Nicole Keeney (nicolejkeeney)

nicolejkeeney

Geek Repo

Location:Colorado, USA

Home Page:nicolekeeney.com

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Nicole Keeney's repositories

icesat2-book

Interactive Jupyter Book for wrangling, visualizing, and analyzing ICESat-2 sea ice thickness data

Language:Jupyter NotebookLicense:MITStargazers:14Issues:1Issues:2

fluxnet_ESI

Using atmospheric humidity deficits to discern soil moisture deficits. Python code repository for Baldocchi et al. (2021)

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:5Issues:1Issues:0

prism

Download and grid PRISM climate data to an input shapefile

Language:RLicense:MITStargazers:2Issues:1Issues:0

aggregate_gridMET

Aggregate gridMET data by census tract

Language:RLicense:MITStargazers:1Issues:1Issues:0

wind_erosion_model_calibration

Calibration of a wind erosion model using remote sensing-derived vegetation characteristics

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:1Issues:1Issues:0

climate-data-science-eval

An evaluation of climate data science skills in Python

Language:Jupyter NotebookLicense:MITStargazers:0Issues:0Issues:0

cookiecutter-science-project

Cookiecutter template for science analysis projects

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

dust_landuse_analysis

Analyzing dust concentration by land use type in coccidioidomycosis endemic regions in the CA Central Valley

Language:HTMLLicense:GPL-3.0Stargazers:0Issues:1Issues:0
Language:SCSSStargazers:0Issues:0Issues:0

geo-py-docker

Basic files and instructions for setting up docker container (with JupyterLab) for python projects. Based on pangeo docker workflow

Language:DockerfileLicense:GPL-3.0Stargazers:0Issues:1Issues:0

google_drive_python

Useful notebooks and instructions for working with google drive and google colab in python

Language:Jupyter NotebookLicense:MITStargazers:0Issues:1Issues:0

is2-streamlit-app

Streamlit web app for displaying ICESat-2 gridded data

Language:PythonLicense:MITStargazers:0Issues:2Issues:0

nicolejkeeney.github.io

Nicole's personal website

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

read_IMPROVE_data

Notebooks for working with IMPROVE aerosol monitor data to (1) derive mean monthly dust concentrations and (2) visualize monitor locations in California using an interactive folium map

Language:Jupyter NotebookStargazers:0Issues:1Issues:0