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A data analytics project to visualize and explore the Chicago Crimes Dataset

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DATA ANALYTICS - PROJECT

FORECASTING CRIME - BURGLARY USING ARIMA

Contributors:

  • Nikhil KR (PES2201800044)
  • Roshan Daivajna (PES2201800372)
  • Ruchira R Vadiraj (PES2201800602)

Description:

  • The link to the dataset can be found here (https://catalog.data.gov/dataset/crimes-2001-to-present-398a4).
  • The data is first acquired from the given link and is pre-processed.
  • The PartI.py file handles data acquisition, data pre-processing and exploratory data analysis.
  • The refined processed data is saved as a CSV file (output.csv - Download locally).
  • The second part of the analysis is done in R due to the packages available and ease of use.
  • The PartII.R file gets the output.csv file and model selection and forecasting is done.
  • The final result obtained is shown as the output, with the error rates.

NOTE :

  • Forecasting is done on a particular type of crime, Burglary.
  • Data aggregation and further model selection is done in R due to easy data handling provided by R dataframes.

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A data analytics project to visualize and explore the Chicago Crimes Dataset

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  • Python 68.5%
  • R 31.5%