Week 4: Apply 3
Michael Kulig
2024-02-15
Import data
# csv file
data <- read.csv("data/MKmyData.csv")
data## Column1 ID.on.Tag Animal.Name Scientific.Name
## 1 1 Tommy-Tag Tommy Felis catus
## 2 2 Athena Athena Felis catus
## 3 3 Ares Ares Felis catus
## 4 4 Lola Lola Felis catus
## 5 5 Maverick Maverick Felis catus
## 6 6 Coco Coco Felis catus
## 7 7 Charlie Charlie Felis catus
## 8 8 Jago Jago Felis catus
## 9 9 Morpheus-Tag Morpheus Felis catus
## 10 10 Nettle-Tag Nettle Felis catus
## 11 11 Meg-Tag Meg Felis catus
## 12 12 Friday Friday Felis catus
## 13 13 Carbonel-Tag Carbonel Felis catus
## 14 14 Fonzie-Tag Fonzie Felis catus
## 15 15 Jessy-Tag Jessy Felis catus
## 16 16 Barney-Tag Barney Felis catus
## 17 17 Sparky-Tag Sparky Felis catus
## 18 18 Indie-Tag Indie Felis catus
## 19 19 Whiskey-Tag Whiskey Felis catus
## 20 20 Rusty-Tag Rusty Felis catus
## 21 21 Mifty-Tag Mifty Felis catus
## 22 22 Wilfred-Tag Wilfred Felis catus
## 23 23 Johnny-Tag Johnny Felis catus
## 24 24 Poppet-Tag Poppet Felis catus
## 25 25 Pussy-Tag Pussy Felis catus
## 26 26 Henry-Tag Henry Felis catus
## 27 27 Winnie-Tag Winnie Felis catus
## 28 28 Tom-Tag Tom Felis catus
## 29 29 Lady T-Tag Lady T Felis catus
## 30 30 Bella-Tag Bella Felis catus
## 31 31 Ladyboyhawke-Tag Ladyboyhawke Felis catus
## 32 32 Charlie2-Tag Charlie2 Felis catus
## 33 33 Max-Tag Max Felis catus
## 34 34 Ebby-Tag Ebby Felis catus
## 35 35 Bear-Tag Bear Felis catus
## 36 36 Bumbles-Tag Bumbles Felis catus
## 37 37 Chloe-Tag Chloe Felis catus
## 38 38 Merlin-Tag Merlin Felis catus
## 39 39 Felix-Tag Felix Felis catus
## 40 40 Beanie-Tag Beanie Felis catus
## 41 41 Sid-Tag Sid Felis catus
## 42 42 Binky-Tag Binky Felis catus
## 43 43 Amber-Tag Amber Felis catus
## 44 44 Ernie-Tag Ernie Felis catus
## 45 45 Bits-Tag Bits Felis catus
## 46 46 Maxwell-Tag Maxwell Felis catus
## 47 47 Lightening Bugg-Tag Lightening Bugg Felis catus
## 48 48 Bobs-Tag Bobs Felis catus
## 49 49 Carrots-Tag Carrots Felis catus
## 50 50 Smudge-Tag Smudge Felis catus
## 51 51 Magic-Tag Magic Felis catus
## 52 52 Spike-Tag Spike Felis catus
## 53 53 Dory-Tag Dory Felis catus
## 54 54 Tigger-Tag Tigger Felis catus
## 55 55 Jago2-Tag Jago2 Felis catus
## 56 56 Frank-Tag Frank Felis catus
## 57 57 Skye-Tag Skye Felis catus
## 58 58 Jezebel-Tag Jezebel Felis catus
## 59 59 Boots-Tag Boots Felis catus
## 60 60 Smudge_2-Tag Smudge_2 Felis catus
## 61 61 Frank_2-Tag Frank_2 Felis catus
## 62 62 Freya-Tag Freya Felis catus
## 63 63 Spot-Tag Spot Felis catus
## 64 64 Tipsy-Tag Tipsy Felis catus
## 65 65 Flash-Tag Flash Felis catus
## 66 66 Gracie-Tag Gracie Felis catus
## 67 67 Teddy-Tag Teddy Felis catus
## 68 68 Marley-Tag Marley Felis catus
## 69 69 Guinness-Tag Guinness Felis catus
## 70 70 Reggie-Tag Reggie Felis catus
## 71 71 Jessie-Tag Jessie Felis catus
## 72 72 Roger-Tag Roger Felis catus
## 73 73 Gracie_2-Tag Gracie_2 Felis catus
## 74 74 Dexter-Tag Dexter Felis catus
## 75 75 Tilly-Tag Tilly Felis catus
## 76 76 Balu-Tag Balu Felis catus
## 77 77 Missy-Tag Missy Felis catus
## 78 78 Dexter2-Tag Dexter2 Felis catus
## 79 79 Fairclough-Tag Fairclough Felis catus
## 80 80 Keegan-Tag Keegan Felis catus
## 81 81 Maggie-Tag Maggie Felis catus
## 82 82 Lily-Tag Lily Felis catus
## 83 83 Abba-Tag Abba Felis catus
## 84 84 Worf-Tag Worf Felis catus
## 85 85 Pants-Tag Pants Felis catus
## 86 86 Jim-Tag Jim Felis catus
## 87 87 Lucy-Tag Lucy Felis catus
## 88 88 Macaulay Mccat-Tag Macaulay Mccat Felis catus
## 89 89 Neil-Tag Neil Felis catus
## 90 90 Siberia-Tag Siberia Felis catus
## 91 91 Moscow-Tag Moscow Felis catus
## 92 92 Neva-Tag Neva Felis catus
## 93 93 Alfie-Tag Alfie Felis catus
## 94 94 Casper-Tag Casper Felis catus
## 95 95 Ginge-Tag Ginge Felis catus
## 96 96 Jasper-Tag Jasper Felis catus
## 97 97 Charlie3-Tag Charlie3 Felis catus
## 98 98 Millie-Tag Millie Felis catus
## 99 99 SmokeyLongnose-Tag SmokeyLongnose Felis catus
## 100 100 CJ-Tag CJ Felis catus
## 101 101 Seb-Tag Seb Felis catus
## Tag.Deployment.Start Tag.Deployment.End Hunt. X..Prey.per.Month
## 1 6/3/17 1:02 6/10/17 2:10 TRUE 12.5
## 2 6/24/17 1:02 6/30/17 23:59 TRUE 3.0
## 3 6/24/17 1:03 6/30/17 23:58 NA 0.0
## 4 6/24/17 1:18 6/30/17 9:04 TRUE 3.0
## 5 6/25/17 1:04 7/3/17 9:10 TRUE 3.0
## 6 6/28/17 1:02 7/5/17 6:50 TRUE 3.0
## 7 6/28/17 1:03 7/4/17 7:08 TRUE 3.0
## 8 6/28/17 4:10 7/4/17 2:50 TRUE 17.5
## 9 7/1/17 1:02 7/9/17 6:39 TRUE 3.0
## 10 7/1/17 1:05 7/8/17 0:05 TRUE 7.5
## 11 7/2/17 1:02 7/9/17 0:36 TRUE 3.0
## 12 7/2/17 7:28 7/7/17 21:56 TRUE 0.5
## 13 7/7/17 1:01 7/14/17 2:51 FALSE 0.0
## 14 7/8/17 1:02 7/15/17 8:10 TRUE 0.5
## 15 7/8/17 1:02 7/8/17 13:12 TRUE 3.0
## 16 7/8/17 1:16 7/15/17 7:20 TRUE 0.5
## 17 7/8/17 2:36 7/15/17 1:56 TRUE 0.5
## 18 7/9/17 1:03 7/16/17 9:33 TRUE 0.5
## 19 7/9/17 1:04 7/16/17 3:11 TRUE 0.5
## 20 7/9/17 2:19 7/16/17 0:34 TRUE 3.0
## 21 7/13/17 1:01 7/20/17 0:31 TRUE 12.5
## 22 7/13/17 1:01 7/20/17 1:19 NA 0.0
## 23 7/13/17 1:02 7/16/17 0:08 TRUE 12.5
## 24 7/13/17 1:02 7/19/17 20:52 TRUE 3.0
## 25 7/13/17 1:05 7/20/17 16:06 TRUE 3.0
## 26 7/14/17 1:02 7/21/17 0:04 FALSE 0.0
## 27 7/16/17 1:02 7/23/17 0:11 TRUE 3.0
## 28 7/16/17 1:02 7/24/17 4:47 TRUE 12.5
## 29 7/16/17 1:03 7/23/17 15:06 TRUE 3.0
## 30 7/16/17 1:46 7/24/17 5:18 TRUE 7.5
## 31 7/16/17 22:26 7/22/17 1:36 TRUE 3.0
## 32 7/17/17 1:01 7/23/17 0:05 TRUE 3.0
## 33 7/17/17 1:03 7/23/17 5:19 TRUE 3.0
## 34 7/20/17 1:02 7/27/17 0:05 TRUE 3.0
## 35 7/20/17 1:03 7/27/17 4:17 TRUE 3.0
## 36 7/20/17 3:06 7/27/17 0:08 TRUE 3.0
## 37 7/20/17 3:29 7/26/17 19:25 TRUE 3.0
## 38 7/20/17 9:25 7/27/17 0:24 TRUE 7.5
## 39 7/22/17 1:02 7/26/17 0:50 TRUE 3.0
## 40 7/22/17 1:02 7/29/17 9:52 FALSE 0.0
## 41 7/22/17 1:04 7/29/17 10:23 TRUE 17.5
## 42 7/22/17 1:06 7/28/17 15:28 FALSE 0.0
## 43 7/28/17 1:03 8/4/17 0:07 TRUE 3.0
## 44 7/28/17 1:05 8/4/17 2:03 TRUE 3.0
## 45 7/29/17 1:02 7/31/17 0:44 TRUE 3.0
## 46 7/29/17 1:02 8/8/17 3:58 TRUE 17.5
## 47 7/29/17 1:02 8/3/17 3:57 NA 0.0
## 48 7/29/17 5:36 8/5/17 9:25 TRUE 3.0
## 49 8/25/17 1:01 9/1/17 19:04 TRUE 17.5
## 50 8/25/17 1:01 9/1/17 3:03 TRUE 3.0
## 51 8/25/17 1:02 8/25/17 17:06 TRUE 3.0
## 52 8/25/17 1:02 9/1/17 7:59 TRUE 7.5
## 53 8/25/17 1:03 9/1/17 0:05 TRUE 0.5
## 54 8/25/17 1:04 9/1/17 1:46 TRUE 0.5
## 55 8/25/17 1:05 9/1/17 18:46 FALSE 0.0
## 56 8/25/17 1:05 9/1/17 0:08 TRUE 3.0
## 57 8/25/17 1:22 9/1/17 8:15 TRUE 0.5
## 58 8/25/17 1:50 9/1/17 7:58 NA 0.0
## 59 8/25/17 2:00 8/31/17 4:48 FALSE 0.0
## 60 8/25/17 6:15 9/1/17 6:45 TRUE 0.5
## 61 8/26/17 1:03 9/2/17 8:21 FALSE 0.0
## 62 8/27/17 1:45 9/3/17 2:08 TRUE 0.5
## 63 8/27/17 2:19 9/2/17 6:37 TRUE 17.5
## 64 8/28/17 15:39 9/4/17 9:49 NA 0.0
## 65 8/28/17 23:51 9/4/17 10:28 TRUE 3.0
## 66 9/7/17 5:02 9/12/17 15:32 FALSE 0.0
## 67 9/10/17 1:46 9/13/17 7:46 TRUE 0.5
## 68 9/10/17 11:02 9/15/17 19:54 TRUE 0.5
## 69 9/13/17 18:02 9/18/17 0:05 TRUE 3.0
## 70 9/17/17 1:02 9/24/17 0:52 TRUE 7.5
## 71 9/17/17 1:04 10/16/17 0:05 TRUE 3.0
## 72 9/17/17 1:05 9/23/17 23:57 TRUE 0.5
## 73 9/17/17 1:21 9/22/17 16:15 TRUE 0.5
## 74 9/17/17 1:34 9/24/17 7:35 TRUE 3.0
## 75 9/17/17 2:53 9/24/17 4:27 TRUE 3.0
## 76 9/18/17 1:03 9/25/17 5:39 TRUE 3.0
## 77 9/18/17 6:57 9/25/17 6:46 TRUE 3.0
## 78 9/23/17 17:31 9/29/17 5:09 FALSE 0.0
## 79 9/24/17 1:02 10/1/17 0:31 FALSE 0.0
## 80 9/24/17 1:03 9/30/17 14:41 TRUE 3.0
## 81 9/25/17 1:03 10/2/17 17:22 NA 0.0
## 82 9/25/17 1:03 10/2/17 14:57 NA 0.0
## 83 9/25/17 1:19 10/2/17 11:04 TRUE 3.0
## 84 9/25/17 1:20 9/30/17 13:12 TRUE 7.5
## 85 9/28/17 1:02 10/3/17 10:45 NA 0.0
## 86 9/28/17 1:02 10/4/17 13:42 TRUE 3.0
## 87 9/29/17 0:01 10/6/17 0:44 TRUE 0.5
## 88 9/29/17 7:01 10/26/17 16:51 TRUE 17.5
## 89 9/30/17 4:28 10/7/17 0:04 NA 0.0
## 90 10/9/17 1:01 10/16/17 0:06 TRUE 3.0
## 91 10/23/17 1:02 10/30/17 2:21 TRUE 0.5
## 92 10/23/17 1:03 10/31/17 0:09 FALSE 0.0
## 93 10/23/17 1:03 10/30/17 10:20 TRUE 3.0
## 94 10/30/17 1:02 11/6/17 5:08 TRUE 0.5
## 95 10/30/17 1:05 11/7/17 19:55 TRUE 17.5
## 96 11/18/17 1:46 11/25/17 1:11 TRUE 12.5
## 97 11/20/17 1:16 11/26/17 0:38 TRUE 7.5
## 98 11/20/17 1:38 11/27/17 0:09 TRUE 7.5
## 99 11/20/17 1:47 11/27/17 2:53 TRUE 0.5
## 100 11/24/17 6:48 11/29/17 3:44 TRUE 0.5
## 101 11/24/17 9:43 11/30/17 0:52 TRUE 3.0
## Reproductive.Condition Sex Hours.Indoor.per.Day X..of.Cats.in.House
## 1 Neutered m 12.5 2
## 2 Spayed f 7.5 2
## 3 Neutered m 7.5 2
## 4 Spayed f 17.5 1
## 5 Neutered m 12.5 1
## 6 Spayed f 12.5 2
## 7 Neutered m 12.5 3
## 8 Neutered m 7.5 4
## 9 Neutered m 2.5 2
## 10 Spayed f 12.5 2
## 11 <NA> f 12.5 1
## 12 Neutered m 7.5 1
## 13 Neutered m 17.5 1
## 14 Neutered m 12.5 2
## 15 Spayed f 12.5 1
## 16 Neutered m 12.5 2
## 17 Spayed f 7.5 4
## 18 Neutered m 17.5 2
## 19 Neutered m 17.5 1
## 20 Neutered m 17.5 1
## 21 Spayed f 7.5 1
## 22 Neutered m 7.5 1
## 23 Neutered m 7.5 1
## 24 Spayed f 22.5 3
## 25 Neutered m 2.5 3
## 26 Neutered m 7.5 1
## 27 Neutered m 12.5 1
## 28 Spayed f 12.5 2
## 29 Neutered m 12.5 3
## 30 Spayed f 12.5 2
## 31 Spayed f 17.5 2
## 32 Neutered m 12.5 2
## 33 Neutered m 12.5 3
## 34 Spayed f 17.5 2
## 35 Neutered m 12.5 2
## 36 Spayed f 12.5 2
## 37 Spayed f 17.5 2
## 38 Neutered m 12.5 1
## 39 Neutered m 22.5 1
## 40 Neutered m 17.5 4
## 41 Spayed f 7.5 1
## 42 Neutered m 17.5 4
## 43 <NA> f 7.5 4
## 44 Neutered m 7.5 4
## 45 Spayed f 2.5 3
## 46 Neutered m 7.5 1
## 47 Neutered m 12.5 2
## 48 Spayed f 7.5 3
## 49 Neutered m 7.5 4
## 50 Neutered m 7.5 1
## 51 Spayed f 12.5 3
## 52 Neutered m 12.5 1
## 53 Not fixed f 7.5 2
## 54 Neutered m 7.5 1
## 55 Neutered m 12.5 1
## 56 Neutered m 7.5 1
## 57 Neutered m 12.5 4
## 58 Spayed f 17.5 4
## 59 Spayed f 22.5 4
## 60 Neutered m 17.5 3
## 61 Neutered m 7.5 4
## 62 Spayed f 12.5 3
## 63 Neutered m 7.5 4
## 64 Spayed f 17.5 1
## 65 Spayed f 17.5 2
## 66 Spayed f 22.5 1
## 67 Spayed f 12.5 3
## 68 Neutered m 7.5 1
## 69 Neutered m 17.5 1
## 70 Spayed f 12.5 3
## 71 Spayed f 7.5 1
## 72 Neutered m 17.5 2
## 73 Spayed f 17.5 2
## 74 Neutered m 12.5 1
## 75 Spayed f 12.5 3
## 76 Spayed f 2.5 1
## 77 Spayed f 7.5 2
## 78 Neutered m 2.5 1
## 79 Neutered m 17.5 2
## 80 Not fixed m 7.5 2
## 81 Spayed f 22.5 2
## 82 Spayed f 22.5 2
## 83 Spayed f 7.5 2
## 84 Spayed f 2.5 2
## 85 Neutered m 12.5 3
## 86 Spayed f 12.5 3
## 87 Spayed f 17.5 1
## 88 Spayed f 2.5 2
## 89 Neutered m 7.5 1
## 90 Neutered m 7.5 2
## 91 Neutered m 12.5 2
## 92 Spayed f 17.5 2
## 93 Neutered m 7.5 2
## 94 Neutered m 12.5 4
## 95 Neutered m 2.5 2
## 96 Neutered m 7.5 1
## 97 <NA> m 12.5 2
## 98 Spayed f 12.5 2
## 99 Spayed f 7.5 2
## 100 Neutered m 22.5 2
## 101 Neutered m 12.5 2
## Dry.Food. Wet.Food. Other.Food. Study.Location Age
## 1 TRUE TRUE FALSE UK 11
## 2 TRUE TRUE FALSE UK 3
## 3 TRUE TRUE FALSE UK 3
## 4 TRUE TRUE FALSE UK 10
## 5 TRUE TRUE TRUE UK 7
## 6 TRUE TRUE TRUE UK 7
## 7 TRUE TRUE FALSE UK 6
## 8 TRUE TRUE TRUE UK 2
## 9 TRUE FALSE NA UK 4
## 10 TRUE FALSE NA UK 4
## 11 TRUE TRUE TRUE UK 8
## 12 TRUE FALSE TRUE UK 1
## 13 TRUE FALSE FALSE UK 8
## 14 TRUE TRUE NA UK 10
## 15 TRUE TRUE TRUE UK 11
## 16 TRUE TRUE NA UK 11
## 17 TRUE TRUE FALSE UK 8
## 18 TRUE FALSE FALSE UK 3
## 19 TRUE TRUE TRUE UK 5
## 20 TRUE FALSE NA UK 4
## 21 TRUE TRUE FALSE UK 2
## 22 TRUE FALSE FALSE UK 6
## 23 TRUE TRUE FALSE UK NA
## 24 TRUE TRUE TRUE UK 10
## 25 TRUE FALSE TRUE UK 2
## 26 TRUE TRUE FALSE UK 8
## 27 TRUE TRUE FALSE UK 12
## 28 TRUE TRUE TRUE UK 3
## 29 TRUE TRUE TRUE UK 2
## 30 TRUE TRUE FALSE UK 3
## 31 TRUE TRUE TRUE UK 5
## 32 TRUE TRUE TRUE UK 9
## 33 TRUE TRUE FALSE UK 5
## 34 FALSE TRUE TRUE UK 10
## 35 TRUE TRUE NA UK 6
## 36 FALSE TRUE TRUE UK 12
## 37 TRUE TRUE NA UK 7
## 38 TRUE FALSE FALSE UK 5
## 39 TRUE TRUE FALSE UK 4
## 40 TRUE TRUE FALSE UK 4
## 41 TRUE FALSE FALSE UK 4
## 42 TRUE TRUE FALSE UK 4
## 43 TRUE TRUE TRUE UK 4
## 44 TRUE TRUE TRUE UK 1
## 45 TRUE FALSE TRUE UK 13
## 46 TRUE TRUE TRUE UK 6
## 47 TRUE FALSE FALSE UK 0
## 48 TRUE FALSE TRUE UK 13
## 49 TRUE TRUE FALSE UK 3
## 50 TRUE TRUE TRUE UK 3
## 51 TRUE FALSE FALSE UK 3
## 52 TRUE FALSE TRUE UK 0
## 53 TRUE TRUE TRUE UK 1
## 54 TRUE TRUE FALSE UK 3
## 55 TRUE TRUE NA UK 2
## 56 TRUE TRUE TRUE UK 4
## 57 TRUE TRUE FALSE UK 5
## 58 TRUE TRUE TRUE UK 14
## 59 TRUE TRUE TRUE UK 16
## 60 TRUE FALSE FALSE UK 7
## 61 TRUE TRUE FALSE UK 7
## 62 TRUE TRUE FALSE UK 4
## 63 TRUE TRUE TRUE UK 2
## 64 TRUE FALSE FALSE UK 0
## 65 TRUE TRUE TRUE UK 3
## 66 TRUE FALSE FALSE UK 2
## 67 TRUE TRUE FALSE UK 9
## 68 TRUE TRUE FALSE UK 1
## 69 TRUE TRUE TRUE UK 7
## 70 TRUE TRUE TRUE UK 8
## 71 TRUE TRUE FALSE UK 5
## 72 TRUE TRUE NA UK 6
## 73 TRUE TRUE NA UK 6
## 74 TRUE TRUE FALSE UK 3
## 75 TRUE FALSE FALSE UK 5
## 76 TRUE FALSE TRUE UK 7
## 77 TRUE TRUE FALSE UK 3
## 78 TRUE TRUE FALSE UK 1
## 79 TRUE TRUE FALSE UK 4
## 80 TRUE TRUE FALSE UK 3
## 81 TRUE FALSE FALSE UK 3
## 82 TRUE FALSE FALSE UK 9
## 83 TRUE FALSE FALSE UK 3
## 84 TRUE TRUE TRUE UK 8
## 85 TRUE FALSE TRUE UK 8
## 86 TRUE FALSE TRUE UK 8
## 87 TRUE TRUE TRUE UK 5
## 88 TRUE TRUE FALSE UK 6
## 89 TRUE TRUE FALSE UK 7
## 90 TRUE TRUE FALSE UK 8
## 91 TRUE FALSE TRUE UK 1
## 92 TRUE FALSE TRUE UK 4
## 93 TRUE TRUE TRUE UK 3
## 94 TRUE TRUE FALSE UK 6
## 95 TRUE FALSE TRUE UK 3
## 96 TRUE FALSE FALSE UK 2
## 97 FALSE TRUE TRUE UK 5
## 98 FALSE TRUE TRUE UK 3
## 99 TRUE TRUE TRUE UK 9
## 100 TRUE TRUE FALSE UK 5
## 101 TRUE FALSE FALSE UK 3Plot data
data %>%
ggplot(aes(Reproductive.Condition)) +
geom_bar()