Marriage: both_sexes.csv

Table actions

This table contains data behind the story Marriage Isn’t Dead — Yet.

Source for all data is Decennial Census (years 1960 to 2000) and American Community Survey (years 2001-2012), via IPUMS USA.

Except in the divorce file, figures represent share of the relevant population that has never been married (MARST == 6 in the IPUMS data). Note that in the story, charts generally show the share that have ever been married, which is simply 1 - n. In the divorce file, figures are share of the relevant population that is currently divorced, conditional on having ever been married.

Variable names are as follows. Number in variable names are age ranges, so all_2534 is the marriage rate for everyone ages 25 to 34.

Header Description
all Total (or all men/women in sex-specific files)
HS High school graduate or less (EDUCD < 65)
SC Some college (EDUCD >= 65 & <= 100)
BAp Bachelor's degree or more (EDUCD > 100)
BAo Bachelor's degree, no graduate degre (EDUCD > 100 & <= 113)
GD Graduate degree (EDUCD > 113)
White Non-Hispanic white
Black Black or African-American
Hisp Hispanic of any race
NE New England (REGION == 11)
MA Mid-Atlantic (REGION == 12)
Midwest Midwest (REGION == 21-23)
South South (REGION == 31-34)
Mountain Mountain West (REGION == 41)
Pacific Pacific (REGION == 42)
poor Family income in lowest 25%
mid Family income in middle 50%
rich Family income in top 25%
work Employed 50+ weeks prior year
nowork Not employed at least 50 weeks prior year
nokids_all No own children living at home
kids_all At least one own child living at home

Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub · About: simonw/fivethirtyeight-datasette

1 row where "date" is on date 2005-01-01

✎ View and edit SQL

This data as json, copyable, CSV (advanced)

Suggested facets: date (date)

Link rowid ▼ Unnamed: 0 year date all_2534 HS_2534 SC_2534 BAp_2534 BAo_2534 GD_2534 White_2534 Black_2534 Hisp_2534 NE_2534 MA_2534 Midwest_2534 South_2534 Mountain_2534 Pacific_2534 poor_2534 mid_2534 rich_2534 all_3544 HS_3544 SC_3544 BAp_3544 BAo_3544 GD_3544 White_3544 Black_3544 Hisp_3544 NE_3544 MA_3544 Midwest_3544 South_3544 Mountain_3544 Pacific_3544 poor_3544 mid_3544 rich_3544 all_4554 HS_4554 SC_4554 BAp_4554 BAo_4554 GD_4554 White_4554 Black_4554 Hisp_4554 NE_4554 MA_4554 Midwest_4554 South_4554 Mountain_4554 Pacific_4554 poor_4554 mid_4554 rich_4554 nokids_all_2534 kids_all_2534 nokids_HS_2534 nokids_SC_2534 nokids_BAp_2534 nokids_BAo_2534 nokids_GD_2534 kids_HS_2534 kids_SC_2534 kids_BAp_2534 kids_BAo_2534 kids_GD_2534 nokids_poor_2534 nokids_mid_2534 nokids_rich_2534 kids_poor_2534 kids_mid_2534 kids_rich_2534
10 10 10 2005 2005-01-01 0.379345137795961 0.387068030631773 0.359666265205879 0.388609649230315 0.402911610704289 0.35142507293975 0.34387589267402 0.575173098230383 0.358954377393946 0.450971885766113 0.463850807570628 0.362480457286156 0.34738207038469 0.341277703713612 0.403880731993575 0.551922358168366 0.347668291171296 0.262045219910141 0.16859543264941 0.186976371158716 0.154897817253754 0.156358906466591 0.157873061707162 0.153470271801194 0.14393043865501 0.323192040471345 0.165597802598456 0.188715702459965 0.202193854152008 0.154058391274609 0.154725154717489 0.153734702524598 0.189535426915303 0.310960351232642 0.147794239720269 0.0674847000861153 0.106627015398147 0.114840615808277 0.0950886859365206 0.106747463592565 0.106627734190588 0.106936441638197 0.0906698767953988 0.219160597910895 0.106415385615315 0.111831823021325 0.129886349528731 0.101912838982562 0.0976739569445206 0.0913300054359397 0.117546562182038 0.214221872018675 0.0903651519045544 0.0314321253119159 0.610130746652542 0.129535758883269 0.638869140556426 0.609708464540643 0.582372671428887 0.602887469451609 0.529404252074879 0.170866790324827 0.129908779666533 0.0457983664924681 0.0509958078564464 0.0321173492057131 0.737549169962846 0.608967574059662 0.471279251923952 0.323611416109805 0.0852490070564453 0.0313263995911071

Advanced export

JSON shape: default, array, newline-delimited

CSV options: 

CREATE TABLE "marriage/both_sexes" (
"Unnamed: 0" INTEGER,
  "year" INTEGER,
  "date" TEXT,
  "all_2534" REAL,
  "HS_2534" REAL,
  "SC_2534" REAL,
  "BAp_2534" REAL,
  "BAo_2534" REAL,
  "GD_2534" REAL,
  "White_2534" REAL,
  "Black_2534" REAL,
  "Hisp_2534" REAL,
  "NE_2534" REAL,
  "MA_2534" REAL,
  "Midwest_2534" REAL,
  "South_2534" REAL,
  "Mountain_2534" REAL,
  "Pacific_2534" REAL,
  "poor_2534" REAL,
  "mid_2534" REAL,
  "rich_2534" REAL,
  "all_3544" REAL,
  "HS_3544" REAL,
  "SC_3544" REAL,
  "BAp_3544" REAL,
  "BAo_3544" REAL,
  "GD_3544" REAL,
  "White_3544" REAL,
  "Black_3544" REAL,
  "Hisp_3544" REAL,
  "NE_3544" REAL,
  "MA_3544" REAL,
  "Midwest_3544" REAL,
  "South_3544" REAL,
  "Mountain_3544" REAL,
  "Pacific_3544" REAL,
  "poor_3544" REAL,
  "mid_3544" REAL,
  "rich_3544" REAL,
  "all_4554" REAL,
  "HS_4554" REAL,
  "SC_4554" REAL,
  "BAp_4554" REAL,
  "BAo_4554" REAL,
  "GD_4554" REAL,
  "White_4554" REAL,
  "Black_4554" REAL,
  "Hisp_4554" REAL,
  "NE_4554" REAL,
  "MA_4554" REAL,
  "Midwest_4554" REAL,
  "South_4554" REAL,
  "Mountain_4554" REAL,
  "Pacific_4554" REAL,
  "poor_4554" REAL,
  "mid_4554" REAL,
  "rich_4554" REAL,
  "nokids_all_2534" REAL,
  "kids_all_2534" REAL,
  "nokids_HS_2534" REAL,
  "nokids_SC_2534" REAL,
  "nokids_BAp_2534" REAL,
  "nokids_BAo_2534" REAL,
  "nokids_GD_2534" REAL,
  "kids_HS_2534" REAL,
  "kids_SC_2534" REAL,
  "kids_BAp_2534" REAL,
  "kids_BAo_2534" REAL,
  "kids_GD_2534" REAL,
  "nokids_poor_2534" REAL,
  "nokids_mid_2534" REAL,
  "nokids_rich_2534" REAL,
  "kids_poor_2534" REAL,
  "kids_mid_2534" REAL,
  "kids_rich_2534" REAL
);