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| other:uvcdat:cdat_conda:cdat_2024_03 [2025/04/09 16:48] – [Extra packages list] Added NumExpr jypeter | other:uvcdat:cdat_conda:cdat_2024_03 [2025/08/27 11:09] (current) – [Extra packages list] added pynco jypeter |
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| * [[https://xlsxwriter.readthedocs.io/|XlsxWriter]]: a Python module for creating Excel XLSX files | * [[https://xlsxwriter.readthedocs.io/|XlsxWriter]]: a Python module for creating Excel XLSX files |
| * Note: <wrap hi>this is a dependency of ''dreqPy''</wrap> | * Note: <wrap hi>this is a dependency of ''dreqPy''</wrap> |
| | * See also ''pandas'', ''openpyxl'', ''xlrd'' |
| * [[https://earthsystemcog.org/projects/wip/CMIP6DataRequest|dreqPy]]: CMIP6 Data Request Python API | * [[https://earthsystemcog.org/projects/wip/CMIP6DataRequest|dreqPy]]: CMIP6 Data Request Python API |
| * [[https://cmor.llnl.gov/|CMOR]]: CMOR (//Climate Model Output Rewriter//) is used to produce CF-compliant netCDF files | * [[https://cmor.llnl.gov/|CMOR]]: CMOR (//Climate Model Output Rewriter//) is used to produce CF-compliant netCDF files |
| * ''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'', ''pynco'' |
| * [[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]] |
| * 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://www.cvxpy.org/|cvxpy]]: an open source Python-embedded modeling language for convex optimization problems |
| * [[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'' |
| * See also //scikit-learn// | * See also //scikit-learn// |
| * [[https://github.com/TEOS-10/GSW-python|gsw]]: Python implementation of the Thermodynamic Equation Of Seawater | * [[https://github.com/TEOS-10/GSW-python|gsw]]: Python implementation of the Thermodynamic Equation Of Seawater |
| * see also //seawater// | * See also //seawater// |
| * [[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://github.com/mapado/haversine|haversine]]: calculate the distance (in various units) between two points on Earth using their latitude and longitude |
| | * See also ''[[https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html|haversine_distances]] @ scikit-learn'' |
| * [[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 |
| * [[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 ''pynco'', ''cdo'' |
| * [[https://github.com/pydata/numexpr|NumExpr]]: Fast numerical expression evaluator for NumPy | * [[https://github.com/pydata/numexpr|NumExpr]]: Fast numerical expression evaluator for NumPy |
| * [[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 |
| | * 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]'' |
| * [[http://pandas.pydata.org/|pandas]]: Python Data Analysis Library | * [[http://pandas.pydata.org/|pandas]]: Python Data Analysis Library |
| * [[https://pyleoclim-util.readthedocs.io/|pyleoclim]]: a Python package designed for the analysis of paleoclimate data | * [[https://pyleoclim-util.readthedocs.io/|pyleoclim]]: a Python package designed for the analysis of paleoclimate data |
| * **Wait** till it can be installed with ''conda'' ([[https://github.com/LinkedEarth/Pyleoclim_util/discussions/205|Why I'm not installing Pyleoclim yet]]) | * **Wait** till it can be installed with ''conda'' ([[https://github.com/LinkedEarth/Pyleoclim_util/discussions/205|Why I'm not installing Pyleoclim yet]]) |
| | * [[https://www.pymoo.org/|pymoo]]: multi-objective Optimization in Python |
| | * [[https://pynco.readthedocs.io/|pynco]]:Python bindings for NCO |
| | * See also ''nco'', ''cdo'', ''python-cdo'' |
| * [[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://www.tensorflow.org/|tensorflow-mkl]]: an end-to-end open source machine learning platform | * [[https://www.tensorflow.org/|tensorflow-mkl]]: an end-to-end open source machine learning platform |
| * [[https://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version | * [[https://anaconda.org/anaconda/tensorflow-mkl|tensorflow-mkl]] will install the **CPU**-based (**not GPU**) version |
| * [[https://github.com/tqdm|tqdm]]: make your loops show a smart progress meter | * [[https://github.com/tqdm/tqdm|tqdm]]: make your loops show a smart progress meter |
| * [[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://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 | * See also ''pandas'', ''XlsxWriter'', ''openpyxl'' |
| * ''xoa'' is the successor of [[http://www.ifremer.fr/vacumm/|vacumm]] (vacumm does **not** support Python3) | * [[https://xoa.readthedocs.io/|xoa]]: xarray-based ocean analysis library |
| | * ''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. |
