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pandas-2.2.0-cp312-cp312-emscripten_3_1_52_wasm32.whl.metadata

pandas-2.2.0-cp312-cp312-emscripten_3_1_52_wasm32.whl.metadata 19 KB
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  1. Metadata-Version: 2.1
    2. 

  2. Name: pandas
    3. 

  3. Version: 2.2.0
    4. 

  4. Summary: Powerful data structures for data analysis, time series, and statistics
    5. 

  5. Home-page: https://pandas.pydata.org
    6. 

  6. Author-Email: The Pandas Development Team <pandas-dev@python.org>
    7. 

  7. License: BSD 3-Clause License
    8. 

  8.         
    9. 

  9.         Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
    10. 

  10.         All rights reserved.
    11. 

  11.         
    12. 

  12.         Copyright (c) 2011-2023, Open source contributors.
    13. 

  13.         
    14. 

  14.         Redistribution and use in source and binary forms, with or without
    15. 

  15.         modification, are permitted provided that the following conditions are met:
    16. 

  16.         
    17. 

  17.         * Redistributions of source code must retain the above copyright notice, this
    18. 

  18.           list of conditions and the following disclaimer.
    19. 

  19.         
    20. 

  20.         * Redistributions in binary form must reproduce the above copyright notice,
    21. 

  21.           this list of conditions and the following disclaimer in the documentation
    22. 

  22.           and/or other materials provided with the distribution.
    23. 

  23.         
    24. 

  24.         * Neither the name of the copyright holder nor the names of its
    25. 

  25.           contributors may be used to endorse or promote products derived from
    26. 

  26.           this software without specific prior written permission.
    27. 

  27.         
    28. 

  28.         THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
    29. 

  29.         AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
    30. 

  30.         IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
    31. 

  31.         DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
    32. 

  32.         FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
    33. 

  33.         DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
    34. 

  34.         SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
    35. 

  35.         CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
    36. 

  36.         OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
    37. 

  37.         OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
    38. 

  38. Classifier: Development Status :: 5 - Production/Stable
    39. 

  39. Classifier: Environment :: Console
    40. 

  40. Classifier: Intended Audience :: Science/Research
    41. 

  41. Classifier: License :: OSI Approved :: BSD License
    42. 

  42. Classifier: Operating System :: OS Independent
    43. 

  43. Classifier: Programming Language :: Cython
    44. 

  44. Classifier: Programming Language :: Python
    45. 

  45. Classifier: Programming Language :: Python :: 3
    46. 

  46. Classifier: Programming Language :: Python :: 3 :: Only
    47. 

  47. Classifier: Programming Language :: Python :: 3.9
    48. 

  48. Classifier: Programming Language :: Python :: 3.10
    49. 

  49. Classifier: Programming Language :: Python :: 3.11
    50. 

  50. Classifier: Programming Language :: Python :: 3.12
    51. 

  51. Classifier: Topic :: Scientific/Engineering
    52. 

  52. Project-URL: Homepage, https://pandas.pydata.org
    53. 

  53. Project-URL: Documentation, https://pandas.pydata.org/docs/
    54. 

  54. Project-URL: Repository, https://github.com/pandas-dev/pandas
    55. 

  55. Requires-Python: >=3.9
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  56. Requires-Dist: numpy<2,>=1.22.4; python_version < "3.11"
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  59. Requires-Dist: python-dateutil>=2.8.2
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  60. Requires-Dist: pytz>=2020.1
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  61. Requires-Dist: tzdata>=2022.7
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  63. Requires-Dist: pytest>=7.3.2; extra == "test"
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  64. Requires-Dist: pytest-xdist>=2.2.0; extra == "test"
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  66. Requires-Dist: numba>=0.56.4; extra == "performance"
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  68. Requires-Dist: scipy>=1.10.0; extra == "computation"
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  69. Requires-Dist: xarray>=2022.12.0; extra == "computation"
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  72. Requires-Dist: gcsfs>=2022.11.0; extra == "gcp"
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  73. Requires-Dist: pandas-gbq>=0.19.0; extra == "gcp"
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  74. Requires-Dist: odfpy>=1.4.1; extra == "excel"
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  75. Requires-Dist: openpyxl>=3.1.0; extra == "excel"
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  77. Requires-Dist: pyxlsb>=1.0.10; extra == "excel"
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  83. Requires-Dist: pyreadstat>=1.2.0; extra == "spss"
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  91. Requires-Dist: adbc-driver-sqlite>=0.8.0; extra == "sql-other"
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  92. Requires-Dist: beautifulsoup4>=4.11.2; extra == "html"
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  93. Requires-Dist: html5lib>=1.1; extra == "html"
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  94. Requires-Dist: lxml>=4.9.2; extra == "html"
    95. 

  95. Requires-Dist: lxml>=4.9.2; extra == "xml"
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  96. Requires-Dist: matplotlib>=3.6.3; extra == "plot"
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  97. Requires-Dist: jinja2>=3.1.2; extra == "output-formatting"
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  98. Requires-Dist: tabulate>=0.9.0; extra == "output-formatting"
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  99. Requires-Dist: PyQt5>=5.15.9; extra == "clipboard"
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  100. Requires-Dist: qtpy>=2.3.0; extra == "clipboard"
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  101. Requires-Dist: zstandard>=0.19.0; extra == "compression"
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  102. Requires-Dist: dataframe-api-compat>=0.1.7; extra == "consortium-standard"
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  103. Requires-Dist: adbc-driver-postgresql>=0.8.0; extra == "all"
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  106. Requires-Dist: bottleneck>=1.3.6; extra == "all"
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  107. Requires-Dist: dataframe-api-compat>=0.1.7; extra == "all"
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  108. Requires-Dist: fastparquet>=2022.12.0; extra == "all"
    109. 

  109. Requires-Dist: fsspec>=2022.11.0; extra == "all"
    110. 

  110. Requires-Dist: gcsfs>=2022.11.0; extra == "all"
    111. 

  111. Requires-Dist: html5lib>=1.1; extra == "all"
    112. 

  112. Requires-Dist: hypothesis>=6.46.1; extra == "all"
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  113. Requires-Dist: jinja2>=3.1.2; extra == "all"
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  114. Requires-Dist: lxml>=4.9.2; extra == "all"
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  115. Requires-Dist: matplotlib>=3.6.3; extra == "all"
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  116. Requires-Dist: numba>=0.56.4; extra == "all"
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  117. Requires-Dist: numexpr>=2.8.4; extra == "all"
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  118. Requires-Dist: odfpy>=1.4.1; extra == "all"
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  119. Requires-Dist: openpyxl>=3.1.0; extra == "all"
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  120. Requires-Dist: pandas-gbq>=0.19.0; extra == "all"
    121. 

  121. Requires-Dist: psycopg2>=2.9.6; extra == "all"
    122. 

  122. Requires-Dist: pyarrow>=10.0.1; extra == "all"
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  123. Requires-Dist: pymysql>=1.0.2; extra == "all"
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  124. Requires-Dist: PyQt5>=5.15.9; extra == "all"
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  125. Requires-Dist: pyreadstat>=1.2.0; extra == "all"
    126. 

  126. Requires-Dist: pytest>=7.3.2; extra == "all"
    127. 

  127. Requires-Dist: pytest-xdist>=2.2.0; extra == "all"
    128. 

  128. Requires-Dist: python-calamine>=0.1.7; extra == "all"
    129. 

  129. Requires-Dist: pyxlsb>=1.0.10; extra == "all"
    130. 

  130. Requires-Dist: qtpy>=2.3.0; extra == "all"
    131. 

  131. Requires-Dist: scipy>=1.10.0; extra == "all"
    132. 

  132. Requires-Dist: s3fs>=2022.11.0; extra == "all"
    133. 

  133. Requires-Dist: SQLAlchemy>=2.0.0; extra == "all"
    134. 

  134. Requires-Dist: tables>=3.8.0; extra == "all"
    135. 

  135. Requires-Dist: tabulate>=0.9.0; extra == "all"
    136. 

  136. Requires-Dist: xarray>=2022.12.0; extra == "all"
    137. 

  137. Requires-Dist: xlrd>=2.0.1; extra == "all"
    138. 

  138. Requires-Dist: xlsxwriter>=3.0.5; extra == "all"
    139. 

  139. Requires-Dist: zstandard>=0.19.0; extra == "all"
    140. 

  140. Provides-Extra: test
    141. 

  141. Provides-Extra: performance
    142. 

  142. Provides-Extra: computation
    143. 

  143. Provides-Extra: fss
    144. 

  144. Provides-Extra: aws
    145. 

  145. Provides-Extra: gcp
    146. 

  146. Provides-Extra: excel
    147. 

  147. Provides-Extra: parquet
    148. 

  148. Provides-Extra: feather
    149. 

  149. Provides-Extra: hdf5
    150. 

  150. Provides-Extra: spss
    151. 

  151. Provides-Extra: postgresql
    152. 

  152. Provides-Extra: mysql
    153. 

  153. Provides-Extra: sql-other
    154. 

  154. Provides-Extra: html
    155. 

  155. Provides-Extra: xml
    156. 

  156. Provides-Extra: plot
    157. 

  157. Provides-Extra: output-formatting
    158. 

  158. Provides-Extra: clipboard
    159. 

  159. Provides-Extra: compression
    160. 

  160. Provides-Extra: consortium-standard
    161. 

  161. Provides-Extra: all
    162. 

  162. Description-Content-Type: text/markdown
    163. 

  163. 

  164. <div align="center">
    165. 

  165.   <img src="https://pandas.pydata.org/static/img/pandas.svg"><br>
    166. 

  166. </div>
    167. 

  167. 

  168. -----------------
    169. 

  169. 

  170. # pandas: powerful Python data analysis toolkit
    171. 

  171. 

  172. | | |
    173. 

  173. | --- | --- |
    174. 

  174. | Testing | [![CI - Test](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml/badge.svg)](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml) [![Coverage](https://codecov.io/github/pandas-dev/pandas/coverage.svg?branch=main)](https://codecov.io/gh/pandas-dev/pandas) |
    175. 

  175. | Package | [![PyPI Latest Release](https://img.shields.io/pypi/v/pandas.svg)](https://pypi.org/project/pandas/) [![PyPI Downloads](https://img.shields.io/pypi/dm/pandas.svg?label=PyPI%20downloads)](https://pypi.org/project/pandas/) [![Conda Latest Release](https://anaconda.org/conda-forge/pandas/badges/version.svg)](https://anaconda.org/conda-forge/pandas) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/pandas.svg?label=Conda%20downloads)](https://anaconda.org/conda-forge/pandas) |
    176. 

  176. | Meta | [![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3509134.svg)](https://doi.org/10.5281/zenodo.3509134) [![License - BSD 3-Clause](https://img.shields.io/pypi/l/pandas.svg)](https://github.com/pandas-dev/pandas/blob/main/LICENSE) [![Slack](https://img.shields.io/badge/join_Slack-information-brightgreen.svg?logo=slack)](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) |
    177. 

  177. 

  178. 

  179. ## What is it?
    180. 

  180. 

  181. **pandas** is a Python package that provides fast, flexible, and expressive data
    182. 

  182. structures designed to make working with "relational" or "labeled" data both
    183. 

  183. easy and intuitive. It aims to be the fundamental high-level building block for
    184. 

  184. doing practical, **real world** data analysis in Python. Additionally, it has
    185. 

  185. the broader goal of becoming **the most powerful and flexible open source data
    186. 

  186. analysis / manipulation tool available in any language**. It is already well on
    187. 

  187. its way towards this goal.
    188. 

  188. 

  189. ## Table of Contents
    190. 

  190. 

  191. - [Main Features](#main-features)
    192. 

  192. - [Where to get it](#where-to-get-it)
    193. 

  193. - [Dependencies](#dependencies)
    194. 

  194. - [Installation from sources](#installation-from-sources)
    195. 

  195. - [License](#license)
    196. 

  196. - [Documentation](#documentation)
    197. 

  197. - [Background](#background)
    198. 

  198. - [Getting Help](#getting-help)
    199. 

  199. - [Discussion and Development](#discussion-and-development)
    200. 

  200. - [Contributing to pandas](#contributing-to-pandas)
    201. 

  201. 

  202. ## Main Features
    203. 

  203. Here are just a few of the things that pandas does well:
    204. 

  204. 

  205.   - Easy handling of [**missing data**][missing-data] (represented as
    206. 

  206.     `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data
    207. 

  207.   - Size mutability: columns can be [**inserted and
    208. 

  208.     deleted**][insertion-deletion] from DataFrame and higher dimensional
    209. 

  209.     objects
    210. 

  210.   - Automatic and explicit [**data alignment**][alignment]: objects can
    211. 

  211.     be explicitly aligned to a set of labels, or the user can simply
    212. 

  212.     ignore the labels and let `Series`, `DataFrame`, etc. automatically
    213. 

  213.     align the data for you in computations
    214. 

  214.   - Powerful, flexible [**group by**][groupby] functionality to perform
    215. 

  215.     split-apply-combine operations on data sets, for both aggregating
    216. 

  216.     and transforming data
    217. 

  217.   - Make it [**easy to convert**][conversion] ragged,
    218. 

  218.     differently-indexed data in other Python and NumPy data structures
    219. 

  219.     into DataFrame objects
    220. 

  220.   - Intelligent label-based [**slicing**][slicing], [**fancy
    221. 

  221.     indexing**][fancy-indexing], and [**subsetting**][subsetting] of
    222. 

  222.     large data sets
    223. 

  223.   - Intuitive [**merging**][merging] and [**joining**][joining] data
    224. 

  224.     sets
    225. 

  225.   - Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of
    226. 

  226.     data sets
    227. 

  227.   - [**Hierarchical**][mi] labeling of axes (possible to have multiple
    228. 

  228.     labels per tick)
    229. 

  229.   - Robust IO tools for loading data from [**flat files**][flat-files]
    230. 

  230.     (CSV and delimited), [**Excel files**][excel], [**databases**][db],
    231. 

  231.     and saving/loading data from the ultrafast [**HDF5 format**][hdfstore]
    232. 

  232.   - [**Time series**][timeseries]-specific functionality: date range
    233. 

  233.     generation and frequency conversion, moving window statistics,
    234. 

  234.     date shifting and lagging
    235. 

  235. 

  236. 

  237.    [missing-data]: https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html
    238. 

  238.    [insertion-deletion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#column-selection-addition-deletion
    239. 

  239.    [alignment]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html?highlight=alignment#intro-to-data-structures
    240. 

  240.    [groupby]: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#group-by-split-apply-combine
    241. 

  241.    [conversion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe
    242. 

  242.    [slicing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#slicing-ranges
    243. 

  243.    [fancy-indexing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced
    244. 

  244.    [subsetting]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#boolean-indexing
    245. 

  245.    [merging]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging
    246. 

  246.    [joining]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-on-index
    247. 

  247.    [reshape]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
    248. 

  248.    [pivot-table]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
    249. 

  249.    [mi]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#hierarchical-indexing-multiindex
    250. 

  250.    [flat-files]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files
    251. 

  251.    [excel]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#excel-files
    252. 

  252.    [db]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries
    253. 

  253.    [hdfstore]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#hdf5-pytables
    254. 

  254.    [timeseries]: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#time-series-date-functionality
    255. 

  255. 

  256. ## Where to get it
    257. 

  257. The source code is currently hosted on GitHub at:
    258. 

  258. https://github.com/pandas-dev/pandas
    259. 

  259. 

  260. Binary installers for the latest released version are available at the [Python
    261. 

  261. Package Index (PyPI)](https://pypi.org/project/pandas) and on [Conda](https://docs.conda.io/en/latest/).
    262. 

  262. 

  263. ```sh
    264. 

  264. # conda
    265. 

  265. conda install -c conda-forge pandas
    266. 

  266. ```
    267. 

  267. 

  268. ```sh
    269. 

  269. # or PyPI
    270. 

  270. pip install pandas
    271. 

  271. ```
    272. 

  272. 

  273. The list of changes to pandas between each release can be found
    274. 

  274. [here](https://pandas.pydata.org/pandas-docs/stable/whatsnew/index.html). For full
    275. 

  275. details, see the commit logs at https://github.com/pandas-dev/pandas.
    276. 

  276. 

  277. ## Dependencies
    278. 

  278. - [NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays](https://www.numpy.org)
    279. 

  279. - [python-dateutil - Provides powerful extensions to the standard datetime module](https://dateutil.readthedocs.io/en/stable/index.html)
    280. 

  280. - [pytz - Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations](https://github.com/stub42/pytz)
    281. 

  281. 

  282. See the [full installation instructions](https://pandas.pydata.org/pandas-docs/stable/install.html#dependencies) for minimum supported versions of required, recommended and optional dependencies.
    283. 

  283. 

  284. ## Installation from sources
    285. 

  285. To install pandas from source you need [Cython](https://cython.org/) in addition to the normal
    286. 

  286. dependencies above. Cython can be installed from PyPI:
    287. 

  287. 

  288. ```sh
    289. 

  289. pip install cython
    290. 

  290. ```
    291. 

  291. 

  292. In the `pandas` directory (same one where you found this file after
    293. 

  293. cloning the git repo), execute:
    294. 

  294. 

  295. ```sh
    296. 

  296. pip install .
    297. 

  297. ```
    298. 

  298. 

  299. or for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_install/#install-editable):
    300. 

  300. 

  301. 

  302. ```sh
    303. 

  303. python -m pip install -ve . --no-build-isolation --config-settings=editable-verbose=true
    304. 

  304. ```
    305. 

  305. 

  306. See the full instructions for [installing from source](https://pandas.pydata.org/docs/dev/development/contributing_environment.html).
    307. 

  307. 

  308. ## License
    309. 

  309. [BSD 3](LICENSE)
    310. 

  310. 

  311. ## Documentation
    312. 

  312. The official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/).
    313. 

  313. 

  314. ## Background
    315. 

  315. Work on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and
    316. 

  316. has been under active development since then.
    317. 

  317. 

  318. ## Getting Help
    319. 

  319. 

  320. For usage questions, the best place to go to is [StackOverflow](https://stackoverflow.com/questions/tagged/pandas).
    321. 

  321. Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata).
    322. 

  322. 

  323. ## Discussion and Development
    324. 

  324. Most development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues).
    325. 

  325. 

  326. Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions.
    327. 

  327. 

  328. There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors.
    329. 

  329. 

  330. Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page.
    331. 

  331. 

  332. ## Contributing to pandas
    333. 

  333. 

  334. [![Open Source Helpers](https://www.codetriage.com/pandas-dev/pandas/badges/users.svg)](https://www.codetriage.com/pandas-dev/pandas)
    335. 

  335. 

  336. All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
    337. 

  337. 

  338. A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**.
    339. 

  339. 

  340. If you are simply looking to start working with the pandas codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out.
    341. 

  341. 

  342. You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas).
    343. 

  343. 

  344. Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’...you can do something about it!
    345. 

  345. 

  346. Feel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack).
    347. 

  347. 

  348. As contributors and maintainers to this project, you are expected to abide by pandas' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/.github/blob/master/CODE_OF_CONDUCT.md)
    349. 

  349. 

  350. <hr>
    351. 

  351. 

  352. [Go to Top](#table-of-contents)
    353.