Chicago Crime Analysis

2013314025 서장영

1. Data SearchingSource https://data.cityofchicago.org/view/5cd6-ry5g

TitleChicago crime 2001 ~

Filtered by Date2016-08-01 ~2016–11-24

This dataset has rows of 87000

2. Data preparation

I deleted some useless variables(like ID, block, iUCR, Beat, FBI cord, etc..)

I change my record to analysis easy.(like change TRUE to 1, change FALSE to 0)

1. Proportion of Domestic crime

Domestic crime is just 15%

X axis = domestic or notY axis = proportion

2. Crime occurrence – commu-nity

X axis = Community of ChicagoY axis = Crime occurrence

3. Crime occurrence – Primary.-Type

X axis = crime type ( but omitted because of axis length )Y axis = crime occurrence

4. Crime type visualization

Used package :“ggplot2”

X axis = Fre-quencyY axis = crime type

5. Crime description word cloud

Used packages :“wordcloud”“KoNlp”“tm”

There are too many value in Crime Description

So, I make it into wordcloudWordcloud is good tool to do textmining.

6. Location wordcloudI used wordcloud methodWithout extractNoun function

This is crime location

Emphasised word : Street, Residence, Side walk

7. Time series

X axis = Crime dateY axis = occurrenceThe number of crime is decreased in November than August

8. Map Visualization

Used packages :“ggmap”“ggplot2”

This is Map of ChicagoWith red point(=Crime)

8. Map Visualization

Used packages :“ggmap”“ggplot2”

This is Map of ChicagoWith red point(=Crime)

9. Crime Type – Arrest Propor-tion

X axis :Proportion of arrest

Y axis :Crime type.

There are big differ-ences between crime type

10. District Arrest proportionX axis :Arrest proportion

Y axis :District 1 ~ 31

11. Chisq-TestChisq – Test is only method I can use.

Because all of variables in my dataset is categorial

This result shows

Arrest and crime type is dependant

District and crime type is depen-

dant

Arrest and District is dependant

12. Verification

I execute chisq-Test one more on data set2015 May crime dataset.

And I deduce same re-sults.