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If you want to import pandas from the source directory, you may need to run 'python -m pip install -ve . --no-build-isolation -Ceditable-verbose=true' to build the C extensions first.) get_option set_option reset_optiondescribe_optionoption_contextoptions)7 ArrowDtype Int8Dtype Int16Dtype Int32Dtype Int64Dtype UInt8Dtype UInt16Dtype UInt32Dtype UInt64Dtype Float32Dtype Float64DtypeCategoricalDtype PeriodDtype IntervalDtypeDatetimeTZDtype StringDtype BooleanDtypeNAisnaisnullnotnanotnullIndexCategoricalIndex RangeIndex MultiIndex IntervalIndexTimedeltaIndex DatetimeIndex PeriodIndex IndexSliceNaTPeriod period_range Timedeltatimedelta_range Timestamp date_range bdate_rangeIntervalinterval_range DateOffset to_numeric to_datetime to_timedeltaFlagsGrouper factorizeuniqueNamedAggarray Categoricalset_eng_float_formatSeries DataFrame)col) SparseDtype) infer_freq)offsets)eval)concatlreshapemelt wide_to_longmerge merge_asof merge_orderedcrosstabpivot pivot_table get_dummies from_dummiescutqcut)apiarrayserrorsioplottingtseries)testing) show_versions) ExcelFile ExcelWriter read_excelread_csvread_fwf read_table read_pickle to_pickleHDFStoreread_hdfread_sqlread_sql_queryread_sql_tableread_clipboard read_parquetread_orc read_feather read_htmlread_xml read_json read_stataread_sas read_spss read_iceberg)json_normalize)testF) __version____git_version__T) get_versionsz closest-tagversionzfull-revisionida pandas - a powerful data analysis and manipulation library for Python ===================================================================== **pandas** is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, **real world** data analysis in Python. Additionally, it has the broader goal of becoming **the most powerful and flexible open source data analysis / manipulation tool available in any language**. It is already well on its way toward this goal. Main Features ------------- Here are just a few of the things that pandas does well: - Easy handling of missing data in floating point as well as non-floating point data. - Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects - Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let `Series`, `DataFrame`, etc. automatically align the data for you in computations. - Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data. - Make it easy to convert ragged, differently-indexed data in other Python and NumPy data structures into DataFrame objects. - Intelligent label-based slicing, fancy indexing, and subsetting of large data sets. - Intuitive merging and joining data sets. - Flexible reshaping and pivoting of data sets. - Hierarchical labeling of axes (possible to have multiple labels per tick). - Robust IO tools for loading data from flat files (CSV and delimited), Excel files, databases, and saving/loading data from the ultrafast HDF5 format. - Time series-specific functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. )rrrrrArr%rDr7r*rr`rar;rrr<rhr$r,rrrrr5rr(r'r-r?r.rr+r&rCrFrr0r)r2rrrrrXr@rYr4rErJrQrVr3r rZrIr=rUrTrrGr6r[r r!rxrKrLrNrOrPr"r#rHr r r/rRrSr\rWrmrcrbrprdrirqrwrsrornrfrurvrjrkrlrtrerrr rBr r_ryr^r1r9r8rgr:r]r>rM) __future__r __docformat___hard_dependencies _dependency __import__ ImportError_e pandas.compatr _is_numpy_dev_errname_modulepandas._configrr r r r r pandas.core.config_initpandaspandas.core.apirrrrrrrrrrrrrrrrrrr r!r"r#r$r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDpandas.core.colrEpandas.core.dtypes.dtypesrFpandas.tseries.apirGpandas.tseriesrHpandas.core.computation.apirIpandas.core.reshape.apirJrKrLrMrNrOrPrQrRrSrTrUrVrWrXrYrZr[r\r]r^pandas.util._print_versionsr_ pandas.io.apir`rarbrcrdrerfrgrhrirjrkrlrmrnrorprqrrrsrtrurvrwpandas.io.json._normalizerxpandas.util._testerry_built_with_mesonpandas._version_mesonrzr{pandas._versionr|vget__doc____all__L/home/mande/repo/quber/.venv/lib/python3.13/site-packages/pandas/__init__.pyrs"" +%K;&  >>>>>>>>>>>>>>>~ 1)",">=5B5$  & Vs E 3K=A4 4  iiG  y!+ +   @,A%% q|4Kee-.Oa s@EE5 FE2 E--E25F;FF=GG