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other:uvcdat:cdat_conda:cdat_8_2_1 [2024/05/15 16:53] – [Extra packages list] Updated tqdm link jypeterother:uvcdat:cdat_conda:cdat_8_2_1 [2025/08/20 15:41] (current) – [Python distribution based on CDAT 8.2.1 notes] jypeter
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 +  * [[other:uvcdat:cdat_conda:cdat_2024_03|JYP's Python distribution (2024-03)]]
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     * ''python-cdo'' will install the ''cdo'' package (providing the ''cdo ''executable) as a dependency     * ''python-cdo'' will install the ''cdo'' package (providing the ''cdo ''executable) as a dependency
     * see also [[https://code.mpimet.mpg.de/projects/cdo/wiki/Cdo%7Brbpy%7D|Using CDO from python or ruby]]     * see also [[https://code.mpimet.mpg.de/projects/cdo/wiki/Cdo%7Brbpy%7D|Using CDO from python or ruby]]
 +    * See also ''nco''
   * [[https://cds.climate.copernicus.eu/api-how-to|cdsapi]]: The Climate Data Store (CDS) Application Program Interface (API) is a service providing programmatic access to CDS data   * [[https://cds.climate.copernicus.eu/api-how-to|cdsapi]]: The Climate Data Store (CDS) Application Program Interface (API) is a service providing programmatic access to CDS data
     * CDS = Copernicus [[https://cds.climate.copernicus.eu/|Climate Data Store]]     * CDS = Copernicus [[https://cds.climate.copernicus.eu/|Climate Data Store]]
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     * the colormaps are also available in [[https://jiffyclub.github.io/palettable/scientific/|palettable.scientific]]     * the colormaps are also available in [[https://jiffyclub.github.io/palettable/scientific/|palettable.scientific]]
   * [[http://matplotlib.org/cmocean/|cmocean]]: beautiful colormaps for oceanography ''[color]''   * [[http://matplotlib.org/cmocean/|cmocean]]: beautiful colormaps for oceanography ''[color]''
 +  * [[https://github.com/kelvinou01/conda-which|conda-which]]: find the package owning a file
 +    * See the [[https://github.com/conda/conda/issues/14026|Is there an easy way to find the package "owning" a file ?]] GH issue
   * [[https://dash.plotly.com/|dash]] and [[https://github.com/plotly/jupyter-dash|jupyter-dash]]: the original low-code framework for rapidly building data apps in Python, R, Julia, and F#   * [[https://dash.plotly.com/|dash]] and [[https://github.com/plotly/jupyter-dash|jupyter-dash]]: the original low-code framework for rapidly building data apps in Python, R, Julia, and F#
     * see also ''plotly''     * see also ''plotly''
 +  * [[https://docs.dask.org/|dask]]: a Python library for parallel and distributed computing
 +    * dask.[[https://distributed.dask.org/|distributed]]: lightweight library for distributed computing in Python
 +    * See also: flox
   * [[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 dtale -c conda-forge''
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   * [[https://noaa-orr-erd.github.io/gridded/index.html|gridded]]: a single API for accessing / working with gridded model results on multiple grid types   * [[https://noaa-orr-erd.github.io/gridded/index.html|gridded]]: a single API for accessing / working with gridded model results on multiple grid types
     * Supports the [[http://cfconventions.org/|CF]], [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID]] and [[http://sgrid.github.io/sgrid/|SGRID]] conventions     * Supports the [[http://cfconventions.org/|CF]], [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID]] and [[http://sgrid.github.io/sgrid/|SGRID]] conventions
 +  * [[https://uber.github.io/h3-py/|h3-py]]: Uber’s H3 Hexagonal Hierarchical Geospatial Indexing System in Python
 +    * Additional reading: [[https://towardsdatascience.com/uber-h3-for-data-analysis-with-python-1e54acdcc908|Uber H3 for Data Analysis with Python]]
   * [[https://icclim.readthedocs.io/|icclim]]: icclim (Index Calculation for CLIMate) is a Python library to compute climate indices   * [[https://icclim.readthedocs.io/|icclim]]: icclim (Index Calculation for CLIMate) is a Python library to compute climate indices
   * [[https://intake.readthedocs.io/|intake]]: a lightweight package for finding, investigating, loading and disseminating data   * [[https://intake.readthedocs.io/|intake]]: a lightweight package for finding, investigating, loading and disseminating data
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   * [[https://gitlab.com/remikz/nccmp|nccmp]]: compare two NetCDF files bitwise, semantically or with a user defined tolerance (absolute or relative percentage)   * [[https://gitlab.com/remikz/nccmp|nccmp]]: compare two NetCDF files bitwise, semantically or with a user defined tolerance (absolute or relative percentage)
     * can probably also be done with [[https://code.mpimet.mpg.de/projects/cdo/embedded/index.html#x1-580002.1.3|cdo -v diffn file1.nc file2.nc]]     * can probably also be done with [[https://code.mpimet.mpg.de/projects/cdo/embedded/index.html#x1-580002.1.3|cdo -v diffn file1.nc file2.nc]]
 +  * [[https://nco.sourceforge.net/|nco]]: The NCO toolkit manipulates and analyzes data stored in netCDF-accessible formats
 +    * Note: this only installs the [[https://nco.sourceforge.net/#Definition|nco executables]] (''ncks'', ''ncatted'', ...)! It is not really a Python package
 +    * See also ''cdo''
   * [[https://opencv.org/|OpenCV]]: OpenCV (Open Source Computer Vision Library) is an open-source library that includes several hundreds of computer vision algorithms. See also [[https://www.geeksforgeeks.org/opencv-python-tutorial/|OpenCV Python Tutorial]] and **scikit-image**   * [[https://opencv.org/|OpenCV]]: OpenCV (Open Source Computer Vision Library) is an open-source library that includes several hundreds of computer vision algorithms. See also [[https://www.geeksforgeeks.org/opencv-python-tutorial/|OpenCV Python Tutorial]] and **scikit-image**
   * [[https://openpyxl.readthedocs.io/|openpyxl]]: a Python library to read/write Excel 2010 ''xlsx''/''xlsm'' files   * [[https://openpyxl.readthedocs.io/|openpyxl]]: a Python library to read/write Excel 2010 ''xlsx''/''xlsm'' files
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   * [[https://xgrads.readthedocs.io/|xgrads]]: parse and read binary dataset described by a ''.ctl'' file commonly used by [[http://cola.gmu.edu/grads/|GrADS]] or [[http://www.opengrads.org/|openGrADS]]   * [[https://xgrads.readthedocs.io/|xgrads]]: parse and read binary dataset described by a ''.ctl'' file commonly used by [[http://cola.gmu.edu/grads/|GrADS]] or [[http://www.opengrads.org/|openGrADS]]
   * [[https://xlrd.readthedocs.io/|xlrd]]: a library for reading data and formatting information from Excel files in the historical .xls format   * [[https://xlrd.readthedocs.io/|xlrd]]: a library for reading data and formatting information from Excel files in the historical .xls format
-  * [[https://xoa.readthedocs.io/en/latest/|xoa]]: xarray-based ocean analysis library +  * [[https://xoa.readthedocs.io/|xoa]]: xarray-based ocean analysis library 
-    * ''xoa'' is the successor of [[http://www.ifremer.fr/vacumm/|vacumm]] (vacumm does **not** support Python3)+    * ''xoa'' is the successor of [[https://umr-lops-vacumm.ifremer.fr/|vacumm]] (vacumm does **not** support Python3)
   * [[https://xskillscore.readthedocs.io/|xskillscore]]: metrics for verifying forecasts   * [[https://xskillscore.readthedocs.io/|xskillscore]]: metrics for verifying forecasts
   * [[https://docs.profiling.ydata.ai/|ydata-profiling]]: a leading package for data profiling, that automates and standardizes the generation of detailed reports, complete with statistics and visualizations.   * [[https://docs.profiling.ydata.ai/|ydata-profiling]]: a leading package for data profiling, that automates and standardizes the generation of detailed reports, complete with statistics and visualizations.
other/uvcdat/cdat_conda/cdat_8_2_1.1715784809.txt.gz · Last modified: by jypeter

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