Displaying “tutorial” tags
Author: Dani Arribas-Bel & Contexily Contributors
Welcome to the taster guide for contextily, the package for contextual tiles in Python. In this notebook, we will show the basic functionality available in contextily, a package to work with web-tiles for background maps. To do that, we will use additional data to illustrate contextily can be integrated ...more
Welcome to the taster guide for contextily, the package for contextual tiles in Python. In this notebook, we will show the basic functionality available in contextily, a package to work with web-tiles for background maps. To do that, we will use additional data to illustrate contextily can be integrated with other libraries such as geopandas and rasterio.
Author: Dask Developers
Dask is a parallel computing library that scales the existing Python ecosystem. This tutorial will introduce Dask and parallel data analysis more generally.
Author: GeoCat
Affiliation: NCAR
The examples below show GeoCAT-comp functions being utilized in real-world use cases. They also demonstrate how GeoCAT-comp can be used to make plots with Matplotlib (using Cartopy) and PyNGL (work in progress).
Author: HoloViz developers
The user guide provides a detailed introduction to the API and features of hvPlot. In the Introduction you will learn how to activate the plotting API and start using it. Next you will learn to use the API for tabular data and get an overview of the types of plots you can generate and how to customize ...more
The user guide provides a detailed introduction to the API and features of hvPlot. In the Introduction you will learn how to activate the plotting API and start using it. Next you will learn to use the API for tabular data and get an overview of the types of plots you can generate and how to customize them; including how to customize interactivity using widgets. Next is an overview on how to display and save plots in the notebook, on the commandline, and from a script. Another section will introduce you to generating subplots from your data. Once the basics are covered you can learn how to use the plotting API for specific types of data including streaming data, gridded data network graphs, geographic data, and timeseries data.
Author: the Matplotlib development team
This page contains more in-depth guides for using Matplotlib. It is broken up into beginner, intermediate, and advanced sections, as well as sections covering specific topics.
Author: MetPy developers
Affiliation: Unidata
This collection of tutorials (under development) demonstrates the use of MetPy to perform common meteorological tasks.
Author: Anonymous
Affiliation: Unidata
MetPy is a modern meteorological open-source toolkit for Python. It is a maintained project of Unidata to serve the academic meteorological community. MetPy consists of three major areas of functionality: plots, calculations, and file i/o.
Author: Anonymous
Affiliation: Unidata
Unidata Numpy tutorial that covers how to create an array of ‘data’, perform basic calculations on this data using python math functions, and slice and index the array.
Author: MapBox
This document explains how to use Rasterio to read existing files and to create new files. Some advanced topics are glossed over to be covered in more detail elsewhere in Rasterio’s documentation.
Author: Anonymous
Affiliation: Unidata
An overview on Siphon from the Unidata Python Workshop that: uses Siphon to access a THREDDS catalog, filters data, and uses Siphon to perform remote data access.
Author: Anonymous
Affiliation: Unidata
An introduction to Xarray through the Unidata Python Workshop that asks, "What is XArray and how does XArray fit in with Numpy and Pandas?"" by creating a DataArray, openning netCDF data using XArray, and subsetting the data.
Author: Xarray Developers
A collection of tutorials provided by the Xarray developers.
Author: Hanna Asefaw, Lisa Tauxe, Brendan Cych
Affiliation: Scripps Institution of Oceanography
Python Programming for Earth Science Students
Author: Nikolay Koldunov
Affiliation: Alfred Wegener Institute for Polar and Marine Research
This is a short overview of how Python is used in science and particularly in geosciences targeting people who already know programming (e.g. Matlab).
