Rising and falling dog names

How each name's share of registered dogs changed between the first and last years of data in Allegheny County, New York City, Sweden, Toronto, Cambridge, Vancouver, Zurich, Worcester and Basel, averaged over the places.

Rising

Name	Change	Dogs, early → late years
Iris	45.9×	Sweden 0 → 3515; New York City 20 → 9
Goose	14.4×	New York City 26 → 48; Allegheny County 3 → 40
Greta	12.0×	Sweden 0 → 2690; Allegheny County 69 → 17; New York City 25 → 9
Ghost	10.8×	New York City 22 → 28; Allegheny County 2 → 25
Arlo	9.3×	Toronto 10 → 130; Allegheny County 10 → 35; New York City 26 → 35
Birdie	6.7×	New York City 30 → 27; Allegheny County 5 → 23
Maple	6.6×	Toronto 51 → 165; New York City 32 → 61; Allegheny County 11 → 34
Mochi	5.5×	Toronto 16 → 131; New York City 75 → 85
Nova	5.5×	Sweden 6068 → 7011; Toronto 22 → 136; New York City 43 → 90
Yuki	5.4×	Toronto 27 → 86; Zurich 1 → 41; Basel 0 → 34
Maisie	5.3×	Toronto 19 → 114; New York City 33 → 25; Allegheny County 10 → 22
Loki	5.3×	Toronto 96 → 243; New York City 106 → 92; Allegheny County 51 → 80
Finley	5.3×	Toronto 34 → 75; Allegheny County 5 → 25; New York City 21 → 21
Ollie	5.2×	Toronto 111 → 288; New York City 126 → 110; Allegheny County 41 → 50
Hazel	4.8×	Toronto 72 → 192; New York City 157 → 90; Allegheny County 28 → 61
Maya	4.6×	Sweden 0 → 2694; Toronto 235 → 229; New York City 138 → 50
Atlas	4.6×	Sweden 3574 → 5506; Allegheny County 6 → 28; New York City 18 → 27
River	4.6×	Toronto 39 → 84; New York City 26 → 35; Allegheny County 14 → 29
Koda	4.5×	Toronto 63 → 132; Allegheny County 71 → 64; New York City 50 → 55
Freya	4.5×	Toronto 17 → 31; Zurich 2 → 26; Allegheny County 10 → 25
Poppy	4.4×	Toronto 91 → 250; New York City 54 → 68; Allegheny County 26 → 64
Balu	4.3×	Zurich 24 → 53; Basel 1 → 44
Mabel	4.2×	Toronto 41 → 96; New York City 63 → 51; Allegheny County 15 → 36
Willow	4.1×	Toronto 151 → 329; Allegheny County 67 → 103; New York City 85 → 81
Archie	4.1×	Toronto 124 → 338; New York City 110 → 94; Allegheny County 51 → 68
Oakley	4.1×	Toronto 45 → 107; Allegheny County 32 → 56; New York City 25 → 24
Finn	4.0×	Toronto 100 → 217; New York City 82 → 70; Allegheny County 12 → 64
Butters	4.0×	Allegheny County 9 → 18; New York City 27 → 16
Franklin	3.8×	New York City 48 → 40; Allegheny County 19 → 24
Lilly	3.7×	Sweden 0 → 3322; Toronto 124 → 84; Zurich 33 → 60
Kai	3.7×	Toronto 27 → 85; New York City 34 → 37; Allegheny County 14 → 12
Bonnie	3.7×	Sweden 0 → 4174; Toronto 121 → 82; New York City 81 → 38
Luna	3.6×	Sweden 4092 → 10626; Toronto 292 → 1008; New York City 513 → 451
Theo	3.6×	Toronto 48 → 137; New York City 61 → 63; Allegheny County 16 → 30
Blu	3.5×	New York City 83 → 36; Toronto 5 → 31; Allegheny County 15 → 18
Bowie	3.5×	Toronto 30 → 140; New York City 67 → 39; Allegheny County 13 → 12
Aspen	3.4×	Allegheny County 23 → 25; New York City 22 → 17
Otto	3.3×	Sweden 0 → 3292; New York City 79 → 24; Allegheny County 64 → 18
Nugget	3.3×	Toronto 16 → 71; New York City 32 → 34; Allegheny County 51 → 22
Stevie	3.2×	New York City 40 → 41; Toronto 10 → 32

Falling

Name	Change	Dogs, early → late years
Casey	0.07×	Worcester 67 → 13; New York City 126 → 10; Allegheny County 491 → 7
Madison	0.08×	New York City 152 → 13; Allegheny County 181 → 1; Toronto 94 → 0
Tess	0.09×	Allegheny County 93 → 5; Toronto 103 → 0
Kelsey	0.10×	Allegheny County 49 → 0; Toronto 51 → 0
Tia	0.10×	Allegheny County 63 → 2; Toronto 81 → 0
Brandy	0.10×	New York City 89 → 15; Worcester 64 → 10; Allegheny County 283 → 4
Lexus	0.10×	Allegheny County 62 → 0; Toronto 38 → 0
Samantha	0.10×	Allegheny County 201 → 6; Worcester 62 → 6; New York City 102 → 5
Sheba	0.11×	Allegheny County 214 → 8; New York City 69 → 8; Worcester 71 → 5
Mackenzie	0.11×	Allegheny County 36 → 0; Toronto 54 → 0
Abbie	0.11×	Allegheny County 63 → 1; Toronto 47 → 0
Molson	0.11×	Allegheny County 25 → 0; Toronto 71 → 0
Nikki	0.11×	Allegheny County 207 → 7; New York City 72 → 7; Worcester 29 → 3
Scruffy	0.11×	Allegheny County 114 → 4; New York City 55 → 2; Toronto 83 → 0
Mercedes	0.12×	Allegheny County 51 → 0; Toronto 31 → 0
Nikita	0.12×	Allegheny County 78 → 5; Toronto 73 → 0
Abbey	0.12×	Allegheny County 157 → 8; New York City 31 → 1; Toronto 108 → 0
Katie	0.13×	Worcester 22 → 10; Allegheny County 242 → 8; New York City 76 → 5
Jessie	0.13×	Allegheny County 159 → 14; New York City 71 → 10; Toronto 265 → 0
Sandy	0.13×	New York City 203 → 42; Allegheny County 270 → 17; Worcester 56 → 11
Sparky	0.14×	New York City 194 → 18; Worcester 15 → 12; Allegheny County 235 → 9
Sierra	0.14×	Allegheny County 112 → 7; Toronto 47 → 0
Jesse	0.14×	New York City 59 → 7; Allegheny County 103 → 4; Toronto 102 → 0
Taffy	0.14×	New York City 23 → 4; Allegheny County 101 → 1; Toronto 82 → 0
Chelsea	0.14×	New York City 66 → 13; Worcester 24 → 8; Allegheny County 137 → 3
Missy	0.14×	New York City 153 → 33; Allegheny County 303 → 13; Worcester 42 → 11
Buttons	0.15×	New York City 43 → 4; Allegheny County 99 → 1; Toronto 44 → 0
Cheyenne	0.15×	Allegheny County 129 → 4; Toronto 25 → 0
Samson	0.15×	New York City 110 → 15; Allegheny County 174 → 7; Toronto 87 → 0
Mandy	0.15×	New York City 39 → 6; Allegheny County 208 → 5; Toronto 69 → 0
Jazz	0.15×	New York City 35 → 7; Allegheny County 58 → 1; Toronto 127 → 0
Morgan	0.15×	New York City 32 → 6; Allegheny County 131 → 2; Toronto 72 → 0
Ally	0.15×	Allegheny County 47 → 2; Toronto 42 → 0
Tasha	0.15×	Allegheny County 99 → 5; New York City 27 → 5; Worcester 37 → 3
Haley	0.15×	Allegheny County 92 → 3; Toronto 26 → 0
Cassie	0.16×	New York City 62 → 11; Allegheny County 181 → 8; Toronto 101 → 0
Spencer	0.16×	Allegheny County 117 → 9; New York City 65 → 7; Toronto 113 → 0
Taz	0.16×	New York City 62 → 16; Allegheny County 182 → 8; Worcester 25 → 3
Ben	0.16×	Allegheny County 152 → 12; New York City 57 → 11; Toronto 177 → 0
Patches	0.16×	Worcester 20 → 13; Allegheny County 206 → 7; New York City 70 → 5

"Early" and "late" are the first two and last two years with enough data in each place. The change is relative to all dogs registered in those years.