For my final project I would like to focus on the data set of Slave Sales between 1775 and 1865. This data set includes numeric,text,and geographic information on slaves up for sale. This data set features a couple of numeric columns, one regarding a slaves age from infant to as old as 99, another appraised value of that slave, and another was the year listed for sale ranging from 1742-1865. As for the geography of this dataset, a column is included for the state the slave was sold. Ironically the only states mentioned are in the south including Georgia,Louisiana, and Mississippi. The other geographic column of counties is used to narrow in on a certain location a slave was sold at. This dataset also has columns for the sex of slave, defects of a slave and skills a slave possesses. For a column like the sex of a slave there are only 2 options male of female, while the defects and skills of slaves can hoist a bunch of options ranging from old to lame. I did notice that for the defect and skills columns both had significantly more blank spaces then all other columns.
As for relationships between the different columns and rows in the slave sales dataset there are several. I noticed their is a correlation between the defects, age,and sex of a slave and the appraised value. Old and disobedient slaves were sold for way less than a young male “prime” slave. Young slaves were often valued very low as well. Also most of the skills types are connected to just one race. Women were seen as child bearers and caretakers, while men were seen more as laborers.