The U.S. Census API Call Builder, a CGR data science team project, aids in pulling data via the Census API.
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Updated
Feb 28, 2017 - HTML
The U.S. Census API Call Builder, a CGR data science team project, aids in pulling data via the Census API.
This a dashboard showing the self response rates by state, how they compare to the response rates in 2010, and the percentage of households responding via internet vs traditional mail. Tech used: VueJS, D3.JS and TopoJSON.
A data project exploring whether city population sizes are correlated with preventative health behaviors and visualizations of the relationships.
Performed ETL on data collected from various sources (csvs downloaded from various sources and the US Census API) to create a single database, in order to explore questions surrounding the "Defund the Police" movement. Specifically looking at data regarding police-involved shootings and state budgets.
Data science project for feature engineering and classification using as case study the Census Income dataset
Exploratory Data Analysis and Classification Modelling of the Adult Income Dataset aka the Census Income Dataset
Strong-Side-Left-Side Team Project Website Repo
In this work we attempt to fill in the gap years for the US Agricultural Census in Utah counties. Open source data from NOAA, Agricultural Census, and BLS are used leveraging Machine Learning methods and models.
A Website auto-created by Processing using US Census data
Analytics dashboard with aggregate user metrics by state/county. Preview:
Final Paper for NYU Data Bootcamp Fall 2018 Course
Using Spark to query a large dataset of recycling cart tip data from the Cincinnati Open Data Portal
EDA on #Kenya2019Census
Cleaned data from the 2016-2017 AIGA Design Census surveys
🐍🤯 Utilising Python w/ Pandas and Jupyter to create Dataframes to read in 1994 US Census data to compile an Analytical Base Table (ABT) which displays a Categorical and Continuous Data Quality Report. Dealing with Data Quality Issues (DQIs) such as Cardinality Issues, Outliers and Missing Values.
This repository was created by two students from the Harvard Kennedy School on behalf of the City of Rochester, NY. The code in this repository uses Census PUMS data to quantify the right-sized affordable housing gap in Rochester.
Get Started with Data Science. Understand how to apply different Data Science methods to solve real-world problems.
projects done with R, census data, and the tidycensus library
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