Statistical Atlas  /  ,

Coming and Going Age Generations

By Nathan Yau

Since no one has figured out how to defeat time, age generations come and go. This chart shows the generational breakdowns since 1920.

RELATIVE POPULATION DISTRIBUTION OF

AGE GENERATIONS

FROM 1920 THROUGH 2019

Based on estimates from the Decennial Census and the American Community Survey

A new generation begins.

100%

Generation Alpha

Greatest Generation

Generation Z

80%

Millennials

60%

Lost Generation

Generation X

40%

20%

Boomers

Missionary Generation

Progressive Generation

Silent Generation

0%

1920

1930

1940

1950

1960

1970

1980

1990

2000

2010

2019

Gilded and Transcendental Generations

All generations come to an end eventually.

Even the greatest.

RELATIVE POPULATION DISTRIBUTION OF

AGE GENERATIONS

FROM 1920 THROUGH 2019

Based on estimates from the Decennial Census and the American Community Survey

Gilded and Transcendental

Progressive

Greatest

Lost

Missionary

0%

20%

40%

60%

80%

100%

1920

1930

1940

1950

1960

1970

1980

1990

2000

2010

2019

0%

20%

40%

60%

80%

100%

Alpha

Z

Millennials

X

Boomers

Silent

The Census Bureau released counts for 2020, but only at the national and state levels. So the most recent count available by age uses estimates from the 2019 American Community Survey. As time does, the older generations will shift down a bit, and Generation Alpha will grow.

See here for a more detailed view of the distribution for 2019.

Chart Type Used

Stacked Bar Chart

Become a member. Support an independent site. Make great charts.

Join Now

Learn to Visualize Data See All →

How I Made That: Animated Square Pie Chart

Also known as waffle charts. Using animated transitions between values, you can allow for comparisons between categories.

How to Make Symbol-based Glyph Charts, with R Examples

Using geometric shapes as an encoding can provide another dimension to your charts.

How to Make a Bump Chart in R

Visualize rankings over time instead of absolute values to focus on order instead of the magnitude of change.

How to visualize data with cartoonish faces ala Chernoff

The goal of Chernoff faces is to show a bunch of variables at once via facial features like lips, eyes, and nose size. Most of the time there are better solutions, but the faces can be interesting to work with.