A Day in the Life of Americans
I can tell you that about 40 percent of people age 25 to 34 are working on an average day at three in the afternoon. I can tell you similar numbers for housework, leisure, travel, and other things. It’s an overview.
What I really want to see is closer to the individual and a more granular sense of how each person contributes to the patterns. I want to see how a person’s entire day plays out. (As someone who works from home, I’m always interested in what’s on the other side.)
So again I looked at microdata from the American Time Use Survey from 2014, which asked thousands of people what they did during a 24-hour period. I used the data to simulate a single day for 1,000 Americans representative of the population — to the minute.
More specifically, I tabulated transition probabilities for one activity to the other, such as from work to traveling, for every minute of the day. That provided 1,440 transition matrices, which let me model a day as a time-varying Markov chain. The simulations below come from this model, and it’s kind of mesmerizing.
Each dot represents a person, color represents the activity, and time of day is shown in the top left. As someone changes an activity, say from sleep to a morning commute, the dot moves accordingly.
Following the timeline of the ATUS, the simulation starts at 4:00am and runs through 24 hours. The day starts with little movement as people are asleep and won’t wake up for a few hours. For most, the day starts at 7:00am and then it’s off to the races (which is especially fun to see on the fast speed).
You see people head to work, run errands, do housework, take care of the kids, commute, relax, and eat at almost designated times during the day. I stared at these dots longer than I care to admit.
Although with all 1,000 dots floating around it can be a challenge to keep track of where all those people went.
So I drew lines to show the paths.
In the graphics that follow, colors represent paths ending in that activity. Traveling is not included to make activity changes more obvious.
Between 6:30am and 7:30am, most people wake up, head into personal care such as showering and brushing teeth, and then head to work, eat breakfast, relax for a bit, and do housework.
From noon to 1:00pm, you see a lot of movement from work or housework to eating and drinking and then back again. Many also take the time to relax.
Getting off work
As you might expect, once the clock strikes 5:00pm, people head home to prepare and/or eat dinner.
Between 10:00pm and midnight, people wind down for the day, shifting from leisure to personal care and eventually going to sleep.
When and where people work, a simulation.
See the half-hour breakdowns for a day, by sex and age group.
Here’s how to make a chart similar to this one.
Become a member. Learn to visualize data. From beginner to advanced.Join Today
This is for people interested in the process of creating, designing, and exploring data graphics. Your support goes directly to FlowingData, an independently run site.
What You Get
- Instant access to tutorials on how to make and design data graphics
- Source code and files to use with your own data
- In-depth courses on visualization in R
- Hand-picked links and resources from around the web
- Members-only newsletter
Data, R, and a 3-D Printer
We almost always look at data through a screen. It’s quick and good for exploration. So is there value in making data physical? I played around with a 3-D printer to find out.
Where Bars Outnumber Grocery Stores
A closer look at the age old question of where there are more bars than grocery stores, and vice versa.