In this post I take a look at the gory crime scene across India to determine which states are the heavy weights in crimes. Who is the undisputed champion of rapes in a year? Which state excels in cruelty by husbands and the relatives to wives? Which state leads in dowry deaths? To get the answers to these questions I perform analysis of the state-wise crime data against women with the data from Open Government Data (OGD) Platform India. The dataset for this analysis was taken for the Crime against Women from OGD.
(Do see my post Revisiting crimes against women in India which includes an interactive Shiny app)
The data in OGD is available for crimes against women in different states under different ‘crime heads’ like rape, dowry deaths, kidnapping & abduction etc. The data is available for years from 2001 to 2012. This data is plotted as a scatter plot and a linear regression line is then fit on the available data. Based on this linear model, the projected incidence of crimes likes rapes, dowry deaths, abduction & kidnapping is performed for each of the states. This is then used to build a table of different crime heads for all the states predicting the number of crimes till the year 2018. Fortunately, R crunches through the data sets quite easily. The overall projections of crimes against as women is shown below based on the linear regression for each of these states
Projections over the next couple of years
The tables below are based on the projected incidence of crimes under various categories assuming that these states maintain their torrid crime rate. A cursory look at the tables below clearly indicate the Uttar Pradesh is the undisputed heavy weight champion in 4 of 5 categories shown. Maharashtra and Andhra Pradesh take 2nd and 3rd ranks in the total crimes against women and are significant contenders in other categories too.
A) Projected rapes in India
The top 3 heavy weights in projected rapes over the next 5 years are 1) Madhya Pradesh 2) Uttar Pradesh 3) Maharashtra
Full table: Rape.csv
B) Projected Dowry deaths in India
Full table: Dowry Deaths.csv
C) Kidnapping & Abduction
Full table: Kidnapping&Abduction.csv
D) Cruelty by husband & relatives
Full table: Cruelty by husbands_relatives.csv
E) Total crimes against women
Full table: Total crimes.csv
Here is a visualization of ‘Total crimes against women’ created as a choropleth map
The implementation for this analysis was done using the R language. The R code, dataset, output and the crime charts can be accessed at GitHub at crime-against-women
Directory structure
– R code
– dataset used
– output
– statewise-crime-charts
The analysis has been completely parametrized. A quick look at the implementation is shown below. A function state crime was created as given below
statecrime.R
This function (statecrime.R) does the following
a) Creates a scatter plot for the state for the crime head
b) Computes a best linear regression fir and draws this line
c) Uses the model parameters (coefficients) to compute the projected crime in the years to come
d) Writes the projected values to a text file
c) Creates a directory with the name of the state if it does not exist and stores the jpeg of the plot there.
statecrime <- function(indiacrime, row, state,crime) {
year <- c(2001:2012)
# Make seperate folders for each state
if(!file.exists(state)) {
dir.create(state)
}
setwd(state)
crimeplot <- paste(crime,".jpg")
jpeg(crimeplot)
# Plot the details of the crime
plot(year,thecrime ,pch= 15, col="red", xlab = "Year", ylab= crime, main = atitle,
,xlim=c(2001,2018),ylim=c(ymin,ymax), axes=FALSE)
A linear regression line is fit using ‘lm’
# Fit a linear regression model
lmfit <-lm(thecrime~year)
# Draw the lmfit line
abline(lmfit)
The model parameters are then used to draw the line and also project for the next 5 years from 2013 to 2018
nyears <-c(2013:2018)
nthecrime <- rep(0,length(nyears))
# Projected crime incidents from 2013 to 2018 using a linear regression model
for (i in seq_along(nyears)) {
nthecrime[i] <- lmfit$coefficients[2] * nyears[i] + lmfit$coefficients[1]
}
The projected data for each state is appended into an appropriate file which is then used to display the tables at the top of this post
# Write the projected crime rate in a file
nthecrime <- round(nthecrime,2)
nthecrime <- c(state, nthecrime, "\n")
print(nthecrime)
#write(nthecrime,file=fileconn, ncolumns=9, append=TRUE,sep="\t")
filename <- paste(crime,".txt")
# Write the output in the ./output directory
setwd("./output")
cat(nthecrime, file=filename, sep=",",append=TRUE)
The above function is then repeatedly called for each state for the different crime heads. (Note: It is possible to check the read both the states and crime heads with R and perform the computation repeatedly. However, I have done this the manual way!)
crimereport.R
# 1. Andhra Pradesh
i <- 1
statecrime(indiacrime, i, "Andhra Pradesh","Rape")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Kidnapping& Abduction")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Dowry Deaths")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Assault on Women")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Insult to modesty")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Cruelty by husband_relatives")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Imporation of girls from foreign country")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Immoral traffic act")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Dowry prohibition act")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Indecent representation of Women Act")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Commission of Sati Act")
i <- i+38
statecrime(indiacrime, i, "Andhra Pradesh","Total crimes against women")
...
...
and so on for all the states
Charts for different crimes against women
1) Uttar Pradesh
The plots for Uttar Pradesh are shown below
Rapes in UP
Dowry deaths in UP
Cruelty by husband/relative
Total crimes against women in Uttar Pradesh
You can find more charts in GitHub by clicking Uttar Pradesh
2) Maharashtra : Some of the charts for Maharashtra
Rape
Kidnapping & Abduction
Total crimes against women in Maharashtra
More crime charts for Maharashtra
Crime charts can be accessed for the following states from GitHub ( in alphabetical order)
3) Andhra Pradesh
4) Arunachal Pradesh
5) Assam
6) Bihar
7) Chattisgarh
8) Delhi (Added as an exception based on its notoriety)
9) Goa
10) Gujarat
11) Haryana
12) Himachal Pradesh
13) Jammu & Kashmir
14) Jharkhand
15) Karnataka
16) Kerala
17) Madhya Pradesh
18) Manipur
19) Meghalaya
20) Mizoram
21) Nagaland
22) Odisha
23) Punjab
24) Rajasthan
25) Sikkim
26) Tamil Nadu
27) Tripura
28) Uttarkhand
29) West Bengal
The code, dataset and the charts can be cloned/forked from GitHub at crime-against-women
Let me know if you find any interesting patterns in the data.
Thoughts, comments welcome!
See also
My book ‘Practical Machine Learning with R and Python’ on Amazon
A peek into literacy in India: Statiscal learning with R
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