nyc-open-data
There are 9 repositories under nyc-open-data topic.
mebauer/data-analysis-using-python
Data Analysis Using Python: A Beginner’s Guide Featuring NYC Open Data.
josh-grasso/NYC_Residential_Real_Estate
Buying a home in NYC, what Neighborhoods are the best value? This project seeks to understand the fundamental factors that explain differences in residential real estate prices across NYC.
bklynate/nycjobportal
[WIP] Building a New York City job portal using the NYC OpenData Jobs API:
mkupisie/Clustering-geodemographic_classification_of_NYC_using_K-means_geopandas_sklearn
Conducting geodemographic classification for ethnic groups in NYC using K-means algorithm available in sklearn.cluster module.
p-disha/NYC-Open-Dataset-Analysis
Identified data types for each distinct column value on 1900 data sets. For each column, summarized semantic types present in the column, using Fuzzy Logic, Levenshtein distance. Identified & derived inference the 3 most frequent 311 complaint types by borough.
tejakiransirivella/CrashLens-NYC
CrashLens analyzes traffic accident data through visualizations (histograms, pie charts, line plots, scatter plots) and DBSCAN clustering to identify accident hotspots. It includes data cleaning and supports datasets from various locations, with a focus on NYC crash data.
CyberTokyo112/data-analysis-using-python
Developed a comprehensive exploratory data analysis (EDA) of a vehicle repairs dataset, uncovering patterns in repair types, costs, and vehicle platforms. Includes data cleaning, insights extraction, tag generation from free-text fields, and saving of cleaned datasets for further analysis.
Harish-34/renovation-trend-analysis
Interactive Streamlit dashboard analyzing NYC renovation permits using NLP, clustering, time-series trends, and ML models. Includes keyword extraction, category prediction, PCA plots, and exportable visuals.
thetechleila/NYC-K-8-Public-School-Student-Performance-2016-2024
EDA to find insights, trends and patterns among the NYC K-8 Public School student academic performance and population to determine which factors may have impacted educational outcomes after the Covid19 Lockdown.