DogpersonScubadivesDrove acar >1hour toget herePrefersto codein RPlays amusicalinstrumentWriteswikipediaarticlesSpeaks>2languagesIshungryright nowStarwarsfanHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingDoesnot likepizzaHas beento aconcert inlast monthKnows amagictrickPrefers tocode inMATLABHas beenat sea for>1 weekHas beento thePacificOceanHas aparrotHas workedin a cleanlab (on landor on a ship)Is anatmosphericscientistHasa catFlewhere ona planeHas aGitHubMovedhousewithin thelast yearWorkswithlidarHas beento theAtlanticOceanLovesrainbowunicornsWorkswithcitizenscientistsDoes adistancesportDoeslakescienceClimberDoesNOT liketo teachbut has toKnowswhat asundog isHasinteractedwith a CTD-RosetteCan tell afield workdisasterstoryknows 3TaylorSwiftsongsHas used asun-photometerPlays amusicalinstrumentFliesdronesHas useda weatherballoonModels(data orfashion)Hasconsideredbecomingan astronautHas beento theArcticOceanLives >2hoursdrive tothe oceanKnows moreaboutpolarimetrythan owningthe sunglassesPrefersto codein pythonHas beenat sea for>1 weekFilters alot ofseawaterHas doneairbornescienceBrewsbeerDid fieldwork inthe lastyearFlew aninstrumenton ER-2Does alot ofoutreachLovesaerosolsHas beento theSouthernOceanDogpersonScubadivesDrove acar >1hour toget herePrefersto codein RPlays amusicalinstrumentWriteswikipediaarticlesSpeaks>2languagesIshungryright nowStarwarsfanHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingDoesnot likepizzaHas beento aconcert inlast monthKnows amagictrickPrefers tocode inMATLABHas beenat sea for>1 weekHas beento thePacificOceanHas aparrotHas workedin a cleanlab (on landor on a ship)Is anatmosphericscientistHasa catFlewhere ona planeHas aGitHubMovedhousewithin thelast yearWorkswithlidarHas beento theAtlanticOceanLovesrainbowunicornsWorkswithcitizenscientistsDoes adistancesportDoeslakescienceClimberDoesNOT liketo teachbut has toKnowswhat asundog isHasinteractedwith a CTD-RosetteCan tell afield workdisasterstoryknows 3TaylorSwiftsongsHas used asun-photometerPlays amusicalinstrumentFliesdronesHas useda weatherballoonModels(data orfashion)Hasconsideredbecomingan astronautHas beento theArcticOceanLives >2hoursdrive tothe oceanKnows moreaboutpolarimetrythan owningthe sunglassesPrefersto codein pythonHas beenat sea for>1 weekFilters alot ofseawaterHas doneairbornescienceBrewsbeerDid fieldwork inthe lastyearFlew aninstrumenton ER-2Does alot ofoutreachLovesaerosolsHas beento theSouthernOcean

Human Bingo: Find someone who... - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Dog person
  2. Scuba dives
  3. Drove a car >1 hour to get here
  4. Prefers to code in R
  5. Plays a musical instrument
  6. Writes wikipedia articles
  7. Speaks >2 languages
  8. Is hungry right now
  9. Star wars fan
  10. Has called into a PACE Science & Applications Team (SAT) Meeting
  11. Does not like pizza
  12. Has been to a concert in last month
  13. Knows a magic trick
  14. Prefers to code in MATLAB
  15. Has been at sea for >1 week
  16. Has been to the Pacific Ocean
  17. Has a parrot
  18. Has worked in a clean lab (on land or on a ship)
  19. Is an atmospheric scientist
  20. Has a cat
  21. Flew here on a plane
  22. Has a GitHub
  23. Moved house within the last year
  24. Works with lidar
  25. Has been to the Atlantic Ocean
  26. Loves rainbow unicorns
  27. Works with citizen scientists
  28. Does a distance sport
  29. Does lake science
  30. Climber
  31. Does NOT like to teach but has to
  32. Knows what a sundog is
  33. Has interacted with a CTD-Rosette
  34. Can tell a field work disaster story
  35. knows 3 Taylor Swift songs
  36. Has used a sun-photometer
  37. Plays a musical instrument
  38. Flies drones
  39. Has used a weather balloon
  40. Models (data or fashion)
  41. Has considered becoming an astronaut
  42. Has been to the Arctic Ocean
  43. Lives >2 hours drive to the ocean
  44. Knows more about polarimetry than owning the sunglasses
  45. Prefers to code in python
  46. Has been at sea for >1 week
  47. Filters a lot of seawater
  48. Has done airborne science
  49. Brews beer
  50. Did field work in the last year
  51. Flew an instrument on ER-2
  52. Does a lot of outreach
  53. Loves aerosols
  54. Has been to the Southern Ocean