Crime Against Women in India – Addressing 8 Questions Using rCharts, googleVis, and shiny

October 5, 2013
By

(This article was first published on Adventures in Analytics and Visualization, and kindly contributed to R-bloggers)

Recent crimes against women, specifically the 2012 gang rape in New Delhi of a 23 year old lady, have pushed this issue as a substantially significant one for Indians to deal with. In this post, I try to address 8 different questions regarding crime against women in India. (1). How have numbers in different types of crimes and percentage of different crimes changed over the past few years for the country as a whole and for individual States/Union Territories? This is answered using data available for 12 years (2001-2012). For rest of the questions, I focus on data from 2012. (2) At the States/Union territories level, how are different types of crimes related to each other, in terms of their correlations? (3) Which States/UTs have a higher incidence of different types of crimes? (4) How can different States/UTs be classified based on the nature and extent of crime occurring in them? In question 5 through 7,  I ask questions 2 through 4 again, but for different cities.  Question 8 – Can the States, Union Territories, and Cities be mapped along with their incidence levels of different crimes in 2012? 

Tools Used: Analysis has been done using R and visualizations have been developed using rCharts and googleVis. Interactivity has also been facilitated by the shiny server environment, thanks to RStudio. Other R libraries used include reshape2, plyr, and scales. Special thanks to Ramnath Vaidyanathan and @timelyportfolio for their super quick assistance with questions on rCharts. All datasets used for this post and the code for generating charts and shiny applications are available at github.

Given the length of the post and the number of charts, I decided avoid posting it completely here and have created a separate page on blogger. For the entire post, please visit: http://bit.ly/1937EN9 

To leave a comment for the author, please follow the link and comment on his blog: Adventures in Analytics and Visualization.

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