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other:uvcdat:cdat_conda:cdat_8_2_1 [2023/10/03 08:52] jypeter [Extra packages list] xgrads can now be installed with conda |
other:uvcdat:cdat_conda:cdat_8_2_1 [2023/12/15 15:26] jypeter [Extra packages list] Added Sweetviz and AutoViz |
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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 | ||
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</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'' | ||
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* [[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 | ||
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* [[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 | ||
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* ''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://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 ==== |