It does not matter the city, state, or country you live in - crime occurs everywhere. In fact, in just the city of Boston alone, there were over 73,000 crime incidents that the Bolice Police had to respond to in 2022. 73,000! That's approximately 200 incidents PER DAY! According to another source, city-data.com, Boston crime was higher than that of 78.3% of other major US cities. Do these staggering number not raise a primary concern for all residents in the city?
https://www.city-data.com/crime/crime-Boston-Massachusetts.html
import pandas as pd
pd.read_csv('crime.csv')
C:\Users\spenc\AppData\Local\Temp\ipykernel_7372\904721680.py:3: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.
pd.read_csv('crime.csv')
| INCIDENT_NUMBER | OFFENSE_CODE | OFFENSE_CODE_GROUP | OFFENSE_DESCRIPTION | DISTRICT | REPORTING_AREA | SHOOTING | OCCURRED_ON_DATE | YEAR | MONTH | DAY_OF_WEEK | HOUR | UCR_PART | STREET | Lat | Long | Location | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 222076257 | 619 | NaN | LARCENY ALL OTHERS | D4 | 167 | 0 | 2022-01-01 00:00:00 | 2022 | 1 | Saturday | 0 | NaN | HARRISON AVE | 42.339542 | -71.069409 | (42.33954198983014, -71.06940876967543) |
| 1 | 222053099 | 2670 | NaN | HARASSMENT/ CRIMINAL HARASSMENT | A7 | 0 | 2022-01-01 00:00:00 | 2022 | 1 | Saturday | 0 | NaN | BENNINGTON ST | 42.377246 | -71.032597 | (42.37724638479816, -71.0325970804128) | |
| 2 | 222039411 | 3201 | NaN | PROPERTY - LOST/ MISSING | D14 | 778 | 0 | 2022-01-01 00:00:00 | 2022 | 1 | Saturday | 0 | NaN | WASHINGTON ST | 42.349056 | -71.150498 | (42.34905600030506, -71.15049849975023) |
| 3 | 222011090 | 3201 | NaN | PROPERTY - LOST/ MISSING | B3 | 465 | 0 | 2022-01-01 00:00:00 | 2022 | 1 | Saturday | 0 | NaN | BLUE HILL AVE | 42.284826 | -71.091374 | (42.28482576580488, -71.09137368938802) |
| 4 | 222062685 | 3201 | NaN | PROPERTY - LOST/ MISSING | B3 | 465 | 0 | 2022-01-01 00:00:00 | 2022 | 1 | Saturday | 0 | NaN | BLUE HILL AVE | 42.284826 | -71.091374 | (42.28482576580488, -71.09137368938802) |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 73847 | 232000091 | 1402 | NaN | VANDALISM | A1 | 66 | 0 | 2022-12-31 23:30:00 | 2022 | 12 | Saturday | 23 | NaN | CHARLES ST | 42.359790 | -71.070782 | (42.35979037458775, -71.07078234449541) |
| 73848 | 232000002 | 3831 | NaN | M/V - LEAVING SCENE - PROPERTY DAMAGE | C11 | 0 | 2022-12-31 23:37:00 | 2022 | 12 | Saturday | 23 | NaN | COLUMBIA RD | 42.319593 | -71.062607 | (42.31959298334654, -71.06260699634272) | |
| 73849 | 232000140 | 619 | NaN | LARCENY ALL OTHERS | D14 | 778 | 0 | 2022-12-31 23:45:00 | 2022 | 12 | Saturday | 23 | NaN | WASHINGTON ST | 42.349056 | -71.150498 | (42.34905600030506, -71.15049849975023) |
| 73850 | 232000315 | 3201 | NaN | PROPERTY - LOST/ MISSING | D4 | 167 | 0 | 2022-12-31 23:50:00 | 2022 | 12 | Saturday | 23 | NaN | HARRISON AVENUE | NaN | NaN | NaN |
| 73851 | 232000052 | 3114 | NaN | INVESTIGATE PROPERTY | A1 | 0 | 2022-12-31 23:50:00 | 2022 | 12 | Saturday | 23 | NaN | MOUNT VERNON ST | 42.357879 | -71.069680 | (42.357878706878985, -71.06967973039733) |
73852 rows × 17 columns
pd.read_csv('description.csv')
| Field Name | Description | |
|---|---|---|
| 0 | [incident_num] | Internal BPD report number |
| 1 | [offense_code] | Numerical code of offense description |
| 2 | [Offense_Code_Group_Description] | Internal categorization of [offense_description] |
| 3 | [Offense_Description] | Primary descriptor of incident |
| 4 | [district] | What district the crime was reported in |
| 5 | [reporting_area] | RA number associated with the where the crime ... |
| 6 | [shooting] | Indicated a shooting took place. |
| 7 | [occurred_on] | Earliest date and time the incident could have... |
| 8 | [UCR_Part] | Universal Crime Reporting Part number (1,2, 3) |
| 9 | [street] | Street name the incident took place |
Using latitude and longitude coordinates, I will plot the locations of all crimes and determine whether location has a play in overall Boston crime. Additionally, I will use the crime occurrance date to determine whether the time of day also has an impact. Lastly, using offense codes and desciptions will paint a picture as to how severe crimes are (different color coordinates on plot graph). Doing so allows me to discover whether location, time of day, and types of crimes has an effect overall crime in Boston and further inform local residents about how to stay safe in the city.