All Projects → willgeary → Covid Nyc Dasymetric Map

willgeary / Covid Nyc Dasymetric Map

Projects that are alternatives of or similar to Covid Nyc Dasymetric Map

Julia notebooks
Julia Jupyter/Colab Notebooks
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Dslt
Deep Regression Tracking with Shrinkage Loss
Stars: ✭ 55 (-3.51%)
Mutual labels:  jupyter-notebook
Pybkb v2
Python scripts that help me be a successfull meteorologist. (Python 2) For Python 3, use: https://github.com/blaylockbk/pyBKB_v3
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Voila Demo
Demo for voila
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Imagenet
Trial on kaggle imagenet object localization by yolo v3 in google cloud
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
A Week In Wild Ai
360 view on ai/ml/dl applications
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Ds and ml projects
Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Amazon Sagemaker Safe Deployment Pipeline
Safe blue/green deployment of Amazon SageMaker endpoints using AWS CodePipeline, CodeBuild and CodeDeploy.
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Sccaf
Single-Cell Clustering Assessment Framework
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Interpreting Decision Trees And Random Forests
Unwrapping decision trees and random forests to make them less of a black box
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Waveglow Vqvae
WaveGlow vocoder with VQVAE
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Rnn Walkthrough
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Endtoend Predictive Modeling Using Python
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Arabic poem generator
Generating Arabic poetry using Markov chains.
Stars: ✭ 55 (-3.51%)
Mutual labels:  jupyter-notebook
Codeforces Api
Tools for estimating problem difficulty, predictors rating trajectories, and tracking individual learning progress in algorithms.
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Paraphrase Generator
A paraphrase generator built using the T5 model which produces paraphrased English sentences.
Stars: ✭ 55 (-3.51%)
Mutual labels:  jupyter-notebook
Tensorflow Machine Learning Projects
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook
Covidnet Ct
COVID-Net Open Source Initiative - Models and Data for COVID-19 Detection in Chest CT
Stars: ✭ 57 (+0%)
Mutual labels:  jupyter-notebook
Clr
Stars: ✭ 1,087 (+1807.02%)
Mutual labels:  jupyter-notebook
Baidu dogs
百度西交第三届大数据比赛Baseline(全国第4名)
Stars: ✭ 56 (-1.75%)
Mutual labels:  jupyter-notebook

Dasymetric Map of COVID Cases in New York City

Follow some conversation around this on Twitter.

STOP mapping COVID case counts by zip code! 🙅‍♀️🚫

Zip codes come in varying shapes and sizes, introducing bias known as the Modifiable Areal Unit Problem (MAUP).

The maps below display population, tests and recorded COVID cases in NYC.

The maps on the left are a simple choropleth maps displaying raw counts by zip code.

The maps in the middle are dasymetric maps which redistribute raw counts from zip codes to residential buildings within the zip code proportionate to building volume, and then re-aggregates by equal area hexagon.

The maps on the right are smoothed version of the dasymetric hexagon grid maps using kernel density estimation.

alt text

COVID case counts should be accompanied by data on population and the total number of tests administered. It is flawed to draw conclusions about the spread of COVID without accounting for the number of tests administered. And it is flawed to aggregate this data by zip code.

There is some seriously flawed research going on right now which attempts to draw conclusions about how COVID spreads by simply overlying data on top of raw case counts by zip code. Please be aware of this!

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].