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Description
In order to keep the content on the PyAOS website as up-to-date and relevant as possible, it would be useful to conduct a regular census (perhaps every year or two).
I'm thinking that the data (which would be made openly available in csv format at this GitHub repository) could be collected using Google Forms.
Here's what I'm thinking for questions:
(Multiple choice means you can only pick one of the options; checkbox means you can select as many as you like.)
Demographics
| Question | Type | Options |
|---|---|---|
| Age | Free text | |
| Gender: How do you identify? | Multiple choice | - Woman - Non-binary - Man - Other (free text) |
| Career stage | Multiple choice | - Undergraduate - Masters - PhD - Academic (within 5 years of highest qualification) - Academic (more than 5 years post highest qualification) - Industry / Professional (within 5 years) - Industry / Professional (more than 5 years) - Other (free text) |
| AOS discipline/s | Checkbox | - Atmospheric Aerosols - Atmospheric Chemistry - Atmospheric Dynamics - Atmospheric Radiation - Climate Change Processes - Climatology (excl. Climate Change Processes) - Cloud Physics - Meteorology - Biological Oceanography - Chemical Oceanography - Physical Oceanography - Paleoclimatology - Tropospheric and Stratospheric Physics - Modelling - AOS Research Software Engineer - AOS Research Computing Support - Other (free text) |
| Country of residence | Free text | Use 2-letter country code from this list |
| How long have you been using Python? | Multiple choice | - less than 1 year - 1-2 years - 2-5 years - 6-10 years - more than 10 years |
| What types of AOS data do you work with? | Checkbox | - Raster (i.e. multi-dimensional gridded data such as a regular time/latitude/longitude/depth grid) - Vector (i.e. discrete geometric locations that define the shape of a spatial point, line or polygon) - Tabular - Other (free text) |
| Which of those data types do you most commonly work with? | Multiple choice | - Raster (i.e. multi-dimensional gridded data such as a regular time/latitude/longitude/depth grid) - Vector (i.e. discrete geometric locations that define the shape of a spatial point, line or polygon) - Tabular - Other (free text) |
| What file formats are your AOS data stored in? | Checkbox | - netCDF - Zarr - GRIB - HDF - GeoTIFF - csv - GeoJSON - GeoPackage - Shapefile - MapInfo TAB - ESRI File Geodatabase - A custom binary format - Other (free text) |
| Which of those file formats do you most commonly work with? | Multiple choice | - netCDF - Zarr - GRIB - HDF - GeoTIFF - csv - GeoJSON - GeoPackage - Shapefile - MapInfo TAB - ESRI File Geodatabase - A custom binary format - Other (free text) |
| What computing platforms do you use for your AOS data science? | Checkbox | - Personal laptop/desktop - Supercomputer (e.g. run by your institution or a national facility) - Cloud (e.g. Amazon Web Services) - Other (free text) |
| Which of those computing platforms do you most commonly work on for your AOS data sciecne? | Multiple choice | - Personal laptop/desktop - Supercomputer (e.g. run by your institution or a national facility) - Cloud (e.g. Amazon Web Services) - Other (free text) |
| What development environments do you regularly use for your Python coding? | Checkbox | - Jupyter - PyCharm - Spyder - Notepad++ - Sublime Text - Vim - Other (free text) |
Main question (free text)
Writing Python code typically begins with importing various libraries that are either part of the Python standard library or that you've installed using the Python package installer (pip) or conda. Take a look back over five Python scripts / notebooks that you've written recently for AOS data science tasks and cut and paste below all the import statements that you used in those scripts / notebooks (please remove any duplicates). For example, your list might look something like:
import sys
import os
import argparse
import numpy as np
import xarray as xr
import iris
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import pyart
If you've imported any of your own modules, please include the libraries imported in those modules in your list too.
Are there any PyAOS libraries that aren't on your list from the last couple of months but that you've used previously and would like to highlight?