| Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision |
| other:uvcdat:cdat_conda:cdat_8_2_1 [2023/07/10 15:18] – [Extra packages list] added xlrd and openpyxl jypeter | other:uvcdat:cdat_conda:cdat_8_2_1 [2023/12/19 13:42] – [Extra packages list] Added rasterio and rioxarray jypeter |
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| * [[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 |
| * ''conda install -n cdatm19_py3 -c conda-forge cmor'' | * ''conda install -n cdatm19_py3 -c conda-forge cmor'' |
| * Get version number with: ''python -c 'from cmor import *; print( (CMOR_VERSION_MAJOR, CMOR_VERSION_MINOR, CMOR_VERSION_PATCH) )' '' | |
| * <wrap hi>Warning!</wrap> [[https://github.com/PCMDI/cmor/issues/449|CMOR currently requires Python 2.7]] | |
| |
| * [[http://scitools.org.uk/cartopy/|cartopy]]: a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses | * [[http://scitools.org.uk/cartopy/|cartopy]]: a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses |
| </WRAP> | </WRAP> |
| |
| | * [[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 |
| * [[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://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://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'' |
| * [[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 |
| * need to install ''eccodes'' and ''python-eccodes'' ([[https://github.com/ecmwf/eccodes-python/issues/56|details]]) | * need to install ''eccodes'' and ''python-eccodes'' ([[https://github.com/ecmwf/eccodes-python/issues/56|details]]) |
| * see also ''cfgrib'' and ''pygrib'' | * see also ''cfgrib'' and ''pygrib'' |
| | * [[https://ajdawson.github.io/eofs/|eofs]]: a Python package for EOF analysis of spatial-temporal data |
| * [[https://docs.esmvaltool.org/en/latest/|ESMValTool]]: Earth System Model Evaluation Tool | * [[https://docs.esmvaltool.org/en/latest/|ESMValTool]]: Earth System Model Evaluation Tool |
| * not installed yet (March 2022) because it required download of 302 Mb extra packages and a downgrade of gdal | * not installed yet (March 2022) because it required download of 302 Mb extra packages and a downgrade of gdal |
| | * [[https://flox.readthedocs.io/|flox]]: fast & furious //GroupBy// reductions for dask.array |
| | * See also |
| | * [[https://xarray.dev/blog/flox|flox: Faster GroupBy reductions with Xarray]] |
| | * [[https://flox.readthedocs.io/en/latest/implementation.html|Parallel Algorithms]] |
| * [[http://ferret.pmel.noaa.gov/Ferret/documentation/pyferret|pyferret]] and ''ferret_datasets'': Ferret encapsulated in Python | * [[http://ferret.pmel.noaa.gov/Ferret/documentation/pyferret|pyferret]] and ''ferret_datasets'': Ferret encapsulated in Python |
| * [[https://github.com/PBrockmann/ipython_ferretmagic|ipython_ferretmagic]]: IPython notebook extension for ferret | * [[https://github.com/PBrockmann/ipython_ferretmagic|ipython_ferretmagic]]: IPython notebook extension for ferret |
| * [[https://jupyterlab.readthedocs.io/|jupyterlab]]: the next-generation web-based user interface for Project Jupyter | * [[https://jupyterlab.readthedocs.io/|jupyterlab]]: the next-generation web-based user interface for Project Jupyter |
| * [[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://mpltern.readthedocs.io/|mpltern]]: a Python plotting library based on Matplotlib specifically designed for ternary plots | * [[https://mpltern.readthedocs.io/|mpltern]]: a Python plotting library based on Matplotlib specifically designed for ternary plots |
| * [[https://nc-time-axis.readthedocs.io/en/stable/|nc-time-axis]]: a package that enables making plots in matplotlib with axes made up of ''cftime.datetime'' dates with any calendar type | * [[https://nc-time-axis.readthedocs.io/en/stable/|nc-time-axis]]: a package that enables making plots in matplotlib with axes made up of ''cftime.datetime'' dates with any calendar type |
| * [[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://rasterio.readthedocs.io/|rasterio]]: access to geospatial raster data |
| | * [[https://corteva.github.io/rioxarray/|rioxarray]]: ''rasterio'' xarray extension |
| * [[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 |
| * [[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://github.com/SatAgro/suntime|suntime]]: simple sunset and sunrise time calculation python library | * [[https://github.com/SatAgro/suntime|suntime]]: simple sunset and sunrise time calculation python library |
| * **Warning**: not available in conda, use ''pip install suntime'' | * **Warning**: not available in conda, use ''pip install suntime'' |
| | * [[https://github.com/fbdesignpro/sweetviz|Sweetviz]] is pandas based Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. |
| * [[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://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://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! |
| * [[https://xcdat.readthedocs.io/|xcdat]]: xarray extended with Climate Data Analysis Tools | * See also: ''flox'', ''xcdat'', ''rioxarray'', ... |
| | * [[https://xcdat.readthedocs.io/|xcdat]]: Xarray extended with Climate Data Analysis Tools |
| * [[https://xclim.readthedocs.io/|xclim]]: an operational Python library for climate services, providing numerous climate-related indicator tools with an extensible framework for constructing custom climate indicators, statistical downscaling and bias adjustment of climate model simulations, as well as climate model ensemble analysis tools. | * [[https://xclim.readthedocs.io/|xclim]]: an operational Python library for climate services, providing numerous climate-related indicator tools with an extensible framework for constructing custom climate indicators, statistical downscaling and bias adjustment of climate model simulations, as well as climate model ensemble analysis tools. |
| | * [[https://xesmf.readthedocs.io/|xESMF]]: Universal Regridder for Geospatial Data |
| * [[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]] |
| * Install with: ''pip install xgrads'' | |
| * [[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/en/latest/|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 [[http://www.ifremer.fr/vacumm/|vacumm]] (vacumm does **not** support Python3) |
| | * [[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. |
| |
| ==== Removed packages ==== | ==== Removed packages ==== |
