The New York City Fire Department keeps a log of detailed information on incidents handled by FDNY units. In this challenge we will work with a dataset that contains a record of incidents handled by FDNY units from 2013-2017. Download the FDNY data set.(https://data.cityofnewyork.us/api/views/tm6d-hbzd/rows.csv?accessType=DOWNLOAD) Also take a look at the dataset landing page(https://data.cityofnewyork.us/Public-Safety/Incidents-Responded-to-by-Fire-Companies/tm6d-hbzd) and find descriptions of column names here. (https://data.cityofnewyork.us/api/views/tm6d-hbzd/files/1434d09c-fbf8-4450-8b42-9fe0c3b85fb3?download=true&filename=OPEN_DATA_FIRE_INCIDENTS_FILE_DESCRIPTION.xls)
111 - Building fire
to the number that arrive for 651 - Smoke scare, odor of smoke
?
INCIDENT_TYPE_DESC
is 710 - Malicious, mischievous false call, other
.
111 - Building fire
incident has been logged into the Computer Aided Dispatch system and the time at which the first unit arrives on scene.
INCIDENT_TYPE_DESC
is 113 - Cooking fire, confined to container
. Note: round incident times down. For example, if an incident occured at 22:55 it occured in hour 22.
111 - Building fire
at each of those zip codes. Note: The 2010 US Census population by zip code dataset should be downloaded from here (https://s3.amazonaws.com/SplitwiseBlogJB/2010+Census+Population+By+Zipcode+(ZCTA).csv) You will need to use both the FDNY responses and the US Census dataset. Ignore zip codes that do not appear in the census table.
CO detector absent
frequency to the CO detector present
frequency.
A circular road has $N$ positions labeled $0$ through $N-1$ where adjacent positions are connected to each other and position $N-1$ is connected to $0$. $M$ cars start at position $0$ through $M-1$ (inclusive). A car can make a valid move by moving forward one position (or goes from $N-1$ to $0$) if the position it is moving into is empty. At each turn, only consider cars that have a valid move available and make one of the valid moves that you choose randomly with equal probability. After $T$ rounds, we compute the average ($A$) and standard deviation ($S$) of the position of the cars.