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geospatial_course_unitn

repository with code and documentation for the course "Geospatial analysis and representation for data science" for the students in data science of the university of Trento

google-earth-engine-python-examples

Various examples for Google Earth Engine in Python using Jupyter Notebook

gridding

Generic gridding routine for satellite data with corner coordinates supplied. in the Scientific Development Phase, use at your own risk and let authors know about issues (quick&dirty was the way!)

h5py

HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.

image_keras

Building an image classifier using keras

introduction_to_xarray

ipython

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

machine-learning

Workshop on Machine Learning in Python

matplotlib

matplotlib: plotting with Python

modis-python-suite

Python module to download modis data

modis_restservice_qc_filter_python

Access data from the MODIS web service and perform quality filtering in Python

netcdf4-python

netcdf4-python: python/numpy interface to the netCDF C library

numpy-tutorial

Numpy beginner tutorial

ogr-geopandas-tutorial

Material for distance learning course on "Geoprocessing using Python"

osgeopy-code

Code for the book Open source geoprocessing with Python

planetarycomputerexamples

Examples of using the Planetary Computer

py4dvar

Python 4-dimensional variational data assimilation tool

python-

python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

python-for-earth-science-students

python-for-gis-progression-path

Progression path for a GIS analyst who wants to become proficient in using Python for GIS: from apprentice to guru

python-jupyter-notebooks

Some sample python notebooks

python-practical-application-on-climate-variability-studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

python-programming-exercises

100+ Python challenging programming exercises

python-tutorial

A Python 3 programming tutorial for beginners.

python-workshop

A series of Jupyter Notebooks on exploring Unidata technology with Python. See website for more information.

python_for_image_processing_apeer

https://www.youtube.com/playlist?list=PLHae9ggVvqPgyRQQOtENr6hK0m1UquGaG

python_for_microscopists

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

raster-2019

contents for 2019 raster tutorial