Number sites MME 2015-2020
09 February 2021
## [1] ""n
## # A tibble: 20 x 4
## # Groups: year [5]
## year damaged.qualitative n prop
## <int> <chr> <int> <dbl>
## 1 2015 Low 21 13.2
## 2 2015 Moderate 18 11.3
## 3 2015 No 102 64.2
## 4 2015 Severe 18 11.3
## 5 2016 Low 31 12.4
## 6 2016 Moderate 25 10
## 7 2016 No 120 48
## 8 2016 Severe 74 29.6
## 9 2017 Low 37 11.0
## 10 2017 Moderate 45 13.4
## 11 2017 No 179 53.1
## 12 2017 Severe 76 22.6
## 13 2018 Low 100 23.9
## 14 2018 Moderate 81 19.3
## 15 2018 No 172 41.1
## 16 2018 Severe 66 15.8
## 17 2019 Low 46 8.98
## 18 2019 Moderate 54 10.5
## 19 2019 No 202 39.5
## 20 2019 Severe 210 41.0## damaged.qualitative n prop
## 1 Low 235 14.01312
## 2 Moderate 223 13.29756
## 3 No 775 46.21348
## 4 Severe 444 26.47585## # A tibble: 55 x 4
## # Groups: year [5]
## year damaged.percentatge n prop
## <int> <chr> <int> <dbl>
## 1 2015 0-10 88 55.3
## 2 2015 11-20 11 6.92
## 3 2015 21-30 8 5.03
## 4 2015 31-40 4 2.52
## 5 2015 41-50 9 5.66
## 6 2015 51-60 4 2.52
## 7 2015 61-70 3 1.89
## 8 2015 71-80 2 1.26
## 9 2015 81-90 4 2.52
## 10 2015 91-100 7 4.40
## # ... with 45 more rows## damaged.percentatge n prop
## 1 0-10 772 46.034586
## 2 11-20 127 7.573047
## 3 21-30 107 6.380441
## 4 31-40 63 3.756708
## 5 41-50 95 5.664878
## 6 51-60 51 3.041145
## 7 61-70 39 2.325581
## 8 71-80 65 3.875969
## 9 81-90 60 3.577818
## 10 91-100 240 14.311270
## 11 <NA> 58 3.458557## # A tibble: 97 x 5
## # Groups: year [5]
## damaged.qualitative year lower.depth n prop
## <chr> <int> <chr> <int> <dbl>
## 1 Low 2015 0-10 11 6.92
## 2 Low 2015 11-20 8 5.03
## 3 Low 2015 21-30 2 1.26
## 4 Low 2016 >40 1 0.4
## 5 Low 2016 0-10 8 3.2
## 6 Low 2016 11-20 17 6.8
## 7 Low 2016 21-30 4 1.6
## 8 Low 2016 31-40 1 0.4
## 9 Low 2017 >40 1 0.297
## 10 Low 2017 0-10 18 5.34
## # ... with 87 more rows## # A tibble: 5 x 2
## year sum
## <int> <dbl>
## 1 2015 98.1
## 2 2016 95.6
## 3 2017 94.7
## 4 2018 100
## 5 2019 100
## [1] "#A50026" "#D73027" "#F46D43" "#FDAE61" "#FEE090" "#FFFFBF" "#E0F3F8"
## [8] "#ABD9E9" "#74ADD1" "#4575B4" "#313695"## # A tibble: 5 x 2
## year sum
## <int> <dbl>
## 1 2015 98.1
## 2 2016 95.6
## 3 2017 94.7
## 4 2018 100
## 5 2019 100
