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Most popular Collie, Rough Coat names

The names real owners gave 107 Collie, Rough Coats in public license and shelter records.

Top 94 names

  1. Jack3
  2. Luna3
  3. Muffin2
  4. Bernie2
  5. Amber2
  6. Ginger2
  7. Harley2
  8. Gerda2
  9. Jelly2
  10. Toby2
  11. Jupiter2
  12. Tuffy1
  13. Charlie1
  14. Bailey1
  15. Kluge1
  16. Hoa1
  17. Odin1
  18. Reilly1
  19. Chiko1
  20. Ellie1
  21. Adele1
  22. Marco1
  23. Richmond1
  24. Kelahers1
  25. Princess1
  26. King1
  27. Elsie1
  28. Zara1
  29. Ella1
  30. Sara1
  31. Brandon1
  32. Angelica1
  33. Starburst1
  34. Lexie1
  35. Oliver1
  36. Mac1
  37. Paisley1
  38. Tommy1
  39. Kuddie1
  40. Leo1
  41. Flynn1
  42. Colby1
  43. Audrey1
  44. Bishop1
  45. Coco1
  46. Lel1
  47. Raja1
  48. Piper1
  49. Millie1
  50. Lemmy1
  51. Kaya1
  52. Doudou1
  53. Maisie1
  54. Obi1
  55. Jessie1
  56. Laddie1
  57. Walter1
  58. Lily1
  59. Palma1
  60. Agnes1
  61. Chanel1
  62. Albus1
  63. Colorado1
  64. Tyndall1
  65. Domi1
  66. Michael1
  67. Mili1
  68. Neu1
  69. Xido1
  70. Tiberius1
  71. Mitzi1
  72. Rocky1
  73. Dakota1
  74. Sakura1
  75. Adric1
  76. Van-m1
  77. Tony1
  78. April1
  79. Tully1
  80. Aura1
  81. Daphne1
  82. Niffler1
  83. Joey1
  84. Edie1
  85. Abbey1
  86. Foxie-vienna1
  87. Bella1
  88. Krescent1
  89. Kraedinblu1
  90. Abby1
  91. Possum1
  92. Bandit1
  93. Penny1
  94. Chester1
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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.