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If you want to import pandas from the source directory, you may need to run 'python setup.py build_ext' to build the C extensions first.) get_option set_option reset_optiondescribe_optionoption_contextoptions)8 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 factorizeunique value_countsNamedAggarray Categoricalset_eng_float_formatSeries DataFrame) 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_featherread_gbq read_htmlread_xml read_json read_stataread_sas read_spss)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. )rrrrCrr&rFr8r+rrarbr<rrr=rir%r-rrrrr6rr)r(r r.rAr/rr,r'rErGrr1r*r3rrrrrYrBrZr5rKrRrWr4r r[rJr>rUrVr rHr7r\r!r"ryrLrMrOrPrQr#r$rIr rr0rSrTr]rXrnrdrcrqrerrrjrsrurprorgrwrxrkrlrmrvrfrtr rDr r`rzr_r2r:r9rhr;r^r?r@rN) __future__r __docformat___hard_dependencies_missing_dependencies _dependency __import__ ImportError_eappendjoin pandas.compatr _is_numpy_dev_errname_modulepandas._configr r r r r rpandas.core.config_initpandaspandas.core.apirrrrrrrrrrrrrrrrrr r!r"r#r$r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFpandas.core.dtypes.dtypesrGpandas.tseries.apirHpandas.tseriesrIpandas.core.computation.apirJpandas.core.reshape.apirKrLrMrNrOrPrQrRrSrTrUrVrWrXrYrZr[r\r]r^r_pandas.util._print_versionsr` pandas.io.apirarbrcrdrerfrgrhrirjrkrlrmrnrorprqrrrsrtrurvrwrxpandas.io.json._normalizerypandas.util._testerrz_built_with_mesonpandas._version_mesonr{r|pandas._versionr}vget__doc____all__rr\/var/www/html/HyperOracle/crypto_trader/venv/lib/python3.10/site-packages/pandas/__init__.pysl        A   @   h !    +