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| other:uvcdat:cdat_conda:cdat_2024_03 [2026/07/24 10:14] – [Extra packages list] Added netgraph jypeter | other:uvcdat:cdat_conda:cdat_2024_03 [2026/10/19 09:51] (current) – [Extra packages list] Added conda-which warning jypeter |
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| * [[https://github.com/AutoViML/AutoViz|AutoViz]]: the One-Line Automatic Data Visualization Library. Automatically Visualize any dataset, any size with a single line of code | * [[https://github.com/AutoViML/AutoViz|AutoViz]]: the One-Line Automatic Data Visualization Library. Automatically Visualize any dataset, any size with a single line of code |
| * [[https://matplotlib.org/basemap/|basemap]]: a library for plotting 2D data on maps in Python | * [[https://matplotlib.org/basemap/|basemap]]: a library for plotting 2D data on maps in Python |
| | * 2026-09: <wrap hi>''basemap'' can't be installed with a recent version of ''numpy'' (''numpy >= 2.4'')</wrap>, see [[https://github.com/matplotlib/basemap/issues/655|Add numpy 2.5 compatibility]] |
| * [[missing|basemap-data]] and [[https://github.com/conda-forge/basemap-data-hires-feedstock|basemap-data-hires]]: (high resolution) data for ''basemap'' | * [[missing|basemap-data]] and [[https://github.com/conda-forge/basemap-data-hires-feedstock|basemap-data-hires]]: (high resolution) data for ''basemap'' |
| * [[https://blosc.org/python-blosc2/getting_started/overview.html|Python-Blosc2]]: a high-performance compressed ''ndarray'' library with a flexible compute engine | * [[https://blosc.org/python-blosc2/getting_started/overview.html|Python-Blosc2]]: a high-performance compressed ''ndarray'' library with a flexible compute engine |
| * [[https://conda.github.io/conda-pypi/|conda-pypi]]: provides better PyPI interoperability for the conda ecosystem | * [[https://conda.github.io/conda-pypi/|conda-pypi]]: provides better PyPI interoperability for the conda ecosystem |
| * [[https://github.com/kelvinou01/conda-which|conda-which]]: find the package owning a file | * [[https://github.com/kelvinou01/conda-which|conda-which]]: find the package owning a file |
| | * <wrap hi>[[https://github.com/kelvinou01/conda-which/issues/7|conda-which 0.2.2 BREAKS conda > 26.7]]</wrap> |
| * See the [[https://github.com/conda/conda/issues/14026|Is there an easy way to find the package "owning" a file ?]] GH issue | * See the [[https://github.com/conda/conda/issues/14026|Is there an easy way to find the package "owning" a file ?]] GH issue |
| * [[https://www.cvxpy.org/|cvxpy]]: an open source Python-embedded modeling language for convex optimization problems | * [[https://www.cvxpy.org/|cvxpy]]: an open source Python-embedded modeling language for convex optimization problems |
| * [[https://dateutil.readthedocs.io/|python-dateutil]]: the ''dateutil'' module provides powerful extensions to the standard ''datetime'' module, available in Python | * [[https://dateutil.readthedocs.io/|python-dateutil]]: the ''dateutil'' module provides powerful extensions to the standard ''datetime'' module, available in Python |
| * [[https://github.com/man-group/dtale|D-Tale]] brings you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. | * [[https://github.com/man-group/dtale|D-Tale]] brings you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. |
| * Install with: ''conda install dtale -c conda-forge'' | * Install with: ''conda install -c conda-forge dtale'' |
| * [[https://dynamictimewarping.github.io/|python-dtw]]: implementation of Dynamic Time Warping-type (DTW) | * [[https://dynamictimewarping.github.io/|python-dtw]]: implementation of Dynamic Time Warping-type (DTW) |
| * Note: older installations provided [[https://github.com/pierre-rouanet/dtw|dtw]]: DTW (Dynamic Time Warping) python module | * Note: older installations provided [[https://github.com/pierre-rouanet/dtw|dtw]]: DTW (Dynamic Time Warping) python module |
| * install sample data with ''conda install -c conda-forge iris-sample-data'' | * install sample data with ''conda install -c conda-forge iris-sample-data'' |
| * [[https://joblib.readthedocs.io/en/latest/|joblib]]: running Python functions as pipeline jobs | * [[https://joblib.readthedocs.io/en/latest/|joblib]]: running Python functions as pipeline jobs |
| * [[https://jupyterlab.readthedocs.io/|jupyterlab]]: the next-generation web-based user interface for Project Jupyter | * [[https://jupyter.org/|jupyter notebooks]]: Notebook Interface |
| | * Installation: ''conda install -c conda-forge jupyter jupyterlab notebook nbconvert pandoc'' |
| | * Start local server with |
| | * ''jupyter lab'' |
| | * or ''jupyter notebook'' |
| | * Convert notebook with [[https://nbconvert.readthedocs.io/en/latest/usage.html|nbconvert]] |
| | * ''jupyter nbconvert --to html my_notebook.ipynb'' |
| | * ''jupyter nbconvert --to script my_notebook.ipynb'' |
| | * [[https://docs.jupyter.org/|Documentation]] |
| * [[https://github.com/plotly/Kaleido|python-kaleido]]: a cross-platform library for generating static images (e.g. png, svg, pdf, etc.) for web-based visualization libraries | * [[https://github.com/plotly/Kaleido|python-kaleido]]: a cross-platform library for generating static images (e.g. png, svg, pdf, etc.) for web-based visualization libraries |
| * [[https://unidata.github.io/MetPy/latest/|MetPy]]: a collection of tools in Python for reading, visualizing, and performing calculations with weather data | * [[https://unidata.github.io/MetPy/latest/|MetPy]]: a collection of tools in Python for reading, visualizing, and performing calculations with weather data |
| * See also ''pynco'', ''cdo'' | * See also ''pynco'', ''cdo'' |
| * [[https://netgraph.readthedocs.io/|netgraph]]: publication-quality network visualisations in python | * [[https://netgraph.readthedocs.io/|netgraph]]: publication-quality network visualisations in python |
| | * FIXME: need a temporary version until [[https://github.com/paulbrodersen/netgraph/issues/106|"Community Node Layout" example broken with numpy>2.4.6]] is fixed |
| | * ''conda create -n masa_tmp matplotlib networkx netgraph 'numpy<2.5.0' pandas openpyxl'' |
| * [[https://networkx.org/|networkx]]: a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex network | * [[https://networkx.org/|networkx]]: a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex network |
| * [[https://pypi.org/project/nicopal/|nicopal]]: perceptually uniform and colour-vision-deficiency-friendly colour palettes for scientific data visualisation | * [[https://pypi.org/project/nicopal/|nicopal]]: perceptually uniform and colour-vision-deficiency-friendly colour palettes for scientific data visualisation |
| * See also ''pandas'', ''XlsxWriter'', ''xlrd'' | * See also ''pandas'', ''XlsxWriter'', ''xlrd'' |
| * [[https://jiffyclub.github.io/palettable/|Palettable]]: Color palettes for Python ''[color]'' | * [[https://jiffyclub.github.io/palettable/|Palettable]]: Color palettes for Python ''[color]'' |
| | * [[https://python-graph-gallery.com/introduction-to-pypalettes/|PyPalettes]]: a python library that provides more than 2500 different palettes to use in your data visualization |
| | * [[https://python-graph-gallery.com/color-palette-finder/|Python Color Palette Finder]] |
| * [[http://pandas.pydata.org/|pandas]]: Python Data Analysis Library | * [[http://pandas.pydata.org/|pandas]]: Python Data Analysis Library |
| * [[https://geopandas.org/|geopandas]]: an open source project to make working with geospatial data in python easier | * [[https://geopandas.org/|geopandas]]: an open source project to make working with geospatial data in python easier |
| * [[https://peakutils.readthedocs.io/|PeakUtils]]: utilities related to the detection of peaks on 1D data | * [[https://peakutils.readthedocs.io/|PeakUtils]]: utilities related to the detection of peaks on 1D data |
| * [[https://python-pillow.org/|pillow]]: the friendly PIL (//Python Imaging Library//) fork | * [[https://python-pillow.org/|pillow]]: the friendly PIL (//Python Imaging Library//) fork |
| | * [[https://platformdirs.readthedocs.io/|platformdirs]]: a Python library for determining platform-specific system directories (resolves the correct location for macOS, Windows, Linux/Unix, and Android) |
| * [[https://plotly.com/python/|plotly]]: Plotly's Python graphing library (sometimes referred to as //plotly.py//) makes interactive, publication-quality graphs | * [[https://plotly.com/python/|plotly]]: Plotly's Python graphing library (sometimes referred to as //plotly.py//) makes interactive, publication-quality graphs |
| * see also ''python-kaleido'' and ''dash'' | * see also ''python-kaleido'' and ''dash'' |
| * [[https://plotnine.org/|plotnine]]: a data visualization package for Python based on the grammar of graphics, a coherent system for describing and building graphs | * [[https://plotnine.org/|plotnine]]: a data visualization package for Python based on the grammar of graphics, a coherent system for describing and building graphs |
| * similar to ''ggplot2'', a widely successful ''R'' package | * similar to ''ggplot2'', a widely successful ''R'' package |
| | * [[https://pola.rs/|polars]]: an open-source library for data manipulation, known for being one of the fastest data processing solutions on a single machine |
| | * [[https://anaconda.org/channels/conda-forge/packages/polars/overview|polars @ conda-forge]]: official instructions only mention pip installation... |
| * [[https://www.fatiando.org/pooch/|pooch]]: a friend to fetch your data files (makes it easy to download a file, without messing with ''requests'' and ''urllib'') | * [[https://www.fatiando.org/pooch/|pooch]]: a friend to fetch your data files (makes it easy to download a file, without messing with ''requests'' and ''urllib'') |
| * //proplot//: a lightweight matplotlib wrapper for making beautiful, publication-quality graphics | * //proplot//: a lightweight matplotlib wrapper for making beautiful, publication-quality graphics |
| * **Replaced by ''ultraplot''** | * **Replaced by ''ultraplot''** |
| | * [[https://psutil.readthedocs.io/|psutil]]: a cross-platform library for retrieving information on running processes and system utilization |
| * [[https://psyplot.github.io/|psyplot]]: Interactive Data Visualization from Python and GUIs | * [[https://psyplot.github.io/|psyplot]]: Interactive Data Visualization from Python and GUIs |
| * [[https://www.pygmt.org/latest/|PyGMT]]: a Python interface for the [[https://www.generic-mapping-tools.org/|Generic Mapping Tools]] | * [[https://www.pygmt.org/latest/|PyGMT]]: a Python interface for the [[https://www.generic-mapping-tools.org/|Generic Mapping Tools]] |
| * [[https://requests.readthedocs.io/|requests]]: is an elegant and simple HTTP library for Python, built for human beings | * [[https://requests.readthedocs.io/|requests]]: is an elegant and simple HTTP library for Python, built for human beings |
| * See also ''pooch'' | * See also ''pooch'' |
| | * [[https://rich.readthedocs.io/|rich]]: a Python library for writing rich text (with color and style) to the terminal, and for displaying advanced content such as tables, markdown, and syntax highlighted code |
| * [[https://corteva.github.io/rioxarray/stable/|rioxarray]]: an extension of xarray that focuses on geospatial raster data | * [[https://corteva.github.io/rioxarray/stable/|rioxarray]]: an extension of xarray that focuses on geospatial raster data |
| * [[https://geog-312.gishub.org/book/geospatial/rioxarray.html|rioxarray tutorial]] | * [[https://geog-312.gishub.org/book/geospatial/rioxarray.html|rioxarray tutorial]] |
| * [[https://rpy2.github.io/|rpy2]]: an interface to R running embedded in a Python process | * [[https://rpy2.github.io/|rpy2]]: an interface to R running embedded in a Python process |
| | * [[https://salib.readthedocs.io/|SALib]]: Python implementations of commonly used sensitivity analysis methods, including Sobol, Morris, and FAST methods. Useful in systems modeling to calculate the effects of model inputs or exogenous factors on outputs of interest |
| * [[https://scikit.bio/|scikit-bio]]: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources | * [[https://scikit.bio/|scikit-bio]]: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources |
| * [[http://scikit-image.org/|scikit-image]]: a collection of algorithms for image processing in Python | * [[http://scikit-image.org/|scikit-image]]: a collection of algorithms for image processing in Python |
| * [[https://ultraplot.readthedocs.io/en/latest/|UltraPlot]]: a succinct matplotlib wrapper for making beautiful, publication-quality graphics | * [[https://ultraplot.readthedocs.io/en/latest/|UltraPlot]]: a succinct matplotlib wrapper for making beautiful, publication-quality graphics |
| * [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]] | * [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]] |
| | * [[https://amueller.github.io/word_cloud/|wordcloud]]: A little //word cloud// generator in Python |
| * [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! | * [[https://docs.xarray.dev/en/stable/|xarray]]: Xarray makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! |
| * See also: ''flox'', ''xcdat'', ''rioxarray'', ... | * See also: ''flox'', ''xcdat'', ''rioxarray'', ... |
