- you will conduct your own data analysis
- create a file to share that documents your findings. 
- You should start by taking a look at your dataset and brainstorming what questions you could answer using it. 
- Then you should use pandas and NumPy to answer the questions you are most interested in, 
- create a report sharing the answers. 
>> !!You will not be required to use inferential statistics or machine learning to complete this project, but you should make it clear in your communications that your findings are tentative. 
- This project is open-ended in that we are not looking for one right answer.
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About the Data:
The data comes from the FBI's National Instant Criminal Background Check System. The NICS is used by to determine whether a prospective buyer is eligible to buy firearms or explosives. 
Gun shops call into this system to ensure that each customer does not have a criminal record or isn’t otherwise ineligible to make a purchase. 
The data has been supplemented with state level data from census.gov.
● The NICS data is found in one sheet of an .xlsx file. It contains the number of firearm checks by month, state, and type.
● The U.S. census data is found in a .csv file. It contains several variables at the state level.
Most variables just have one data point per state (2016), but a few have data for more than one year.
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 Example Questions
What census data is most associated with high gun per capita?
Which states have had the highest growth in gun registrations?
What is the overall trend of gun purchases?
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We recommend creating a single folder that will eventually contain:

The report communicating your findings
Any Python code you wrote as part of your analysis
The data set you used (which you will not need to submit)

analyze at least one dependent variable and three independent variables in your investigation.
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