Short Description of the Project

This interactive dashboard presents a comprehensive analysis of crime patterns across New York State, offering insights into both violent and property crime trends. Leveraging clustering techniques, mapping tools, and temporal breakdowns, this visualization enables data-driven discussions about public safety across counties.

Dataset and Tableau Public Link

  • Dataset Link: Here
  • Tableau Public Link: Here

Tools and Technologies Used

  • Tableau Desktop 2024.3
  • R Studio 2024.12.0
  • R version 4.4.2

Data Definition

The original dataset was downloaded from NY open data website. This dataset is named as index_crimes_ny and imported to Tableau. The dataset is shown below:

Figure 1: The data fields after importing the data

Each of the variables in the dataset are defined below:

County: Location where the crime was reported.
 
Agency: Police Department that reported the crime.
 
Year: Year the crime incident was reported.
 
Months Reported: Number of months an individual agency reported for the year. However, a data visualization in Figure 2 shows that for most of the observations, the Month Reported is either missing or December. It looks like a human error, happened during the data entry. Therefore, this variable is not considered in this analysis.
Figure 2: Count of Index Total for each Month Reported
Index Total: Includes sum of Murder, Rape, Robbery, Aggravated Assault, Burglary, Larceny and Motor Vehicle Theft.
 
Violent Total: Subtotal includes Murder, Rape, Robbery and Aggravated Assault.
 
Murder: One count per victim. The willful killing of one human being by another. Excludes deaths caused by negligence, suicide, or justifiable homicides, and attempts to murder, which are classified as assault.
 
Rape: One count per victim. Penetration, no matter how slight, of the vagina or anus with any body part or object, or oral penetration by a sex organ of another person, without the consent of the victim.
 
Robbery: One count per victim. The taking or attempting to take anything of value from the care, custody, or control of a person or persons by force or threat of force or violence and/or by putting the victim in fear.
 
Aggravated Assault: One count per victim. The unlawful attack by one person upon another for the purpose of inflicting severe or aggravated bodily injury. This type of assault is usually accompanied by the use of a weapon or by means likely to produce death or great bodily harm, and also includes attempts to commit murder.
 
Property Total: Subtotal includes Burglary, Larceny and Motor Vehicle Theft.
 
Burglary: One count per victim. The unlawful entry of a structure to commit a felony or theft. The use of force to gain entry is not required to classify an offense as Burglary.
 
Larceny: One count per victim. The unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another. It includes crimes such as shoplifting, purse snatching, bicycle thefts, etc., in which no use of force, violence, or fraud occurs.

Motor Vehicle Theft: One count per victim. The theft or attempted theft of a motor vehicle, including automobiles, trucks, buses, motorcycles, and snowmobiles.

Region: Region where the crime was reported. Regions include New York City (Bronx, Kings, New York, Queens, and Richmond counties) and Non-New York City (all other counties).

Data Preparation

The original dataset was downloaded from NY open data website. This dataset is named as index_crimes_ny and imported to Tableau. The dataset is shown below:

Figure 1: The data fields after importing the data

Each of the variables in the dataset are defined below:

County: Location where the crime was reported.
 
Agency: Police Department that reported the crime.
 
Year: Year the crime incident was reported.
 
Months Reported: Number of months an individual agency reported for the year. However, a data visualization in Figure 2 shows that for most of the observations, the Month Reported is either missing or December. It looks like a human error, happened during the data entry. Therefore, this variable is not considered in this analysis.
Figure 2: Count of Index Total for each Month Reported
Index Total: Includes sum of Murder, Rape, Robbery, Aggravated Assault, Burglary, Larceny and Motor Vehicle Theft.
 
Violent Total: Subtotal includes Murder, Rape, Robbery and Aggravated Assault.
 
Murder: One count per victim. The willful killing of one human being by another. Excludes deaths caused by negligence, suicide, or justifiable homicides, and attempts to murder, which are classified as assault.
 
Rape: One count per victim. Penetration, no matter how slight, of the vagina or anus with any body part or object, or oral penetration by a sex organ of another person, without the consent of the victim.
 
Robbery: One count per victim. The taking or attempting to take anything of value from the care, custody, or control of a person or persons by force or threat of force or violence and/or by putting the victim in fear.
 
Aggravated Assault: One count per victim. The unlawful attack by one person upon another for the purpose of inflicting severe or aggravated bodily injury. This type of assault is usually accompanied by the use of a weapon or by means likely to produce death or great bodily harm, and also includes attempts to commit murder.
 
Property Total: Subtotal includes Burglary, Larceny and Motor Vehicle Theft.
 
Burglary: One count per victim. The unlawful entry of a structure to commit a felony or theft. The use of force to gain entry is not required to classify an offense as Burglary.
 
Larceny: One count per victim. The unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another. It includes crimes such as shoplifting, purse snatching, bicycle thefts, etc., in which no use of force, violence, or fraud occurs.

Motor Vehicle Theft: One count per victim. The theft or attempted theft of a motor vehicle, including automobiles, trucks, buses, motorcycles, and snowmobiles.

Region: Region where the crime was reported. Regions include New York City (Bronx, Kings, New York, Queens, and Richmond counties) and Non-New York City (all other counties).

Tableau Dashboard of AirBnB Data of New York City

Data Analysis

Line Plot for Count of Reviews

The line plot in Figure 3 shows the count of reviews over the weeks from January 2018 to June 2019. The observation from the plot is that there is a spike on review counts on the last week of December 2018 and the first week of January 2019. It indicates the Christmas and the year end vacation season. But the sharp increase of review count starts from the second week of May 2019 (~600). It reaches the highest peak on the last week of June 2019 (~5200) and a gradual decrease until the first week of July 2019 (~800). The rise indicates the increase of tourists during the summer season. According to the line plot, this is the best time to collect the customer reviews. 

Figure 3: The weekly count of reviews over the time period January 2018 to July 2019.

Distribution of Listings by Neighborhood Groups

All the listings are distributed according to colors and grouped by the Neighborhoods in Figure 4. The distribution shows that Manhattan and Brooklyns are the most densely distributed areas for AirBnB listings. Distribution in Queens is very large and scattered. Bronx is much smaller in area but the distribution is sparse. The least distribution is observed in Staten Island. 

 

Figure 4: Distribution of Neighborhood groups. Blue = Bronx, Orange = Brooklyn, Red = Manhattan, Tiel = Queens and Green = Staten Island

Density Map for Average Prices

From the density map in Figure 5, it is seen that the lower (southern) part of Manhattan is the most expensive area. Another expensive area is the northern part of Brooklyn, especially the areas adjacent to lower Manhattan. Queens, Bronx and Staten Island are moderate to least expensive areas.

 

Figure 5: Density map for average prices. The green to orange gradient colors indicate the low to high price respectively.

Bar Chart of Average Price by Room Type

From figure 6, it is seen that renting entire home / apartment is most expensive in Manhattan with an average of 243.3 USD. The lowest place to stay in an entire home / apartment is staten island (on an average 118.9 USD). For private room rental, Manhattan is most expensive and Bronx is least expensive with an average price of 104.5 and 56.9 USD respectively. An interesting fact is that, in staten island the average price of private room and shared room is almost similar. The cheapest shared room can be found in Bronx (38.6 USD) and Manhattan costs the highest average price for the shared room.   

 

Figure 6: Bar chart of average price by room type for each neighborhood group.

 Bar Chart of Average Price by Neighborhood

I have created bar charts of average price by Neighborhood in figure 7. Since figure 7 is not coped horizontally on this width, I can refer the Tableau dashboard for clearer view. According to the chart, Sea Gate of Brooklyn has the highest average price for rental i.e.  806 USD. The lowest rental is in New Dorp Beach of Staten Island, 38 USD.  

Figure 7: Bar chart for average price by neighborhood.

Highlight Table for Average Availability 365

To analyze the average availability of rooms in 365 days, we excluded 0’s. After the exclusion, we created a highlight table, shown in figure 8. It can be seen from the figure that Staten Island has the highest availability (227.55 days) of rooms, followed by Bronx (206.65 days), Queens (200.02 days) and Manhattan (183.41 days). Finding room in Brooklyn can be most difficult with an average availability of 178.76 days out of 365 days.   

Figure 8: Average of availibility of AirBnB rental in 365 days.