This visualization is one of a series of visualizations that present US household spending data from the US Bureau of Labor Statistics. This one looks at the education level of the primary resident.
This visualization focuses on the education level of the primary resident. This is defined in the BLS documentation as the person who is first mentioned when the survey respondent is asked who in the household rents or owns the home.
I obtained data from the US Bureau of Labor Statistics (BLS), based upon a survey of consumer households and their spending habits. This data breaks down spending and income into many categories that are aggregated and plotted in a Sankey graph.
One of the key factors in financial health of an individual or household is making sure that household spending is equal to or below household income. If your spending is higher than income, you will be drawing down your savings (if you have any) or borrowing money. If your spending is lower than your income, you will presumably be saving money which can provide flexibility in the future, fund your retirement (maybe even early) and generally give you peace of mind.
The composition of households and income change as the education level of the primary resident changes, which in turn affects spending totals and individual categories.
As stated before, one of the keys to financial security is spending less than your income. We can see that on average, income tends to increase with education level. Those with the highest incomes and greatest spending have advanced degrees, but they also save the most money.
The group with the lowest education level (not finishing high school) have the lowest income and on average needs to borrow or draw down on savings to live their lifestyle.
How does your overall spending compare with those that have the same education level as you? How about spending in individual categories like housing, vehicles, food, clothing, etc…?
Probably one of the best things you can do from a financial perspective is to go through your spending and understand where your money is going. These sankey diagrams are one way to do it and see it visually, but of course, you can also make a table or pie chart (Honestly, whatever gets you to look at your income and expenses is a good thing).
The main thing is to understand where your money is going. Once you’ve done this you can be more conscious of what you are spending your money on, and then decide if you are spending too much (or too little) in certain categories. Having context of what other people spend money on is helpful as well, and why it is useful to compare to these averages, even though the income level, regional cost of living, and household composition won’t look exactly the same as your household.
Here is more information about the Consumer Expenditure Surveys from the BLS website:
The Consumer Expenditure Surveys (CE) collect information from the US households and families on their spending habits (expenditures), income, and household characteristics. The strength of the surveys is that it allows data users to relate the expenditures and income of consumers to the characteristics of those consumers. The surveys consist of two components, a quarterly Interview Survey and a weekly Diary Survey, each with its own questionnaire and sample.
Data and Tools:
Americans are known for loving cars and driving quite a bit. Drivers in the United States own more cars and drive more than those in any other country. So what kinds of vehicles do Americans drive? This visualization looks at the types of vehicles (by body type and country of origin) across the 50 States and Washington DC.
You can view two different attributes about the types of vehicles in use in the United States:
The different categories of passenger vehicles include:
Classification of the vehicles manufacturer (US, Asia or Europe) is based on the company’s headquarters and not the place of vehicle manufacturing. So a Toyota here is an Asian vehicle even if it was assembled in Mississippi.
It is pretty interesting to see the regional differences in vehicle types (cars vs trucks and SUVs) and vehicle brand (domestic vs foreign). Michigan, especially, stands out with their very high domestic ownership. It makes sense as Detroit is the home of the big three US auto manufacturers (Ford, GM and Chrysler). And I hear there’s a very strong culture of owning American cars there (and employee, friends and family discounts as well).
The data is derived from a survey by the US Department of Transportation called the National Household Travel Survey (NHTS) released in 2017. The following is a quote from the NHTS webpage:
The National Household Travel Survey (NHTS) is the source of the Nation’s information about travel by U.S. residents in all 50 States and Washington, DC. This inventory of travel behavior includes trips made by all modes of travel (i.e., private vehicle, public transportation, pedestrian, and cycling) and for all purposes (e.g., travel to work, school, recreation, and personal/family trips). It provides information to assist transportation planners and policymakers who need comprehensive data on travel and transportation patterns in the United States.
Data and Tools:
Given that tax day has just passed, I thought it would be good to check out some data on taxes. The IRS provides a great resource on tax data that I’ve only just gotten into. I think I’ll be able to do more with this in the future. This one looks at how taxes paid varies by state and presents it as a choropleth map (coloring states based on certain categories of tax data).
I may add more categories in the future, so if you have ideas of tax data you want to see visualized let me know and I’ll see what I can do.
Data and Tools:
Code Embed: Cannot use CODECSSresize9 as a global code as it is being used to store 2 unique pieces of code in 3 posts
This map shows the electoral outcome of the 2016 US Presidential Election and is color coded red if the state was won by Donald Trump (R) and blue if the state was won by Hilary Clinton. When looking at the map, red states tend to be larger in area than blue states, but also generally have lower populations. This gives a misleading impression that the electoral share is “redder” than it actually is. For 2016, we can see that Trump won 306 electoral votes or (57% of the total electoral votes), but the map is shaded such that 73% of the area of the US is colored red. Similarly, Clinton won 232 electoral votes, but the map is shaded such that only 27% of the map is colored blue.
The map shrinks the states with low electoral votes relative to its area and increases the size of states with large numbers of electoral votes relative to its area. On average blue states grow as they are under-represented visually, while red states tend to shrink quite a bit because they are over-represented visually. Alaska is the state that shrinks the most and DC and New Jersey are the areas that grow the most in the new map.
I think this gives a more accurate picture of how the states voted because it also gives a sense of the relative weight of those states votes. Even with the change in sizes, the map is still mostly red, but gives a better sense of how close the electoral vote totals are.
Data and Tools:
Electric vehicles are any vehicle that can be plugged in to recharge a battery that provides power to move the vehicle. Two broad classes are battery electric vehicles (BEVs) which only have batteries as their power source and plug-in hybrid electric vehicles (PHEVs) which have an alternative or parallel power source, typically a gasoline engine. PHEVs are built so that when the battery is depleted, the car can still run on gasoline and operate like a hybrid vehicle similar to a regular Toyota Prius (which is not plugged in at all).
Electric vehicles (EVs) have been sold in the US since 2011 (a few commercial models were sold previous to that but not in any significant numbers) and some conversions were also available. Since then, the number of EVs sold has increased pretty significantly. I wanted to look at the distribution of where those vehicles were located. What is interesting is that California accounts for around 50% of the electric vehicles sold in the United States. Other states have lower rates of EV adoption (in some cases much, much lower). There are many reasons for this, including beneficial policies, public awareness, a large number of potential early adopters and a mild climate. Even so, the EV heatmap of California done early shows that sales are mostly limited to the Bay Area, and LA areas.
The map shows data for total electric vehicle sales by state for years 2016, 2017 or 2018 and also the number of EV sales per 1000 licensed drivers (this is all people in the state with a drivers license, not drivers of EVs). If you hover over a state, you can see both data points for that state.
It will be interesting to see how the next generation of electric vehicles continues to improve, lower in price and become more popular with drivers outside of early adopters.
Data and Tools:
California is one of the world’s largest economies (as measured by gross domestic product), currently ranking 5th in the world (if it were judged as it’s own country). This map divides the rest of the US economy into 6 more or less equal parts (each the size of California’s) and they are all within about 10% of each other.
You can hover over a state with your cursor to get more information about the GDP of that state and the group of states that equal California’s economy.
Gross domestic product is a measurement of the size of a region’s economy. It is the sum of gross value added from all entities in the region or state. It measures the monetary value of the goods produced and services provided in a year.
The main sectors of the California economy are agriculture, technology, tourism, media (movies and TV) and trade. Some of the world’s largest and most famous companies contribute to the California economy, like Apple, Google, Facebook, Disney, and Chevron.
Data and Tools: