.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "source/auto_examples/discovery/skip_improve.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_source_auto_examples_discovery_skip_improve.py: IMPROVE Data ----------- This example shows how to get IMPROVE data for the system located at ARM's Southern Great Plains site. .. GENERATED FROM PYTHON SOURCE LINES 9-31 .. code-block:: Python import act import matplotlib.pyplot as plt # Pull the data using the site_id from IMPROVE # https://views.cira.colostate.edu/adms/Pub/SiteSummary.aspx?dsidse=10001&siidse=244 ds = act.discovery.get_improve_data(site_id='244', start_date='1/1/2023', end_date='12/31/2023') # Remove all data that's set to the FillValue ds = ds.where(ds['aluminum_fine'] != ds['aluminum_fine'].attrs['_FillValue']) display = act.plotting.TimeSeriesDisplay(ds, figsize=(10, 6)) display.plot('aluminum_fine') # Print out the known problems documented by IMPROVE print(ds.attrs['site_problems']) # Write out the data to netCDF and csv ds.to_netcdf('./sgpimprove.20230101.nc') ds.to_dataframe().to_csv('sgpimprove.20230101.csv') plt.show() .. _sphx_glr_download_source_auto_examples_discovery_skip_improve.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: skip_improve.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: skip_improve.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: skip_improve.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_