AS1-1 An Analytical Detective
Section 1 - Loading the Data
1.1
How many rows of data (observations) are in this dataset?
mvt <- read.csv("mvtWeek1.csv")
nrow(mvt)## [1] 1916411.2
How many variables are in this dataset?
ncol(mvt)## [1] 111.3
Using the “max” function, what is the maximum value of the variable “ID”?
max(mvt[,1])## [1] 91811511.4
What is the minimum value of the variable “Beat”?
min(mvt[,6])## [1] 1111.5
How many observations have value TRUE in the Arrest variable (this is the number of crimes for which an arrest was made)?
length(which(mvt$Arrest=="TRUE"))## [1] 155361.6
How many observations have a LocationDescription value of ALLEY?
length(which(mvt$LocationDescription=="ALLEY"))## [1] 2308Section 2 - Understanding Dates in R
In many datasets, like this one, you have a date field. Unfortunately, R does not automatically recognize entries that look like dates. We need to use a function in R to extract the date and time. Take a look at the first entry of Date (remember to use square brackets when looking at a certain entry of a variable).
2.1
In what format are the entries in the variable Date?
- Month/Day/Year Hour:Minute
- Day/Month/Year Hour:Minute
- Hour:Minute Month/Day/Year
- Hour:Minute Day/Month/Year
mvt$Date[1]## [1] 12/31/12 23:15
## 131680 Levels: 1/1/01 0:01 1/1/01 0:05 1/1/01 0:30 1/1/01 1:17 ... 9/9/12 9:502.2
Now, let’s convert these characters into a Date object in R. In your R console, type
DateConvert = as.Date(strptime(mvt$Date, "%m/%d/%y %H:%M"))This converts the variable “Date” into a Date object in R. Take a look at the variable DateConvert using the summary function.
What is the month and year of the median date in our dataset? Enter your answer as “Month Year”, without the quotes. (Ex: if the answer was 2008-03-28, you would give the answer “March 2008”, without the quotes.)
DateConvert = as.Date(strptime(mvt$Date, "%m/%d/%y %H:%M"))
summary(DateConvert)## Min. 1st Qu. Median Mean 3rd Qu.
## "2001-01-01" "2003-07-10" "2006-05-21" "2006-08-23" "2009-10-24"
## Max.
## "2012-12-31"2.3
Now, let’s extract the month and the day of the week, and add these variables to our data frame mvt. We can do this with two simple functions. Type the following commands in R:
mvt$Month = months(DateConvert)
mvt$Weekday = weekdays(DateConvert)This creates two new variables in our data frame, Month and Weekday, and sets them equal to the month and weekday values that we can extract from the Date object. Lastly, replace the old Date variable with DateConvert by typing:
mvt$Date = DateConvertUsing the table command, answer the following questions.
In which month did the fewest motor vehicle thefts occur?
mvt$Month = months(DateConvert)
mvt$Weekday = weekdays(DateConvert)
table(mvt$Month)##
## 一月 七月 九月 二月 八月 十一月 十二月 十月 三月 五月
## 16047 16801 16060 13511 16572 16063 16426 17086 15758 16035
## 六月 四月
## 16002 152802.4
On which weekday did the most motor vehicle thefts occur?
mvt$Month = months(DateConvert)
mvt$Weekday = weekdays(DateConvert)
table(mvt$Month)##
## 一月 七月 九月 二月 八月 十一月 十二月 十月 三月 五月
## 16047 16801 16060 13511 16572 16063 16426 17086 15758 16035
## 六月 四月
## 16002 152802.5
Each observation in the dataset represents a motor vehicle theft, and the Arrest variable indicates whether an arrest was later made for this theft. Which month has the largest number of motor vehicle thefts for which an arrest was made?
table(mvt$Arrest,mvt$Month)##
## 一月 七月 九月 二月 八月 十一月 十二月 十月 三月 五月
## FALSE 14612 15477 14812 12273 15243 14807 15029 15744 14460 14848
## TRUE 1435 1324 1248 1238 1329 1256 1397 1342 1298 1187
##
## 六月 四月
## FALSE 14772 14028
## TRUE 1230 1252Section 3 - Visualizing Crime Trends
3.1
Now, let’s make some plots to help us better understand how crime has changed over time in Chicago. Throughout this problem, and in general, you can save your plot to a file. For more information, this website very clearly explains the process.
First, let’s make a histogram of the variable Date. We’ll add an extra argument, to specify the number of bars we want in our histogram. In your R console, type
hist(mvt$Date, breaks=100)
Date <- as.numeric(mvt$Date)
hist(Date,breaks=100)
Looking at the histogram, answer the following questions.
In general, does it look like crime increases or decreases from 2002 - 2012?
- Increases
- Decreases
"Decrease"## [1] "Decrease"In general, does it look like crime increases or decreases from 2005 - 2008?
- Increases
- Decreases
"Decrease"## [1] "Decrease"3.2
Now, let’s see how arrests have changed over time. Create a boxplot of the variable “Date”, sorted by the variable “Arrest” (if you are not familiar with boxplots and would like to learn more, check out this tutorial). In a boxplot, the bold horizontal line is the median value of the data, the box shows the range of values between the first quartile and third quartile, and the whiskers (the dotted lines extending outside the box) show the minimum and maximum values, excluding any outliers (which are plotted as circles). Outliers are defined by first computing the difference between the first and third quartile values, or the height of the box. This number is called the Inter-Quartile Range (IQR). Any point that is greater than the third quartile plus the IQR or less than the first quartile minus the IQR is considered an outlier.
Does it look like there were more crimes for which arrests were made in the first half of the time period or the second half of the time period? (Note that the time period is from 2001 to 2012, so the middle of the time period is the beginning of 2007.)
- First half
- Second half
3.3
Let’s investigate this further. Use the table function for the next few questions.
For what proportion of motor vehicle thefts in 2001 was an arrest made?
Note: in this question and many others in the course, we are asking for an answer as a proportion. Therefore, your answer should take a value between 0 and 1.
table(mvt$Arrest,mvt$Year)##
## 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
## FALSE 18517 16638 14859 15169 14956 14796 13068 13425 11327 14796 15012
## TRUE 2152 2115 1798 1693 1528 1302 1212 1020 840 701 625
##
## 2012
## FALSE 13542
## TRUE 5502152/(2152+18517) ## [1] 0.10411733.4
For what proportion of motor vehicle thefts in 2007 was an arrest made?
1212/(13068+1212)## [1] 0.084873953.5
For what proportion of motor vehicle thefts in 2012 was an arrest made?
550/(550+13542)## [1] 0.03902924Since there may still be open investigations for recent crimes, this could explain the trend we are seeing in the data. There could also be other factors at play, and this trend should be investigated further. However, since we don’t know when the arrests were actually made, our detective work in this area has reached a dead end.
Section 4 - Popular Locations
4.1
Analyzing this data could be useful to the Chicago Police Department when deciding where to allocate resources. If they want to increase the number of arrests that are made for motor vehicle thefts, where should they focus their efforts?
We want to find the top five locations where motor vehicle thefts occur. If you create a table of the LocationDescription variable, it is unfortunately very hard to read since there are 78 different locations in the data set. By using the sort function, we can view this same table, but sorted by the number of observations in each category. In your R console, type:
sort(table(mvt$LocationDescription))Which locations are the top five locations for motor vehicle thefts, excluding the “Other” category? You should select 5 of the following options.
- Bank
- Gas Station
- Hotel/Motel
- Street
- Car Wash
- Restaurant
- Parking Lot/Garage (Non-Residential)
- Alley
- Driveway (Residential)
- Vacant Lot/Land
"Parking Lot/Garage (Non. Resid.), Alley, Gas Station, and Driveway - Residential"## [1] "Parking Lot/Garage (Non. Resid.), Alley, Gas Station, and Driveway - Residential"4.2
Create a subset of your data, only taking observations for which the theft happened in one of these five locations, and call this new data set “Top5”. To do this, you can use the | symbol. In lecture, we used the & symbol to use two criteria to make a subset of the data. To only take observations that have a certain value in one variable or the other, the | character can be used in place of the & symbol. This is also called a logical “or” operation.
Alternately, you could create five different subsets, and then merge them together into one data frame using rbind.
How many observations are in Top5?
Top5 = subset(mvt, LocationDescription=="STREET" | LocationDescription=="PARKING LOT/GARAGE(NON.RESID.)" | LocationDescription=="ALLEY" | LocationDescription=="GAS STATION" | LocationDescription=="DRIVEWAY - RESIDENTIAL")4.3
R will remember the other categories of the LocationDescription variable from the original dataset, so running table(Top5$LocationDescription) will have a lot of unnecessary output. To make our tables a bit nicer to read, we can refresh this factor variable. In your R console, type:
Top5$LocationDescription = factor(Top5$LocationDescription)If you run the str or table function on Top5 now, you should see that LocationDescription now only has 5 values, as we expect.
Use the Top5 data frame to answer the remaining questions.
One of the locations has a much higher arrest rate than the other locations. Which is it? Please enter the text in exactly the same way as how it looks in the answer options for Problem 4.1.
table(Top5$LocationDescription, Top5$Arrest)##
## FALSE TRUE
## ABANDONED BUILDING 0 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0 0
## AIRPORT EXTERIOR - SECURE AREA 0 0
## AIRPORT PARKING LOT 0 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0 0
## AIRPORT VENDING ESTABLISHMENT 0 0
## AIRPORT/AIRCRAFT 0 0
## ALLEY 2059 249
## ANIMAL HOSPITAL 0 0
## APARTMENT 0 0
## APPLIANCE STORE 0 0
## ATHLETIC CLUB 0 0
## BANK 0 0
## BAR OR TAVERN 0 0
## BARBERSHOP 0 0
## BOWLING ALLEY 0 0
## BRIDGE 0 0
## CAR WASH 0 0
## CHA APARTMENT 0 0
## CHA PARKING LOT/GROUNDS 0 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0 0
## CLEANING STORE 0 0
## COLLEGE/UNIVERSITY GROUNDS 0 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0 0
## COMMERCIAL / BUSINESS OFFICE 0 0
## CONSTRUCTION SITE 0 0
## CONVENIENCE STORE 0 0
## CTA GARAGE / OTHER PROPERTY 0 0
## CTA TRAIN 0 0
## CURRENCY EXCHANGE 0 0
## DAY CARE CENTER 0 0
## DEPARTMENT STORE 0 0
## DRIVEWAY - RESIDENTIAL 1543 132
## DRUG STORE 0 0
## FACTORY/MANUFACTURING BUILDING 0 0
## FIRE STATION 0 0
## FOREST PRESERVE 0 0
## GAS STATION 1672 439
## GOVERNMENT BUILDING/PROPERTY 0 0
## GROCERY FOOD STORE 0 0
## HIGHWAY/EXPRESSWAY 0 0
## HOSPITAL BUILDING/GROUNDS 0 0
## HOTEL/MOTEL 0 0
## JAIL / LOCK-UP FACILITY 0 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0 0
## LIBRARY 0 0
## MEDICAL/DENTAL OFFICE 0 0
## MOVIE HOUSE/THEATER 0 0
## NEWSSTAND 0 0
## NURSING HOME/RETIREMENT HOME 0 0
## OTHER 0 0
## OTHER COMMERCIAL TRANSPORTATION 0 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0 0
## PARK PROPERTY 0 0
## PARKING LOT/GARAGE(NON.RESID.) 13249 1603
## POLICE FACILITY/VEH PARKING LOT 0 0
## RESIDENCE 0 0
## RESIDENCE-GARAGE 0 0
## RESIDENCE PORCH/HALLWAY 0 0
## RESIDENTIAL YARD (FRONT/BACK) 0 0
## RESTAURANT 0 0
## SAVINGS AND LOAN 0 0
## SCHOOL, PRIVATE, BUILDING 0 0
## SCHOOL, PRIVATE, GROUNDS 0 0
## SCHOOL, PUBLIC, BUILDING 0 0
## SCHOOL, PUBLIC, GROUNDS 0 0
## SIDEWALK 0 0
## SMALL RETAIL STORE 0 0
## SPORTS ARENA/STADIUM 0 0
## STREET 144969 11595
## TAVERN/LIQUOR STORE 0 0
## TAXICAB 0 0
## VACANT LOT/LAND 0 0
## VEHICLE-COMMERCIAL 0 0
## VEHICLE NON-COMMERCIAL 0 0
## WAREHOUSE 0 04.4
On which day of the week do the most motor vehicle thefts at gas stations happen? (Monday~Sunday)
table(Top5$LocationDescription, Top5$Weekday)##
## 星期一 星期二 星期三
## ABANDONED BUILDING 0 0 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0 0 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0 0 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0 0 0
## AIRPORT EXTERIOR - SECURE AREA 0 0 0
## AIRPORT PARKING LOT 0 0 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0 0 0
## AIRPORT VENDING ESTABLISHMENT 0 0 0
## AIRPORT/AIRCRAFT 0 0 0
## ALLEY 320 323 317
## ANIMAL HOSPITAL 0 0 0
## APARTMENT 0 0 0
## APPLIANCE STORE 0 0 0
## ATHLETIC CLUB 0 0 0
## BANK 0 0 0
## BAR OR TAVERN 0 0 0
## BARBERSHOP 0 0 0
## BOWLING ALLEY 0 0 0
## BRIDGE 0 0 0
## CAR WASH 0 0 0
## CHA APARTMENT 0 0 0
## CHA PARKING LOT/GROUNDS 0 0 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0 0 0
## CLEANING STORE 0 0 0
## COLLEGE/UNIVERSITY GROUNDS 0 0 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0 0 0
## COMMERCIAL / BUSINESS OFFICE 0 0 0
## CONSTRUCTION SITE 0 0 0
## CONVENIENCE STORE 0 0 0
## CTA GARAGE / OTHER PROPERTY 0 0 0
## CTA TRAIN 0 0 0
## CURRENCY EXCHANGE 0 0 0
## DAY CARE CENTER 0 0 0
## DEPARTMENT STORE 0 0 0
## DRIVEWAY - RESIDENTIAL 255 243 234
## DRUG STORE 0 0 0
## FACTORY/MANUFACTURING BUILDING 0 0 0
## FIRE STATION 0 0 0
## FOREST PRESERVE 0 0 0
## GAS STATION 280 270 273
## GOVERNMENT BUILDING/PROPERTY 0 0 0
## GROCERY FOOD STORE 0 0 0
## HIGHWAY/EXPRESSWAY 0 0 0
## HOSPITAL BUILDING/GROUNDS 0 0 0
## HOTEL/MOTEL 0 0 0
## JAIL / LOCK-UP FACILITY 0 0 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0 0 0
## LIBRARY 0 0 0
## MEDICAL/DENTAL OFFICE 0 0 0
## MOVIE HOUSE/THEATER 0 0 0
## NEWSSTAND 0 0 0
## NURSING HOME/RETIREMENT HOME 0 0 0
## OTHER 0 0 0
## OTHER COMMERCIAL TRANSPORTATION 0 0 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0 0 0
## PARK PROPERTY 0 0 0
## PARKING LOT/GARAGE(NON.RESID.) 2128 2073 2103
## POLICE FACILITY/VEH PARKING LOT 0 0 0
## RESIDENCE 0 0 0
## RESIDENCE-GARAGE 0 0 0
## RESIDENCE PORCH/HALLWAY 0 0 0
## RESIDENTIAL YARD (FRONT/BACK) 0 0 0
## RESTAURANT 0 0 0
## SAVINGS AND LOAN 0 0 0
## SCHOOL, PRIVATE, BUILDING 0 0 0
## SCHOOL, PRIVATE, GROUNDS 0 0 0
## SCHOOL, PUBLIC, BUILDING 0 0 0
## SCHOOL, PUBLIC, GROUNDS 0 0 0
## SIDEWALK 0 0 0
## SMALL RETAIL STORE 0 0 0
## SPORTS ARENA/STADIUM 0 0 0
## STREET 22305 21888 22371
## TAVERN/LIQUOR STORE 0 0 0
## TAXICAB 0 0 0
## VACANT LOT/LAND 0 0 0
## VEHICLE-COMMERCIAL 0 0 0
## VEHICLE NON-COMMERCIAL 0 0 0
## WAREHOUSE 0 0 0
##
## 星期五 星期六 星期日
## ABANDONED BUILDING 0 0 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0 0 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0 0 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0 0 0
## AIRPORT EXTERIOR - SECURE AREA 0 0 0
## AIRPORT PARKING LOT 0 0 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0 0 0
## AIRPORT VENDING ESTABLISHMENT 0 0 0
## AIRPORT/AIRCRAFT 0 0 0
## ALLEY 385 341 307
## ANIMAL HOSPITAL 0 0 0
## APARTMENT 0 0 0
## APPLIANCE STORE 0 0 0
## ATHLETIC CLUB 0 0 0
## BANK 0 0 0
## BAR OR TAVERN 0 0 0
## BARBERSHOP 0 0 0
## BOWLING ALLEY 0 0 0
## BRIDGE 0 0 0
## CAR WASH 0 0 0
## CHA APARTMENT 0 0 0
## CHA PARKING LOT/GROUNDS 0 0 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0 0 0
## CLEANING STORE 0 0 0
## COLLEGE/UNIVERSITY GROUNDS 0 0 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0 0 0
## COMMERCIAL / BUSINESS OFFICE 0 0 0
## CONSTRUCTION SITE 0 0 0
## CONVENIENCE STORE 0 0 0
## CTA GARAGE / OTHER PROPERTY 0 0 0
## CTA TRAIN 0 0 0
## CURRENCY EXCHANGE 0 0 0
## DAY CARE CENTER 0 0 0
## DEPARTMENT STORE 0 0 0
## DRIVEWAY - RESIDENTIAL 257 202 221
## DRUG STORE 0 0 0
## FACTORY/MANUFACTURING BUILDING 0 0 0
## FIRE STATION 0 0 0
## FOREST PRESERVE 0 0 0
## GAS STATION 332 338 336
## GOVERNMENT BUILDING/PROPERTY 0 0 0
## GROCERY FOOD STORE 0 0 0
## HIGHWAY/EXPRESSWAY 0 0 0
## HOSPITAL BUILDING/GROUNDS 0 0 0
## HOTEL/MOTEL 0 0 0
## JAIL / LOCK-UP FACILITY 0 0 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0 0 0
## LIBRARY 0 0 0
## MEDICAL/DENTAL OFFICE 0 0 0
## MOVIE HOUSE/THEATER 0 0 0
## NEWSSTAND 0 0 0
## NURSING HOME/RETIREMENT HOME 0 0 0
## OTHER 0 0 0
## OTHER COMMERCIAL TRANSPORTATION 0 0 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0 0 0
## PARK PROPERTY 0 0 0
## PARKING LOT/GARAGE(NON.RESID.) 2331 2199 1936
## POLICE FACILITY/VEH PARKING LOT 0 0 0
## RESIDENCE 0 0 0
## RESIDENCE-GARAGE 0 0 0
## RESIDENCE PORCH/HALLWAY 0 0 0
## RESIDENTIAL YARD (FRONT/BACK) 0 0 0
## RESTAURANT 0 0 0
## SAVINGS AND LOAN 0 0 0
## SCHOOL, PRIVATE, BUILDING 0 0 0
## SCHOOL, PRIVATE, GROUNDS 0 0 0
## SCHOOL, PUBLIC, BUILDING 0 0 0
## SCHOOL, PUBLIC, GROUNDS 0 0 0
## SIDEWALK 0 0 0
## SMALL RETAIL STORE 0 0 0
## SPORTS ARENA/STADIUM 0 0 0
## STREET 23773 22175 21756
## TAVERN/LIQUOR STORE 0 0 0
## TAXICAB 0 0 0
## VACANT LOT/LAND 0 0 0
## VEHICLE-COMMERCIAL 0 0 0
## VEHICLE NON-COMMERCIAL 0 0 0
## WAREHOUSE 0 0 0
##
## 星期四
## ABANDONED BUILDING 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0
## AIRPORT EXTERIOR - SECURE AREA 0
## AIRPORT PARKING LOT 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0
## AIRPORT VENDING ESTABLISHMENT 0
## AIRPORT/AIRCRAFT 0
## ALLEY 315
## ANIMAL HOSPITAL 0
## APARTMENT 0
## APPLIANCE STORE 0
## ATHLETIC CLUB 0
## BANK 0
## BAR OR TAVERN 0
## BARBERSHOP 0
## BOWLING ALLEY 0
## BRIDGE 0
## CAR WASH 0
## CHA APARTMENT 0
## CHA PARKING LOT/GROUNDS 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0
## CLEANING STORE 0
## COLLEGE/UNIVERSITY GROUNDS 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0
## COMMERCIAL / BUSINESS OFFICE 0
## CONSTRUCTION SITE 0
## CONVENIENCE STORE 0
## CTA GARAGE / OTHER PROPERTY 0
## CTA TRAIN 0
## CURRENCY EXCHANGE 0
## DAY CARE CENTER 0
## DEPARTMENT STORE 0
## DRIVEWAY - RESIDENTIAL 263
## DRUG STORE 0
## FACTORY/MANUFACTURING BUILDING 0
## FIRE STATION 0
## FOREST PRESERVE 0
## GAS STATION 282
## GOVERNMENT BUILDING/PROPERTY 0
## GROCERY FOOD STORE 0
## HIGHWAY/EXPRESSWAY 0
## HOSPITAL BUILDING/GROUNDS 0
## HOTEL/MOTEL 0
## JAIL / LOCK-UP FACILITY 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0
## LIBRARY 0
## MEDICAL/DENTAL OFFICE 0
## MOVIE HOUSE/THEATER 0
## NEWSSTAND 0
## NURSING HOME/RETIREMENT HOME 0
## OTHER 0
## OTHER COMMERCIAL TRANSPORTATION 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0
## PARK PROPERTY 0
## PARKING LOT/GARAGE(NON.RESID.) 2082
## POLICE FACILITY/VEH PARKING LOT 0
## RESIDENCE 0
## RESIDENCE-GARAGE 0
## RESIDENCE PORCH/HALLWAY 0
## RESIDENTIAL YARD (FRONT/BACK) 0
## RESTAURANT 0
## SAVINGS AND LOAN 0
## SCHOOL, PRIVATE, BUILDING 0
## SCHOOL, PRIVATE, GROUNDS 0
## SCHOOL, PUBLIC, BUILDING 0
## SCHOOL, PUBLIC, GROUNDS 0
## SIDEWALK 0
## SMALL RETAIL STORE 0
## SPORTS ARENA/STADIUM 0
## STREET 22296
## TAVERN/LIQUOR STORE 0
## TAXICAB 0
## VACANT LOT/LAND 0
## VEHICLE-COMMERCIAL 0
## VEHICLE NON-COMMERCIAL 0
## WAREHOUSE 04.5
On which day of the week do the fewest motor vehicle thefts in residential driveways happen?(Monday~Sunday)
table(Top5$LocationDescription, Top5$Weekday)##
## 星期一 星期二 星期三
## ABANDONED BUILDING 0 0 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0 0 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0 0 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0 0 0
## AIRPORT EXTERIOR - SECURE AREA 0 0 0
## AIRPORT PARKING LOT 0 0 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0 0 0
## AIRPORT VENDING ESTABLISHMENT 0 0 0
## AIRPORT/AIRCRAFT 0 0 0
## ALLEY 320 323 317
## ANIMAL HOSPITAL 0 0 0
## APARTMENT 0 0 0
## APPLIANCE STORE 0 0 0
## ATHLETIC CLUB 0 0 0
## BANK 0 0 0
## BAR OR TAVERN 0 0 0
## BARBERSHOP 0 0 0
## BOWLING ALLEY 0 0 0
## BRIDGE 0 0 0
## CAR WASH 0 0 0
## CHA APARTMENT 0 0 0
## CHA PARKING LOT/GROUNDS 0 0 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0 0 0
## CLEANING STORE 0 0 0
## COLLEGE/UNIVERSITY GROUNDS 0 0 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0 0 0
## COMMERCIAL / BUSINESS OFFICE 0 0 0
## CONSTRUCTION SITE 0 0 0
## CONVENIENCE STORE 0 0 0
## CTA GARAGE / OTHER PROPERTY 0 0 0
## CTA TRAIN 0 0 0
## CURRENCY EXCHANGE 0 0 0
## DAY CARE CENTER 0 0 0
## DEPARTMENT STORE 0 0 0
## DRIVEWAY - RESIDENTIAL 255 243 234
## DRUG STORE 0 0 0
## FACTORY/MANUFACTURING BUILDING 0 0 0
## FIRE STATION 0 0 0
## FOREST PRESERVE 0 0 0
## GAS STATION 280 270 273
## GOVERNMENT BUILDING/PROPERTY 0 0 0
## GROCERY FOOD STORE 0 0 0
## HIGHWAY/EXPRESSWAY 0 0 0
## HOSPITAL BUILDING/GROUNDS 0 0 0
## HOTEL/MOTEL 0 0 0
## JAIL / LOCK-UP FACILITY 0 0 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0 0 0
## LIBRARY 0 0 0
## MEDICAL/DENTAL OFFICE 0 0 0
## MOVIE HOUSE/THEATER 0 0 0
## NEWSSTAND 0 0 0
## NURSING HOME/RETIREMENT HOME 0 0 0
## OTHER 0 0 0
## OTHER COMMERCIAL TRANSPORTATION 0 0 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0 0 0
## PARK PROPERTY 0 0 0
## PARKING LOT/GARAGE(NON.RESID.) 2128 2073 2103
## POLICE FACILITY/VEH PARKING LOT 0 0 0
## RESIDENCE 0 0 0
## RESIDENCE-GARAGE 0 0 0
## RESIDENCE PORCH/HALLWAY 0 0 0
## RESIDENTIAL YARD (FRONT/BACK) 0 0 0
## RESTAURANT 0 0 0
## SAVINGS AND LOAN 0 0 0
## SCHOOL, PRIVATE, BUILDING 0 0 0
## SCHOOL, PRIVATE, GROUNDS 0 0 0
## SCHOOL, PUBLIC, BUILDING 0 0 0
## SCHOOL, PUBLIC, GROUNDS 0 0 0
## SIDEWALK 0 0 0
## SMALL RETAIL STORE 0 0 0
## SPORTS ARENA/STADIUM 0 0 0
## STREET 22305 21888 22371
## TAVERN/LIQUOR STORE 0 0 0
## TAXICAB 0 0 0
## VACANT LOT/LAND 0 0 0
## VEHICLE-COMMERCIAL 0 0 0
## VEHICLE NON-COMMERCIAL 0 0 0
## WAREHOUSE 0 0 0
##
## 星期五 星期六 星期日
## ABANDONED BUILDING 0 0 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0 0 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0 0 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0 0 0
## AIRPORT EXTERIOR - SECURE AREA 0 0 0
## AIRPORT PARKING LOT 0 0 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0 0 0
## AIRPORT VENDING ESTABLISHMENT 0 0 0
## AIRPORT/AIRCRAFT 0 0 0
## ALLEY 385 341 307
## ANIMAL HOSPITAL 0 0 0
## APARTMENT 0 0 0
## APPLIANCE STORE 0 0 0
## ATHLETIC CLUB 0 0 0
## BANK 0 0 0
## BAR OR TAVERN 0 0 0
## BARBERSHOP 0 0 0
## BOWLING ALLEY 0 0 0
## BRIDGE 0 0 0
## CAR WASH 0 0 0
## CHA APARTMENT 0 0 0
## CHA PARKING LOT/GROUNDS 0 0 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0 0 0
## CLEANING STORE 0 0 0
## COLLEGE/UNIVERSITY GROUNDS 0 0 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0 0 0
## COMMERCIAL / BUSINESS OFFICE 0 0 0
## CONSTRUCTION SITE 0 0 0
## CONVENIENCE STORE 0 0 0
## CTA GARAGE / OTHER PROPERTY 0 0 0
## CTA TRAIN 0 0 0
## CURRENCY EXCHANGE 0 0 0
## DAY CARE CENTER 0 0 0
## DEPARTMENT STORE 0 0 0
## DRIVEWAY - RESIDENTIAL 257 202 221
## DRUG STORE 0 0 0
## FACTORY/MANUFACTURING BUILDING 0 0 0
## FIRE STATION 0 0 0
## FOREST PRESERVE 0 0 0
## GAS STATION 332 338 336
## GOVERNMENT BUILDING/PROPERTY 0 0 0
## GROCERY FOOD STORE 0 0 0
## HIGHWAY/EXPRESSWAY 0 0 0
## HOSPITAL BUILDING/GROUNDS 0 0 0
## HOTEL/MOTEL 0 0 0
## JAIL / LOCK-UP FACILITY 0 0 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0 0 0
## LIBRARY 0 0 0
## MEDICAL/DENTAL OFFICE 0 0 0
## MOVIE HOUSE/THEATER 0 0 0
## NEWSSTAND 0 0 0
## NURSING HOME/RETIREMENT HOME 0 0 0
## OTHER 0 0 0
## OTHER COMMERCIAL TRANSPORTATION 0 0 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0 0 0
## PARK PROPERTY 0 0 0
## PARKING LOT/GARAGE(NON.RESID.) 2331 2199 1936
## POLICE FACILITY/VEH PARKING LOT 0 0 0
## RESIDENCE 0 0 0
## RESIDENCE-GARAGE 0 0 0
## RESIDENCE PORCH/HALLWAY 0 0 0
## RESIDENTIAL YARD (FRONT/BACK) 0 0 0
## RESTAURANT 0 0 0
## SAVINGS AND LOAN 0 0 0
## SCHOOL, PRIVATE, BUILDING 0 0 0
## SCHOOL, PRIVATE, GROUNDS 0 0 0
## SCHOOL, PUBLIC, BUILDING 0 0 0
## SCHOOL, PUBLIC, GROUNDS 0 0 0
## SIDEWALK 0 0 0
## SMALL RETAIL STORE 0 0 0
## SPORTS ARENA/STADIUM 0 0 0
## STREET 23773 22175 21756
## TAVERN/LIQUOR STORE 0 0 0
## TAXICAB 0 0 0
## VACANT LOT/LAND 0 0 0
## VEHICLE-COMMERCIAL 0 0 0
## VEHICLE NON-COMMERCIAL 0 0 0
## WAREHOUSE 0 0 0
##
## 星期四
## ABANDONED BUILDING 0
## AIRPORT BUILDING NON-TERMINAL - NON-SECURE AREA 0
## AIRPORT BUILDING NON-TERMINAL - SECURE AREA 0
## AIRPORT EXTERIOR - NON-SECURE AREA 0
## AIRPORT EXTERIOR - SECURE AREA 0
## AIRPORT PARKING LOT 0
## AIRPORT TERMINAL UPPER LEVEL - NON-SECURE AREA 0
## AIRPORT VENDING ESTABLISHMENT 0
## AIRPORT/AIRCRAFT 0
## ALLEY 315
## ANIMAL HOSPITAL 0
## APARTMENT 0
## APPLIANCE STORE 0
## ATHLETIC CLUB 0
## BANK 0
## BAR OR TAVERN 0
## BARBERSHOP 0
## BOWLING ALLEY 0
## BRIDGE 0
## CAR WASH 0
## CHA APARTMENT 0
## CHA PARKING LOT/GROUNDS 0
## CHURCH/SYNAGOGUE/PLACE OF WORSHIP 0
## CLEANING STORE 0
## COLLEGE/UNIVERSITY GROUNDS 0
## COLLEGE/UNIVERSITY RESIDENCE HALL 0
## COMMERCIAL / BUSINESS OFFICE 0
## CONSTRUCTION SITE 0
## CONVENIENCE STORE 0
## CTA GARAGE / OTHER PROPERTY 0
## CTA TRAIN 0
## CURRENCY EXCHANGE 0
## DAY CARE CENTER 0
## DEPARTMENT STORE 0
## DRIVEWAY - RESIDENTIAL 263
## DRUG STORE 0
## FACTORY/MANUFACTURING BUILDING 0
## FIRE STATION 0
## FOREST PRESERVE 0
## GAS STATION 282
## GOVERNMENT BUILDING/PROPERTY 0
## GROCERY FOOD STORE 0
## HIGHWAY/EXPRESSWAY 0
## HOSPITAL BUILDING/GROUNDS 0
## HOTEL/MOTEL 0
## JAIL / LOCK-UP FACILITY 0
## LAKEFRONT/WATERFRONT/RIVERBANK 0
## LIBRARY 0
## MEDICAL/DENTAL OFFICE 0
## MOVIE HOUSE/THEATER 0
## NEWSSTAND 0
## NURSING HOME/RETIREMENT HOME 0
## OTHER 0
## OTHER COMMERCIAL TRANSPORTATION 0
## OTHER RAILROAD PROP / TRAIN DEPOT 0
## PARK PROPERTY 0
## PARKING LOT/GARAGE(NON.RESID.) 2082
## POLICE FACILITY/VEH PARKING LOT 0
## RESIDENCE 0
## RESIDENCE-GARAGE 0
## RESIDENCE PORCH/HALLWAY 0
## RESIDENTIAL YARD (FRONT/BACK) 0
## RESTAURANT 0
## SAVINGS AND LOAN 0
## SCHOOL, PRIVATE, BUILDING 0
## SCHOOL, PRIVATE, GROUNDS 0
## SCHOOL, PUBLIC, BUILDING 0
## SCHOOL, PUBLIC, GROUNDS 0
## SIDEWALK 0
## SMALL RETAIL STORE 0
## SPORTS ARENA/STADIUM 0
## STREET 22296
## TAVERN/LIQUOR STORE 0
## TAXICAB 0
## VACANT LOT/LAND 0
## VEHICLE-COMMERCIAL 0
## VEHICLE NON-COMMERCIAL 0
## WAREHOUSE 0