Brinda Murulidhara HW3

Final Project Proposal

Read in a dataset

I have chosen the Emergency - 911 calls dataset from Kaggle (https://www.kaggle.com/mchirico/montcoalert/version/32) for my final project. The dataset contains emergency 911 calls in Montgomery County, Pennsylvania from 2015 to 2020. Below is the code snippet to read and preview the data.

emergency_calls_data <- read.csv("911.csv")
head(emergency_calls_data)

       lat       lng
1 40.29788 -75.58129
2 40.25806 -75.26468
3 40.12118 -75.35198
4 40.11615 -75.34351
5 40.25149 -75.60335
6 40.25347 -75.28324
                                                                                 desc
1           REINDEER CT & DEAD END;  NEW HANOVER; Station 332; 2015-12-10 @ 17:10:52;
2 BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP; Station 345; 2015-12-10 @ 17:29:21;
3                          HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-Station:STA27;
4               AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A; 2015-12-10 @ 16:47:36;
5    CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; Station 329; 2015-12-10 @ 16:56:52;
6               CANNON AVE & W 9TH ST;  LANSDALE; Station 345; 2015-12-10 @ 15:39:04;
    zip                   title           timeStamp               twp
1 19525  EMS: BACK PAINS/INJURY 2015-12-10 17:10:52       NEW HANOVER
2 19446 EMS: DIABETIC EMERGENCY 2015-12-10 17:29:21 HATFIELD TOWNSHIP
3 19401     Fire: GAS-ODOR/LEAK 2015-12-10 14:39:21        NORRISTOWN
4 19401  EMS: CARDIAC EMERGENCY 2015-12-10 16:47:36        NORRISTOWN
5    NA          EMS: DIZZINESS 2015-12-10 16:56:52  LOWER POTTSGROVE
6 19446        EMS: HEAD INJURY 2015-12-10 15:39:04          LANSDALE
                        addr e
1     REINDEER CT & DEAD END 1
2 BRIAR PATH & WHITEMARSH LN 1
3                   HAWS AVE 1
4         AIRY ST & SWEDE ST 1
5   CHERRYWOOD CT & DEAD END 1
6      CANNON AVE & W 9TH ST 1

Explain the variables in your dataset

Below are the variables in the dataset:

1. lat: Latitude of the location where the emergency occurred. The data type is double.
2. lng: Longitude of the location where the emergency occurred. The data type is double.
3. desc: Description of the emergency. The data type is String.
4. zip: Zipcode of the location where the emergency occurred. The data type is integer.
5. title: Type of emergency. The data type is String.
   
6. timeStamp: Date and time of the emergency call. The data type is String.
7. twp: Township where the emergency occurred. The data type is String.
8. addr: Address of the emergency location. The data type is String.
9. e: Index column whose value is always 1. The data type is integer.

Potential research questions

Below are potential research questions that the dataset can answer:

1. What are the types of emergencies that occur most frequently in Montgomery County?
2. Has there been a reduction/increase in a certain type of emergency (e.g. vehicle accident) from 2015 to 2020?
3. Is there a correlation between datetime and the number of emergencies that occur? E.g. Are there more vehicle accidents during night times and peak hours of traffic? Are there more cardiac arrest emergencies during the daytime?
4. Which townships in Montogomery County get more calls as a result of shootings and stabbings? (This information may give us insights into the crime scene in various townships.)
5. How do heat exhaustion emergencies vary across the year?