Notebook

Conclusions

Now that we have looked at these data sets seperately and partially together here is one more image with all of the together.

Screenshot Race+Job+Spouse.png

So from this we can derive pretty muuch all the same data as before, so a recap.

Recap 1

**71%** of the data-set are marked as White, **23%** of the data-set is marked as Black

**37%** have spouses, **63%** of data-points to not have spouses

**75%** of data-points have Jobs, **25%** do not have Jobs Recap 2

**46%** of those points which have jobs also are married, **12%** of people without Jobs are listed as having Spouses, This leaves the remaining **54%** data points with Jobs without Spouses and **88%** of those without Jobs as also not having Spouses

**70%** of the data entires labled Black have Jobs and the remaining **30%** do not, **77** of White data entries have jobs and the remaining **23%** do not.

**29%** of those with Spouses are Black, this leaves the remaining **71%** of those with Spouses as White, **30%** of those without Spouses are Black and the remaining **70** are White.

**38%** of White lables have Spouses, **337%** of Black lables have Spouses

If we consider our old and new data we see some intresting trends worth taking note of

Employment

If we breakdown employment on racial lines we see that amoungst the Jobless population **Black labels have an unemployment rate 7% (30.59-23.49) higher than their White counterparts**. Spouses

If we take a look at our new visulization we see another intresting trend when comparing Employment and Spouses. We see that amoungst those who have Spouses and are Unemployed they are all almost all White. We see that in this catigory 393 are White and 77 are Black, or, (393/470) 100= **84%** are White and **16%** are Black.

In the normal Spouse rate we see a difference of **38%(white)-37%(black)**= **1%%** difference of Spouse rates. We see amoungst the unemployed that the difference is **84%(white)-16%(black)**= **67%** difference

Finale Thoughts With all the Data collected I think it is clear that what is revealed are signfigant economic disparities between the White and Black populations. I am sure that if I was to continue this project and delve into the types of jobs each group works this would bare out. It is intresting though how this manifests in the Spouse rates between the populations. What I would guess we are seeing in the comparrison's between Jobs and Spouses likly have to due with retirment rates and the need for Black populations to need to keep working later. This is my hypothosis for why the data turned out the way it did.

There are some problems to consider with the project which are worth noting. First and foremost, I have used very dirty data. More than anything else I am certain that there are numerious misreading which are skewing the data. With cleaning also comes introducing new data set possiblities which may spread more light on how marriage is functioning within the data-set.

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