What are the biggest types of complaints about noise? And when do they happen? An analysis of the 311 calls in New York City for 2017.

There are a lot of non-emergency calls each year in New York City. These are made through the 311 phone number. The 311 number is used to report graffiti, make complaints, and provide other information.

In 2017, there were 448,309 calls to the 311 number that were related to noise. That is a lot of complaints about noise. Looking at the complaints about noise can give an insight into the goings-on in New York City.

I first was curious to see which month was the noisiest, or at least, had the most calls into the 311 systems related to noise. I thought some months would naturally have more noise-related complaints than other months because of the holidays during these months. For example, I thought January and December would likely be noisier months because of the Christmas and New Year’s celebrations.

I got the data for this project from the New York City Open Data site. The data from the site originally contained 41 columns with lots of different information. I restricted the data to the year 2017 and filtered it to only contain the 311 calls about noise and then read in only five different columns from the original data. This gave me the following data set.

This data set did contain Null values in the “Incident Address” column and the “Location Type” column. I decided to not drop the Null values from the data set, as they would have no effect on the information I wanted to look at.

To start finding out the answer to my questions, I first changed the “Created Date” column from a String type object to a DateTime object of the Python Library. This would allow me to search months, days, or even the hours that each noise complaint occurred.

I first separated the data into months. To see which month had the most noise complaints, I compared the size of each of the data frames that represented a month. The largest data frame would represent the “Noisiest Month”. Or at least, the one with the most complaints about noise.

I wanted to dig deeper and see what were some of the common causes of all these noise complaints. To do this I built a method that would use the “value_counts” method from the Pandas library to find the 3 most common causes of noise complaints during each month.

As you can see it is possible that the 3 most common causes may be related. For example, someone is having a party with some loud music. Their neighbor bangs and pounds on the wall or door, telling them to be quiet. Some people complain about the party sounds while others complain about the pounding sounds. Soon, the banging people and the party people begin arguing and yelling. After some time, some other person calls to complain about the loud talking,(arguing). All joking aside, these common noise complaints are possibly somewhat related to each other.

I decided to look at the 3 most common locations for noise complaints during the year. As you can see, most complaints happen within the residential area. The street and stores are the second and third most common locations.

I decided to dive deeper into the noise complaints of “Loud Music and Parties.” Where are they happening? To do this, I further filtered the data to only be data that had the noise complaints of “Loud Music and Parties.” Using the same method that I had made previously, I filtered down to the 3 most common locations where the “loud music/parties” were occurring.

I wanted to know what effect the time of day had on the type of noise complaints. I filtered each month into hours of the day and then found the 3 most common types of noise complaints per hour. I am only showing the month of June because the number of graphs would be too great for all twelve months.

By drilling down to the hours of the day in each month, it is possible to somewhat see what is going on during the days in New York City. It sheds light on what a New Yorker may experience each day. The following graph shows the fluctuation of 8 of the more common noise complaints during the days in June.

If you are interested in seeing my work, click here.