Stop and Frisk Digestion

Author

Nic Schwab

Stop, Question, Frisk

Started in the 1990s
New York City Police Practice
- Police need “reasonable suspicion.”
Leads to mistrust in the police by these groups.

Disclaimer: Person Bias

I’m not Black.

I am Hispanic.

I look White.

I am not from New York City.

In this data analysis I will have limited perspective.

Disclaimer: Race

This is an acknowledgement that the construct of race exists and plays a part in the way human being interact with each other.

The Data

Here is NYC’s stop and frisk data.

Let’s consider 2011 data

Each column is a variable
and each row is a stop

The variable names are inconsistent across years.

SQF History

# Read in each csv file. This is a lot 

# With purr csv

file_paths_csv <- fs::dir_ls("../data/2003_2015_csv_files")

file_contents_csv<- file_paths_csv |>
  map(function (path){
    read_csv(path)
  })

# with purr excel

file_paths_xl <- fs::dir_ls("../data/2016_2022_xl_files")

file_contents_xl<- file_paths_xl |>
  map(function (path){
    read_excel(path)
  })

# https://www.youtube.com/watch?v=An1bUIg-nVM

#See the number of rows i.e stops in each year
pre_2016 <- sapply(file_contents_csv, nrow)
post_2016 <- sapply(file_contents_xl, nrow)

years <- c(2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 )
stops_frisks <- c(160851, 313523, 398191, 506491, 472096, 540302, 581168,  601285, 685724, 532911,  191851, 45787, 22563, 12405, 11629,  11008,   13459,9544 , 8947,  15102)  

sqf <- data.frame(years,stops_frisks)



sqf |> 
  ggplot(aes(years,stops_frisks)) +
  
  #geom_rect(aes(xmin=2002,xmax=2014,ymin=0,ymax=Inf),fill="#003585",alpha=0.01)+
  #geom_rect(aes(xmin=2014,xmax=2021,ymin=0,ymax=Inf),fill="#FFFFFF",alpha=0.01)+
  #geom_rect(aes(xmin=2021,xmax=2022,ymin=0,ymax=Inf),fill="#FF6600",alpha=0.01)+
  geom_line()+
  xlab("Year")+
  ylab("Citizens Stopped ('000s)")+
  labs(title="")+
  theme_minimal()+
  scale_y_continuous(breaks = c(0,350000,700000), labels = c("0","350","700"))+
  scale_x_continuous(breaks = c(2003,2013,2022))+
  geom_text(label="Bloomberg", x = 2004.5, y = 40000, color="gray35" ) +
  geom_text(label="de Blasio", x = 2016, y = 40000, color="gray35" ) +
  geom_text(label="Adams", x = 2022, y = 40000, color="gray35" ) +
  geom_text(label=". NYCLU \n suit", x = 2013, y = 650000, color="gray35" ) +
  geom_vline(xintercept=2012, linetype = 3 ) +
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    axis.line = element_line(color = "black"),
    axis.text=element_text(size=12)
  
  )

You found:

For comparison:

Here’s the demographics of NYC¹:

Black: 23.4 %
Latino: 28.9%
White: 39.8%

Data exposure

Data helped to expose the racism of the practice of Stop Question Frisk.

Footnotes

https://www.census.gov/quickfacts/fact/table/newyorkcitynewyork/PST045222↩︎

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