if (!require("pacman")) install.packages("pacman")
## Loading required package: pacman
library(readxl)
SilverSagebrushData2024 <- read_excel("C:/Users/tlittmann/USDA/Rangeland responses to fire - Sagebrush/A_cana/Data/SilverSagebrushData2024.xlsx")
## New names:
## • `` -> `...10`
## • `` -> `...11`
View(SilverSagebrushData2024)
summary(SilverSagebrushData2024)
## Plot Shrub ID Height (cm) D1 (cm)
## Min. :501.0 Min. : 1.00 Min. : 0.00 Min. : 0.00
## 1st Qu.:507.0 1st Qu.: 19.75 1st Qu.: 0.00 1st Qu.: 0.00
## Median :513.5 Median : 38.50 Median : 52.00 Median : 45.00
## Mean :513.2 Mean : 74.14 Mean : 44.14 Mean : 54.76
## 3rd Qu.:519.2 3rd Qu.:131.50 3rd Qu.: 69.25 3rd Qu.: 95.00
## Max. :525.0 Max. :215.00 Max. :130.00 Max. :181.00
## D2 (cm) # of Stems # of Resprouts Length of Resprouts
## Min. : 0.00 Min. : 0.0 Length:80 Length:80
## 1st Qu.: 0.00 1st Qu.: 0.0 Class :character Class :character
## Median : 35.00 Median : 2.0 Mode :character Mode :character
## Mean : 40.61 Mean : 3.8
## 3rd Qu.: 65.50 3rd Qu.: 5.0
## Max. :136.00 Max. :23.0
## Gall Index ...10 ...11
## Min. :0.000 Mode:logical Length:80
## 1st Qu.:0.000 NA's:80 Class :character
## Median :0.000 Mode :character
## Mean :0.125
## 3rd Qu.:0.000
## Max. :1.000
str(SilverSagebrushData2024)
## tibble [80 × 11] (S3: tbl_df/tbl/data.frame)
## $ Plot : num [1:80] 501 501 501 502 502 502 503 503 503 504 ...
## $ Shrub ID : num [1:80] 1 2 3 102 104 106 4 5 6 7 ...
## $ Height (cm) : num [1:80] 0 0 0 0 0 0 124 94 100 0 ...
## $ D1 (cm) : num [1:80] 0 0 0 0 0 0 181 116 160 0 ...
## $ D2 (cm) : num [1:80] 0 0 0 0 0 0 112 107 124 0 ...
## $ # of Stems : num [1:80] 0 0 0 0 0 0 5 2 1 0 ...
## $ # of Resprouts : chr [1:80] "0" "0" "0" "0" ...
## $ Length of Resprouts: chr [1:80] "0" "0" "0" "0" ...
## $ Gall Index : num [1:80] 0 0 0 0 0 0 1 0 0 0 ...
## $ ...10 : logi [1:80] NA NA NA NA NA NA ...
## $ ...11 : chr [1:80] NA NA NA NA ...
data1 <- c(SilverSagebrushData2024$`Height (cm)`)
data1
## [1] 0 0 0 0 0 0 124 94 100 0 0 0 72 49 0 58 89 130 130
## [20] 0 54 0 52 0 0 68 59 58 53 38 0 79 71 71 0 58 58 0
## [39] 92 38 0 50 99 99 52 52 76 76 52 58 76 0 0 0 63 0 33
## [58] 0 48 63 77 77 57 110 57 36 36 57 66 48 0 69 62 0 70 52
## [77] 27 0 0 38
mean(data1)
## [1] 44.1375
dim(SilverSagebrushData2024)
## [1] 80 11
names(SilverSagebrushData2024)
## [1] "Plot" "Shrub ID" "Height (cm)"
## [4] "D1 (cm)" "D2 (cm)" "# of Stems"
## [7] "# of Resprouts" "Length of Resprouts" "Gall Index"
## [10] "...10" "...11"
head(SilverSagebrushData2024$`Shrub ID`[4])
## [1] 102
##Manipulation
columns <- names(SilverSagebrushData2024)
columns
## [1] "Plot" "Shrub ID" "Height (cm)"
## [4] "D1 (cm)" "D2 (cm)" "# of Stems"
## [7] "# of Resprouts" "Length of Resprouts" "Gall Index"
## [10] "...10" "...11"
for( i in 1:length(columns)) {
column = columns[i]
print(head(SilverSagebrushData2024[[column]]))
}
## [1] 501 501 501 502 502 502
## [1] 1 2 3 102 104 106
## [1] 0 0 0 0 0 0
## [1] 0 0 0 0 0 0
## [1] 0 0 0 0 0 0
## [1] 0 0 0 0 0 0
## [1] "0" "0" "0" "0" "0" "0"
## [1] "0" "0" "0" "0" "0" "0"
## [1] 0 0 0 0 0 0
## [1] NA NA NA NA NA NA
## [1] NA NA NA NA "." NA
i
## [1] 11
# Sample vector
values <- c(data1)
# Initialize an empty vector to store non-zero values
non_zero_values <- c()
# Loop through each value in the vector
for (value in values) {
# Check if the value is not zero
if (value != 0) {
# Append the non-zero value to the new vector
non_zero_values <- c(non_zero_values, value)
}
}
# Print the result
print(non_zero_values)
## [1] 124 94 100 72 49 58 89 130 130 54 52 68 59 58 53 38 79 71 71
## [20] 58 58 92 38 50 99 99 52 52 76 76 52 58 76 63 33 48 63 77
## [39] 77 57 110 57 36 36 57 66 48 69 62 70 52 27 38
###Histo it foo
hist(non_zero_values,
main="Histogram of Sage Height",
xlab="Height cm",
ylab = "Number of Plants",
col="red",
border="black")