Dataset: FBI Background Checks 1999–2020

About this Dataset

FBI Background Checks 1999–2020

Context

I have downloaded the dataset from open data at the FBI. I have enriched it with spatial polygons and point for geomapping.

Content

Columns :
**month **=> it's format is "YYYY-MM"
**state **=> normalised U.S. state names. Be careful, New-york is called "New-York state" in order to force geocoders to recognise the state and not NYC.
**handgun **=> number of background check requested for handguns in the month
**long_gun **=> number of background check requested for long_guns in the month
**total **=> add handgun and long_gun for a given month
**centralPoint **=> the longitude and latitude of the center of the given U.S. state
**population **=> number of inhabitant of the given U.S. state
**geometry **=> polynoms representing the boundaries of each given U.S. state
**xtext **=> horizontal offset for the label (the U.S. states located around NYC are very close, so we want an offset to represent the values we want to show)
**ytext **=> vertical offset for the label (the U.S. states located around NYC are very close, so we want an offset to represent the values we want to show)

Acknowledgements

Thanks to the COVID19 to allow me to learn a lot of things, while I'm at home. 😃

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?
Are personnal gun sales a sign of general stress, international disorders ?

Tables

N 002 Fbi Background Checks Out

@kaggle.claudecostantini_fbi_background_checks_1999_2020.n_002_fbi_background_checks_out

217.29 KB
12495 rows
10 columns


CREATE TABLE n_002_fbi_background_checks_out (
  "month" TIMESTAMP,
  "state" VARCHAR,
  "handgun" BIGINT,
  "long_gun" BIGINT,
  "total" BIGINT,
  "centralpoint" VARCHAR,
  "population" BIGINT,
  "geometry" VARCHAR,
  "xtext" BIGINT,
  "ytext" BIGINT
);