Report 2
Tyler Von Bargen
2024-10-07
Columbus Weather
The plots below show you the median temperatures in each month as well as the absolute maximum and minimum temperatures in each month
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## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
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## Loading required package: RSQLite## Rows: 3287 Columns: 9
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): STATION, NAME, DATE
## dbl (6): YEAR, MONTH, DAY, Avg_Wind_Speed, Max_Temp, Min_Temp
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## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Including Plots
Which month of the year has the most varying temperatures?
Which month of the year had the highest average temperature?
## MONTH AverageMaxTemp StandardDeviationMaxTemp AverageMinTemp
## 1 1 36.11111 12.800567 21.10394
## 2 2 40.11811 13.896065 23.87795
## 3 3 51.79570 12.805596 33.12186
## 4 4 65.07037 10.477745 43.18519
## 5 5 76.02509 10.005542 55.79928
## 6 6 82.95185 6.494600 63.20000
## 7 7 85.70968 5.862785 66.78853
## 8 8 84.57706 4.950871 64.96416
## 9 9 78.35556 8.496198 58.19259
## 10 10 65.91398 10.970847 46.44444
## 11 11 52.36296 11.180910 34.74074
## 12 12 42.18638 11.473508 29.16487
## StandardDeviationMinTemp
## 1 12.359714
## 2 12.246677
## 3 10.438904
## 4 9.202541
## 5 8.999752
## 6 6.006564
## 7 5.158817
## 8 5.244950
## 9 7.679932
## 10 8.877441
## 11 8.867017
## 12 9.947057
## DATE Max_Temp
## 1 4/1/2018 51
## 2 4/10/2010 66
## 3 4/10/2011 84
## 4 4/10/2012 48
## 5 4/10/2013 82
## 6 4/10/2014 74
## 7 4/10/2015 70
## 8 4/10/2016 55
## 9 4/10/2017 80
## 10 4/10/2018 45
## 11 4/11/2010 73
## 12 4/11/2011 76
## 13 4/11/2012 50
## 14 4/11/2013 69
## 15 4/11/2014 68
## 16 4/11/2015 59
## 17 4/11/2016 59
## 18 4/11/2017 65
## 19 4/11/2018 62
## 20 4/12/2010 68
## 21 4/12/2011 55
## 22 4/12/2012 60
## 23 4/12/2013 60
## 24 4/12/2014 78
## 25 4/12/2015 69
## 26 4/12/2016 49
## 27 4/12/2017 67
## 28 4/12/2018 79
## 29 4/13/2010 65
## 30 4/13/2011 64
## 31 4/13/2012 66
## 32 4/13/2013 54
## 33 4/13/2014 80
## 34 4/13/2015 79
## 35 4/13/2016 58
## 36 4/13/2017 69
## 37 4/13/2018 82
## 38 4/14/2010 72
## 39 4/14/2011 71
## 40 4/14/2012 57
## 41 4/14/2013 66
## 42 4/14/2014 74
## 43 4/14/2015 61
## 44 4/14/2016 66
## 45 4/14/2017 76
## 46 4/14/2018 75
## 47 4/15/2010 84
## 48 4/15/2011 76
## 49 4/15/2012 78
## 50 4/15/2013 70
## 51 4/15/2014 45
## 52 4/15/2015 69
## 53 4/15/2016 74
## 54 4/15/2017 81
## 55 4/15/2018 61
## 56 4/16/2010 79
## 57 4/16/2011 60
## 58 4/16/2012 77
## 59 4/16/2013 79
## 60 4/16/2014 50
## 61 4/16/2015 62
## 62 4/16/2016 75
## 63 4/16/2017 80
## 64 4/16/2018 46
## 65 4/17/2010 56
## 66 4/17/2011 64
## 67 4/17/2012 63
## 68 4/17/2013 67
## 69 4/17/2014 68
## 70 4/17/2015 74
## 71 4/17/2016 80
## 72 4/17/2017 70
## 73 4/17/2018 37
## 74 4/18/2010 58
## 75 4/18/2011 73
## 76 4/18/2012 68
## 77 4/18/2013 86
## 78 4/18/2014 71
## 79 4/18/2015 79
## 80 4/18/2016 81
## 81 4/18/2017 76
## 82 4/18/2018 57
## 83 4/19/2010 63
## 84 4/19/2011 69
## 85 4/19/2012 74
## 86 4/19/2013 74
## 87 4/19/2014 67
## 88 4/19/2015 73
## 89 4/19/2016 73
## 90 4/19/2017 78
## 91 4/19/2018 52
## 92 4/2/2010 84
## 93 4/2/2011 50
## 94 4/2/2012 64
## 95 4/2/2013 45
## 96 4/2/2014 56
## 97 4/2/2015 63
## 98 4/2/2016 49
## 99 4/2/2017 63
## 100 4/2/2018 45
## 101 4/20/2010 65
## 102 4/20/2011 71
## 103 4/20/2012 78
## 104 4/20/2013 49
## 105 4/20/2014 77
## 106 4/20/2015 65
## 107 4/20/2016 77
## 108 4/20/2017 84
## 109 4/20/2018 58
## 110 4/21/2010 69
## 111 4/21/2011 57
## 112 4/21/2012 57
## 113 4/21/2013 55
## 114 4/21/2014 80
## 115 4/21/2015 61
## 116 4/21/2016 72
## 117 4/21/2017 68
## 118 4/21/2018 60
## 119 4/22/2010 70
## 120 4/22/2011 60
## 121 4/22/2012 51
## 122 4/22/2013 69
## 123 4/22/2014 72
## 124 4/22/2015 52
## 125 4/22/2016 69
## 126 4/22/2017 57
## 127 4/22/2018 69
## 128 4/23/2010 72
## 129 4/23/2011 70
## 130 4/23/2012 58
## 131 4/23/2013 72
## 132 4/23/2014 58
## 133 4/23/2015 50
## 134 4/23/2016 60
## 135 4/23/2017 71
## 136 4/23/2018 70
## 137 4/24/2010 69
## 138 4/24/2011 66
## 139 4/24/2012 64
## 140 4/24/2013 65
## 141 4/24/2014 63
## 142 4/24/2015 58
## 143 4/24/2016 71
## 144 4/24/2017 72
## 145 4/24/2018 56
## 146 4/25/2010 71
## 147 4/25/2011 74
## 148 4/25/2012 63
## 149 4/25/2013 57
## 150 4/25/2014 60
## 151 4/25/2015 51
## 152 4/25/2016 80
## 153 4/25/2017 76
## 154 4/25/2018 62
## 155 4/26/2010 57
## 156 4/26/2011 76
## 157 4/26/2012 63
## 158 4/26/2013 62
## 159 4/26/2014 74
## 160 4/26/2015 60
## 161 4/26/2016 80
## 162 4/26/2017 85
## 163 4/26/2018 67
## 164 4/27/2010 55
## 165 4/27/2011 74
## 166 4/27/2012 56
## 167 4/27/2013 72
## 168 4/27/2014 69
## 169 4/27/2015 54
## 170 4/27/2016 61
## 171 4/27/2017 76
## 172 4/27/2018 71
## 173 4/28/2010 61
## 174 4/28/2011 66
## 175 4/28/2012 51
## 176 4/28/2013 65
## 177 4/28/2014 59
## 178 4/28/2015 63
## 179 4/28/2016 65
## 180 4/28/2017 72
## 181 4/28/2018 53
## 182 4/29/2010 70
## 183 4/29/2011 59
## 184 4/29/2012 70
## 185 4/29/2013 65
## 186 4/29/2014 78
## 187 4/29/2015 68
## 188 4/29/2016 59
## 189 4/29/2017 76
## 190 4/29/2018 58
## 191 4/3/2010 80
## 192 4/3/2011 63
## 193 4/3/2012 65
## 194 4/3/2013 47
## 195 4/3/2014 56
## 196 4/3/2015 62
## 197 4/3/2016 54
## 198 4/3/2017 69
## 199 4/3/2018 62
## 200 4/30/2010 82
## 201 4/30/2011 67
## 202 4/30/2012 84
## 203 4/30/2013 76
## 204 4/30/2014 64
## 205 4/30/2015 57
## 206 4/30/2016 56
## 207 4/30/2017 85
## 208 4/30/2018 70