deb_control_files:
- control
- md5sums
- postinst
- prerm
deb_fields:
Architecture: all
Breaks: augur (<< 24.4.0-1~), cnvkit (<< 0.9.10~), python3-altair (<< 5.0.1~), python3-anndata
(<= 0.8.0-4), python3-biom-format (<< 2.1.15.2-3~), python3-cfgrib (<= 0.9.9-1),
python3-cooler (<< 0.9.3~), python3-dask (<< 2023.12.1~), python3-dials (<< 3.17.0~),
python3-dyda (<= 1.41.1-1.1), python3-emperor (<< 1.0.3+ds-9~), python3-esda (<=
2.5.1-1), python3-feather-format (<< 0.3.1+dfsg1-8~), python3-hypothesis (<< 6.83.1~),
python3-influxdb (<< 5.3.2-1~), python3-joypy (<= 0.2.2-2), python3-jsonpickle
(<< 3.0.2+dfsg-1~), python3-mirtop (<< 0.4.25-5~), python3-nanoget (<< 1.19.3~),
python3-pauvre (<< 0.2.3-3~), python3-pyani (<< 0.2.12-3~), python3-pymatgen (<<
2024.1.27~), python3-pyranges (<= 0.0.111+ds-6), python3-seaborn (<< 0.13.0~),
python3-skbio (<< 0.5.9~), python3-sklearn-pandas (<= 2.2.0-1.1), python3-statsmodels
(<< 0.14.2~), python3-sunpy (<< 5.1.0-1~), python3-ulmo (<= 0.8.8+dfsg1-2), python3-upsetplot
(<< 0.8.0-3~), python3-xarray-sentinel (<< 0.9.5+ds-2~), q2-cutadapt (<< 2023.7.0-1~),
q2-demux (<= 2023.9.1+dfsg-1), q2-quality-control (<= 2022.11.1-2), q2-taxa (<=
2023.9.0+dfsg-1), q2-types (<= 2023.9.0-1), q2templates (<= 2023.9.0+ds-1)
Depends: python3-dateutil, python3-numpy, python3-numpy (>= 1:1.23.2~) | python3-supported-max
(<< 3.11) | python3-supported-min (>= 3.12), python3-numpy (>= 1:1.23.2~) | python3-supported-max
(<< 3.12), python3-numpy (>= 1:1.23.2~) | python3-supported-min (>= 3.11), python3-tz
(>= 2022.7~), python3:any, python3-pandas-lib (>= 2.2.3+dfsg), tzdata
Description: |-
data structures for "relational" or "labeled" data
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. pandas is well suited for many different kinds of
data:
.
- Tabular data with heterogeneously-typed columns, as in an SQL
table or Excel spreadsheet
- Ordered and unordered (not necessarily fixed-frequency) time
series data.
- Arbitrary matrix data (homogeneously typed or heterogeneous) with
row and column labels
- Any other form of observational / statistical data sets. The data
actually need not be labeled at all to be placed into a pandas
data structure
.
This package contains the Python 3 version.
Homepage: https://pandas.pydata.org/
Installed-Size: '22364'
Maintainer: Debian Science Team <debian-science-maintainers@lists.alioth.debian.org>
Package: python3-pandas
Priority: optional
Recommends: python3-scipy, python3-matplotlib, python3-bottleneck, python3-numexpr,
python3-odf, python3-openpyxl, python3-bs4, python3-html5lib, python3-lxml, python3-tables,
python3-jinja2
Section: python
Source: pandas
Suggests: python-pandas-doc, python3-statsmodels
Version: 2.2.3+dfsg-3+debusine1
srcpkg_name: pandas
srcpkg_version: 2.2.3+dfsg-3+debusine1