Most popular Chihuahua, Short Coat names

The names real owners gave 1,340 Chihuahua, Short Coats in public license and shelter records.

Top 100 names

  1. Buddy10
  2. Bella9
  3. Luna9
  4. Peanut8
  5. Daisy8
  6. Lily7
  7. Honey7
  8. Lulu7
  9. Charlie7
  10. Oliver7
  11. Gigi6
  12. Rosie6
  13. Coco6
  14. Frankie6
  15. Toby6
  16. Lola5
  17. Brownie5
  18. Nina5
  19. Zoey5
  20. Penny5
  21. Chloe4
  22. Ivy4
  23. Olive4
  24. Birdie4
  25. Poppy4
  26. Maya4
  27. Bailey4
  28. Hazel4
  29. Bean4
  30. Roxy4
  31. Chip4
  32. Paco4
  33. Taco4
  34. Ziggy4
  35. Jake4
  36. Gizmo4
  37. Archie4
  38. Nelson4
  39. Milo4
  40. Prince4
  41. Miles4
  42. Spike4
  43. Ollie4
  44. Leo4
  45. Ella3
  46. Ellie3
  47. Pippa3
  48. Cleo3
  49. Toki3
  50. Estrella3
  51. Princess3
  52. Sandy3
  53. Ruby3
  54. Phoebe3
  55. Minnie3
  56. Nala3
  57. Lucy3
  58. Annie3
  59. Murphy3
  60. Bug3
  61. Missy3
  62. Moose3
  63. Luca3
  64. Iggy3
  65. Rudy3
  66. Louie3
  67. Momo3
  68. Rocky3
  69. Sammy3
  70. Dobby3
  71. Gustavo3
  72. Henry3
  73. Rufus3
  74. Joey3
  75. Zeus3
  76. Marco3
  77. Max3
  78. Teddy3
  79. Bentley3
  80. Jack3
  81. Auggie2
  82. Chiquita2
  83. Norma2
  84. Chalupa2
  85. Barley2
  86. Mantequilla2
  87. Gracie2
  88. Pocket2
  89. Ginger2
  90. Tiki2
  91. Vella2
  92. Sugar2
  93. Marley2
  94. Greta2
  95. Joy2
  96. Dave2
  97. Fiona2
  98. Kitty2
  99. Lilly2
  100. Pebbles2
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Counts come from public open data: NYC Dog Licensing Dataset (NYC Open Data); Seattle Pet Licenses (public domain); Dogs of Cambridge (ODC PDDL); Licensed Dog and Cat Names, City of Toronto (Open Government Licence – Toronto); Hundenamen, Stadt Zürich (Open Data Zürich); Dog Registrations, City of Adelaide (CC BY 3.0 AU); Burnside Dog Registrations (CC BY 3.0 AU); City of Prospect Dog Registrations (CC BY 3.0 AU); Pet Licenses, City of Richmond; Animal Shelter Intake and Outcome, County of Sonoma; Austin Animal Center Outcomes (public domain). License records count registered pets; shelter records count animals that passed through a shelter (some names are given by staff). Pets that appear in several years of one dataset are counted once. Names are counted as written, so spelling variants are separate.