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Unset this environment variable to silence this warning.) stacklevel)pa_version_under10p1 pa_not_found)VERSIONSz-was not found to be installed on your system.z%was too old on your system - pyarrow pyarrowz= is the current minimum supported version as of this release.z Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0), (to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries) but z If this would cause problems for you, please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466 a 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. 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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. )rrr rDrr'rGr9r,rrbrcr=rrr>rjr&r.rrrrr7rr*r)r!r/rBr0rr-r(rFrHrr2r+r4rrrrrZrCr[r6rLrSrXr5r r\rKr?rVrWr rIr8r]r"r#rzrMrNrPrQrRr$r%rJrrr1rTrUr^rYrorerdrrrfrsrkrtrvrqrprhrxryrlrmrnrwrgrur rEr rar{r`r3r;r:rir<r_r@rArO) __future__roswarnings __docformat___hard_dependencies_missing_dependencies _dependency __import__ ImportError_eappendjoin pandas.compatr _is_numpy_dev_errname_modulepandas._configr r r r rrpandas.core.config_initpandaspandas.core.apirrrrrrrrrrrrrrrrr r!r"r#r$r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFrGpandas.core.dtypes.dtypesrHpandas.tseries.apirIpandas.tseriesrJpandas.core.computation.apirKpandas.core.reshape.apirLrMrNrOrPrQrRrSrTrUrVrWrXrYrZr[r\r]r^r_r`pandas.util._print_versionsra pandas.io.apirbrcrdrerfrgrhrirjrkrlrmrnrorprqrrrsrtrurvrwrxrypandas.io.json._normalizerzpandas.util._testerr{_built_with_mesonpandas._version_mesonr|r}pandas._versionr~vgetenvironwarn FutureWarningpandas.compat.pyarrowrrpandas.compat._optionalrpa_msgDeprecationWarning__doc____all__I/var/www/html/aiagents/fe/lib/python3.12/site-packages/pandas/__init__.pyrs" " 3%=K=;=  3dii@U6VV  %: ???????????????B2)",">=5B5$  BJJ&HMM V  E0@4HY4G3HIK K  HMM  H     &,"& Vs U =$$ }Brd%;<<=iiG  y!G G   ~,A%% q|4Kee-.Oa sAGH* H-H#G??HH* H%%H*-