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A-TALE-OF-THREE-CITIES

microsoft / A-TALE-OF-THREE-CITIES

Star 85

Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.

visualization data r azure leaflet geospatial opendata eda sparksql workshop-materials sparkr anomalydiscovery time-series-analysis anomaly-detection databricks-notebooks timeseries-forecasting azure-databricks datascience-machinelearning aiforsocialgood 311-data
  • Updated May 3, 2021
  • R
Scooters-In-Austin-Data-Analysis

sheetalbongale / Scooters-In-Austin-Data-Analysis

Star 7

Project analyzing the City of Austin's Open Data for 8.4M shared scooter rides and also compare the city's 311 complaints about the same. Find insights about the popular spots for scooter rides and the correlation if these areas also have more scooter complaints and more | Python Project 1 | UT Data Analysis and Visualization Nov 2019 - May 2020

api plotly data-visualization geopandas census-tract scooters 311-data austin-data-analysis
  • Updated Sep 22, 2020
  • Jupyter Notebook

p-disha / NYC-Open-Dataset-Analysis

Star 1

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.

visualization json big-data python3 pyspark levenshtein-distance matplotlib fuzzy-logic data-profiling big-data-analytics nyc-opendata nyc-open-data 311-data
  • Updated Apr 15, 2020
  • Python
DC-311-Service-Requests-Household-Income-Relationship

pkhiyara / DC-311-Service-Requests-Household-Income-Relationship

Star 0

A Python data manipulation and analysis project that examines the relationship between the number of 311 service request calls placed and the average household income of Washington D.C. residents, based on the eight wards that constitute the city, to find a potential correlation through the use of Pandas dataframes and Matplotlib visualizations.

python data pandas-dataframe jupyter-notebook pandas data-visualization data-analysis matplotlib jupyter-notebooks washington-dc income pandas-dataframes dataanalysis pandas-library servicerequest datamanipulation matplotlib-pyplot 311call 311-data
  • Updated Dec 28, 2019
  • Jupyter Notebook

thaophuongtran / 311-Covid-Related-Requests-in-Kansas-City-MO

Star 0

In response to the widespread of COVID-19, citizens sought information and support from their city governance through the 311 non-emergency service request system. Our analysis showed that the pandemic has led to a considerable decline in the aggregate number of 311 calls in Kansas City; however, “Public Safety”, “Public Health”, “Trash/Recyclin…

kcmo 311-data covid-19 crisis-response
  • Updated Mar 26, 2023
  • R

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