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fagan2888's Projects

tushare icon tushare

TuShare is a utility for crawling historical data of China stocks

tutorial_311_trees_p1 icon tutorial_311_trees_p1

Using NYC 311 data, Jonathan Auerbach and Chris Eshleman show how to use Bayesian methods to understand government service demand using storms, which serve as cleanly defined natural experiments. Part one in a two-part brings together NYC 311 data and Census data to set the stage for powerful statistical research.

tutorial_311_trees_p2 icon tutorial_311_trees_p2

Using NYC 311 data, Jonathan Auerbach and Chris Eshleman show how to use Bayesian methods to understand government service demand using storms, which serve as cleanly defined natural experiments. Part two brings together uncovers valuable insight for municipal policymakers.

tutorial_acs_rank icon tutorial_acs_rank

Ranking and scoring variables from the ACS 5 Year with non-profit case study

tutorial_biz_dynamics icon tutorial_biz_dynamics

Using the Census Bureau's Business Dynamics API, DataScience.com has developed a tutorial on business survival rates using Python

tutorial_earthgenome icon tutorial_earthgenome

Earth Genome describes how environmental data can be used to inform industry decision making and illustrates how to get started with Digital Elevation Model (DEM) data

tutorial_mapbox_part2 icon tutorial_mapbox_part2

Part 2 of a Commerce Data Usability Project tutorial on animating atmospheric rivers on web maps. Produced by Mapbox.

tutorial_nist_nvd icon tutorial_nist_nvd

How often should we update our software to stay secure? The National Institute of Standards and Technology (NIST) maintains a database of reported vulnerabilities. We can take a look and try to get some answers.

tutorial_pto icon tutorial_pto

United States and Trademark Office Data Usability Project Tutorial

tutorials icon tutorials

tutorials that may or may not turn into a book

tutorials-3 icon tutorials-3

Jupyter notebook tutorials from QuantConnect website for Python, Finance and LEAN.

tweetsndrugsncities icon tweetsndrugsncities

Detect drug activity in cities based on tweets . Using spatial join of geotagged tweets with 50 cities of America to calculate the drug usage rate in the city which is total number of drug tweets belonging to the city divided by the population of the city.

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