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awesome-geospatial

Long list of geospatial tools and resources

bashmarks

Directory bookmarks for the shell

bib-publication-list

Interactive publications lists with JavaScript + Bibtex

bib2xhtml

Convert BibTeX references into XHTML

bibliometrix

An R-tool for comprehensive science mapping analysis. A package for quantitative research in scientometrics and bibliometrics.

bokeh

Interactive Web Plotting for Python

bokeh-notebooks

Interactive Web Plotting with Bokeh in IPython notebook

bokeh_overview

5 min intro

bootstrap-social

:couple: Social Sign-In Buttons for Bootstrap

bootswatch

Themes for Bootstrap

calcat

California COVID Assessment Tool

california-coronavirus-data

The Los Angeles Times' independent tally of coronavirus cases in California.

cenpy

Explore and download data from Census APIs

clusterpy

Library of spatially constrained clustering algorithms

concentrationmetrics

A python library for the computation of various concentration, inequality and diversity indices

contextily

Context geo-tiles in Python

cookbook-code

Recipes of the IPython Cookbook, the definitive guide to high-performance scientific computing and data science in Python

course_test_59616

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

covid-policy-tracker

Systematic dataset of Covid-19 policy, from Oxford University

cv

Curriculum Vitae

datashader

Turns even the largest data into images, accurately.

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

engcomp1_offtheground

Learn to interact with Python and handle data with Python. Join the online course!

esda

statistics and classes for exploratory spatial data analysis

fit_mvpolya

Dirichlet-Multinomial (Multivariate Polya) Maximum Likelihood Estimate in Python

foodequityscore

food equity score project

foss4g14

PySAL Workshop @FOSS4G14

fuzzywuzzytest