The dataset for the 1880 Census in Albany, New York consists of a lot of basic information as well as a few more detailed pieces of information. In a row the information you get about someone is his or her first and last name, age, race, gender, estimated birth year, relationship in terms of family, marital status, birthplace, and the birthplace of both their father and mother. The data is numeric, textual, and geographic. The columns about birthplace are geographic, the data about age and birth year estimates are numeric, and the remaining columns are textual. It is majorly textual, but the other columns are just as, if not more, important comparatively to the text only columns. The ranges of the two numeric columns correlate because they consist of birth year estimates and age. The minimum age of the dataset is one month old and the maximum age is 98 years old. The minimum year of birth is 1782 and the maximum is 1880. The relationship in terms of family status ranges from son or daughter to self. There are a lot of different terms used in this set. Any sort of relationship that can be had including in laws is listed. Marital status contains the option of single, married, widowed or divorced. Birthplace lists either a country or a state if they were born within the United States. This is true for all three of the birthplace columns in the dataset. Gender consists of either male or female. The most interesting one is the race column. White is the only listed option. Each row is describing a person that was living in Albany during 1880.
Comparisons within the dataset:
I think that a lot of different connections can be made within the dataset and how different columns correlate to each other. One I would start off with is the correlation, or possibly lack there of, of the birthplace and the father and mother’s birthplaces. There is obviously a connection through your relationship to them, but within an Albany census it is interesting to take a look at. Obviously the person in question ended up in Albany by 1880 so how did that happen. There are a plethora of answers to this question, but it is interesting to look at the data because you can kind of piece an understanding together. If they were born in Albany and both parents are from Europe, than you can gather that the parents came over to America and than had children. If the child was also born in Europe you can gather that the children came over to America by themselves and so on. Another connection can be made between age, marital status, and gender. There is bound to be correlation between age and marital status because as you get older you may get married, but when you add in the gender factor it becomes more intriguing. Back during this time it was not unlikely for a woman to get married to an older man at a very young age. This dataset does not directly tell us when anyone was married, but you can start to gather information based on the current marital status versus his or her age. When taking gender into account you will most likely see a younger age for woman when compared to men and their marital status. The last connection between two columns I would make on this dataset is age and relationship within the family. Some people in this dataset are listed as self, which presumably means they have no family within the city of Albany or are not married past a certain age. Some are listed as a son or daughter. I would be curious to find out when you either become self from son or daughter or if self is only someone without family. It makes sense that you become a husband or wife once married, but self is an interesting role.