta_binary_packed.parquet
- delta_binary_packed_expect.csv
- delta_byte_array.md
- delta_byte_array.parquet
- delta_byte_array_expect.csv
- delta_encoding_optional_column.md
- delta_encoding_optional_column.parquet
- delta_encoding_optional_column_expect.csv
- delta_encoding_required_column.md
- delta_encoding_required_column.parquet
- delta_encoding_required_column_expect.csv
- delta_length_byte_array.parquet
- dict-page-offset-zero.parquet
- encrypt_columns_and_footer.parquet.encrypted
- encrypt_columns_and_footer_aad.parquet.encrypted
- encrypt_columns_and_footer_ctr.parquet.encrypted
- encrypt_columns_and_footer_disable_aad_storage.parquet.encrypted
- encrypt_columns_plaintext_footer.parquet.encrypted
- external_key_material_java.parquet.encrypted
- fixed_length_byte_array.md
- fixed_length_byte_array.parquet
- fixed_length_decimal.parquet
- fixed_length_decimal_legacy.parquet
- float16_nonzeros_and_nans.parquet
- float16_zeros_and_nans.parquet
- hadoop_lz4_compressed.parquet
- hadoop_lz4_compressed_larger.parquet
- housing.csv
- incorrect_map_schema.parquet
- int32_decimal.parquet
- int32_with_null_pages.md
- int32_with_null_pages.parquet
- int64_decimal.parquet
- int96_from_spark.md
- int96_from_spark.parquet
- large_string_map.brotli.parquet
- list_columns.parquet
- lz4_raw_compressed.parquet
- lz4_raw_compressed_larger.parquet
- map_no_value.md
- map_no_value.parquet
- mtcars.parquet
- nan_in_stats.parquet
- nation.dict-malformed.parquet
- nested_lists.snappy.parquet
- nested_maps.snappy.parquet
- nested_structs.rust.parquet
- non_hadoop_lz4_compressed.parquet
- nonnullable.impala.parquet
- null_list.parquet
- nullable.impala.parquet
- nulls.snappy.parquet
- old_list_structure.md
- old_list_structure.parquet
- overflow_i16_page_cnt.parquet
- page_v2_empty_compressed.parquet
- plain-dict-uncompressed-checksum.parquet
- present.csv
- README.md
- repeated_no_annotation.parquet
- repeated_primitive_no_list.parquet
- rle-dict-snappy-checksum.parquet
- rle-dict-uncompressed-corrupt-checksum.parquet
- rle_boolean_encoding.parquet
- single_nan.parquet
- sort_columns.parquet
- starwars.csv
- station.csv
- test_no_newline.csv
- test_with_newline.csv
- timestamp_nanos.parquet
- transactions.parquet
- uniform_encryption.parquet.encrypted
- unknown-logical-type.parquet
- ColumnBuilder.hs
- DictEncode.hs
- Markdown.hs
- PackedText.hs
- Parsing.hs
- CSV.hs
- CsvGolden.hs
- JSON.hs
- ExprJsonRoundtrip.hs
- Denotation.hs
- Ensembles.hs
- Metamorphic.hs
- MetricsTests.hs
- Models.hs
- Segmented.hs
- SklearnParity.hs
- Synthesis.hs
- TypedModel.hs
- Aggregations.hs
- Apply.hs
- Core.hs
- Derive.hs
- Filter.hs
- GroupBy.hs
- Inference.hs
- InsertColumn.hs
- Join.hs
- Merge.hs
- Nullable.hs
- NullableHashing.hs
- ParallelGroupBy.hs
- ParallelJoin.hs
- Provenance.hs
- ReadCsv.hs
- Record.hs
- SetOps.hs
- Shuffle.hs
- Sort.hs
- Statistics.hs
- Subset.hs
- Take.hs
- Typing.hs
- VectorKernel.hs
- Window.hs
- WriteCsv.hs
- Categorical.hs
- conftest.py
- test_auto_types.py
- test_decision_tree.py
- test_expressions.py
- test_phase2.py
- test_phase3.py
- test_phase4.py
- test_phase5.py
- test_read_csv_nullable.py
- IOReaders.hs
- Parity.hs
- Assertions.hs
- Functions.hs
- GenDataFrame.hs
- LazyParity.hs
- LazyParquet.hs
- LazyProjection.hs
- Main.hs
- Monad.hs
- PackedTextMain.hs
- PackedTextMigration.hs
- Parquet.hs
- ParquetTestData.hs
- Plotting.hs
- PrettyPrint.hs
- Properties.hs
- Simplify.hs
- ImputePlain.hs
- .fourmolu-ignore
- .ghci
- .gitattributes
- .gitignore
- .hlint.yaml
- .readthedocs.yaml
- cabal.project
- cabal.project.bare
- cabal.project.ci
- CHANGELOG.md
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- dataframe.cabal
- dataframe.ghci
- flake.lock
- flake.nix
- fourmolu.yaml
- LICENSE
- projected_csv_read.md
- README.md
- SECURITY.md
- test_coverage.md
- upload-hackage.sh
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/DataHaskell/dataframe
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd dataframe
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. Python
쉬움 추천사전 준비물
pip install .
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
jupyter notebook
브라우저에서 노트북(.ipynb) 파일들을 열람하고 실행할 수 있는 Jupyter 화면을 켭니다.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
3. Rust
보통사전 준비물
- Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
- Rust (rustup) rustup으로 설치하면 cargo도 함께 설치됩니다.
⚠️ 이 프로젝트는 규모가 큰 저장소라, 이 방법이 실제 핵심 제품이 아니라 내부 하위 패키지를 가리키는 것일 수 있습니다. README 전체를 함께 확인해보세요.
cd dataframe-fusion/rust/dfusion-bridge
이 프로젝트의 관련 파일이 하위 폴더 안에 있어서, 먼저 그 폴더로 이동합니다.
cargo build --release
Rust 프로젝트를 컴파일합니다.
cargo run
빌드 후 바로 실행까지 진행합니다.
cargo build가 에러 없이 끝나면 성공입니다. target/ 폴더에 실행 파일이 생성됩니다.
// repository documentation
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