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annotate div_index.r @ 0:a8924f69348d draft

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planemo upload for repository https://github.com/Marie59/champ_blocs commit 0d86db7d42b608c386a54500064f5f9c9d7019a4
author ecology
date Wed, 04 Jan 2023 13:21:04 +0000
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children eabd2cf09cf0
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a8924f69348d planemo upload for repository https://github.com/Marie59/champ_blocs commit 0d86db7d42b608c386a54500064f5f9c9d7019a4
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1 # author: "Jonathan Richir"
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2 # date: "01 October 2022"
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5 #Rscript
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7 ###############################
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8 ## ##
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9 ###############################
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11 #####Packages : dplyr
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12 # tidyr
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13 # readr
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14 # writexl
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15 # stringr
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16 # readxl
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17 # tibble
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18 # lubridate
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19 # cowplot
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20 # magrittr
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21 # rmarkdown
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22 library(magrittr)
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23 library(dplyr)
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24 #####Load arguments
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26 args <- commandArgs(trailingOnly = TRUE)
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28 #####Import data
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30 if (length(args) < 1) {
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31 stop("This tool needs at least 1 argument")
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32 }else {
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33 qecnato0 <- args[1]
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35 }
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37 qecnato0 <- readRDS(qecnato0)
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40 # first, create vector (4) for qecb and fishing by region (same as above)
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42 bret_egmp_basq_qecb <- c(
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43 "X..algues.brunes",
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44 "X..algues.rouges",
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45 "X..algues.vertes",
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46 "X..Cladophora",
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47 "X..Lithophyllum",
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48 "Nb.Littorina.obtusata",
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49 "Nb.Gibbula.cineraria",
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50 "Nb.Gibbula.pennanti",
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51 "Nb.Gibbula.umbilicalis",
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52 "Nb.Phallusia.mamillata",
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53 "Nb.Tethya.aurantium",
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54 "Nb.Spirobranchus.lamarckii.total",
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55 "Nb.spirorbis.total",
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56 "X..Eponges",
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57 "X..Ascidies.Coloniales",
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58 "X..Ascidies.Solitaires",
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59 "X..Bryozoaires.Dresses",
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60 "X..Balanes.Vivantes"
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61 #, "X..Recouvrement.Sediment"
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62 #, "X..Roche.Nue"
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63 #, "X..Surface.Accolement"
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64 )
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65
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66 egmp_basq_qecb <- c("Nb.Crassostrea.gigas", "Nb.Ostrea.edulis", "X..Mytilus.sp.", "X..Hermelles", "X..Hydraires")
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67
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68 bret_egmp_basq_fishing <- c("Nb.Cancer.pagurus..Tourteau.",
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69 "Nb.Necora.puber..Etrille.",
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70 "Nb.Carcinus.maenas..Crabe.vert.",
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71 "Nb.Nucella.lapilus..Pourpre.",
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72 "Nb.Galathea..Galathées.",
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73 "Nb.Lophozozymus.incisus..ancien.Xantho.incisus.",
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74 "Nb.Palaemon.sp..Crevette.bouquet.ou.crevette.rose.",
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75 "Nb.Haliotis.tuberculata..Ormeau.",
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76 "Nb.Littorina.littorea..Bigorneau.",
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77 "Nb.Xantho.pilipes..Xanthe.poilu.",
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78 "Nb.Mimachlamys.varia..Pétoncle.noir.")
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79
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80 egmp_basq_fishing <- c("Nb.Eriphia.verrucosa..Crabe.verruqueux.", "Nb.Octopus.vulgaris..Poulpe.", "Nb.Paracentrotus.lividus..Oursin.", "Nb.Stramonita.haemastoma..Pourpre.bouche.de.sang.")
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81
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82 # here I can choose to either replace spirorbis and/or spirobranchus by their log10 transformation in bret_egmp_basq_qecb vector
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83 bret_egmp_basq_qecb <- replace(bret_egmp_basq_qecb, bret_egmp_basq_qecb == "Nb.spirorbis.total", "log10.Nb.spirorbis.total")
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84
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85 ## Diversity index
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88 # adiv contains two main functions for species diversity indices: speciesdiv, which includes widely used indices such as species richness and the Shannon index, and divparam, which includes indices that have a parameter to control the importance given to rare versus abundant species in diversity measurements (Pavoine (2020) - adiv: An r package to analyse biodiversity in ecology).
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89
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90 # NB: just like for dissimilarity distance matrices, no sense to use the "fishing" variable lists, because either they are present for the bloc mobile and not for the bloc fixe (therefore false higher diversity for bloc mobile), either they are repeated between face supérieure and face inférieure of bloc mobile.
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92 # function in a loop
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94 row.names(qecnato0) <- c(paste0(qecnato0$region.site_year_month_day, "_", qecnato0$Quadrat.bis, "_", qecnato0$Type.Bloc, "_", qecnato0$Numéro.Bloc.échantillon, "_", qecnato0$Face))
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95
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96 # later on I can copy-paste above code to recreate variable names vector
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97 #bret_egmp_basq_qecb
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98 #egmp_basq_qecb
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99 #Bret_EGMP.BASQ_fishing
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100 #EGMP.BASQ_fishing
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101
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102 # remove boulder variables
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103 bret_egmp_basq_qecb <- bret_egmp_basq_qecb[! bret_egmp_basq_qecb %in% c("X..Recouvrement.Sediment", "X..Roche.Nue", "X..Surface.Accolement")]
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104
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105 qecnato0$period <- as.character(qecnato0$period)
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106 qecnato0$Face <- as.character(qecnato0$Face)
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107
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108 div_list <- vector("list", length(unique(qecnato0$site_year_month_day)))
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109
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110 for (i in c(1:nrow(qecnato0))) {
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111 div_i <- dplyr::filter(qecnato0, site_year_month_day == qecnato0$site_year_month_day[i])
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112
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113 ifelse(unique(div_i$region) == "Bretagne", var. <- c(bret_egmp_basq_qecb), var. <- c(bret_egmp_basq_qecb, egmp_basq_qecb)) # Qu. : Why can't R's ifelse statements return vectors? => you can circumvent the problem if you assign the result inside the ifelse.
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114
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115 #8 remove empty row cfr: In speciesdiv(div_i[, var.]) & divparam(div_i[, var.]) : empty communities should be discarded
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116 div_i <- dplyr::filter(div_i, rowSums(div_i[, var.]) > 0)
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117
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118 div_i_speciesdiv <- adiv::speciesdiv(div_i[, var.])
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119 adiv_i_df <- data.frame(div_i_speciesdiv)
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120
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121 div_i_divparam <- adiv::divparam(div_i[, var.], q = c(0, 0.25, 0.5, 1, 2, 4, 8)) # When q increases, abundant species are overweighted compared to rare species, we thus expect that the evenness in species weights decreases.
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122
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123
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124 par(mfrow = c (1, 1))
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125 plot(adiv::divparam(div_i[, var.], q = 0), main = unique(div_i$site_year_month_day))
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126 plot(adiv::divparam(div_i[, var.], q = 0:10), legend = FALSE, main = unique(div_i$site_year_month_day))
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127
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128 adiv_i_df$x <- div_i_divparam$div$`1`
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129 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[1], " (equi. richness)")
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130 adiv_i_df$x <- div_i_divparam$div$`2`
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131 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[2])
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132 adiv_i_df$x <- div_i_divparam$div$`3`
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133 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[3])
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134 adiv_i_df$x <- div_i_divparam$div$`4`
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135 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[4])
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136 adiv_i_df$x <- div_i_divparam$div$`5`
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137 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[5], " (equi. Simpson)")
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138 adiv_i_df$x <- div_i_divparam$div$`6`
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139 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[6])
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140 adiv_i_df$x <- div_i_divparam$div$`7`
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141 colnames(adiv_i_df)[which(colnames(adiv_i_df) == "x")] <- paste0("Para. ISD, q = ", div_i_divparam$q[7])
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142
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143 # plot
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144 par(mfrow = c(3, 2))
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145 sapply(names(adiv_i_df[, c(1, 8, 2, 3, 12, 4:7, 9:11, 13:ncol(adiv_i_df))]),
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146 function(cname) {
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147 png(paste0(cname, "_histo.png"))
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148 hist(adiv_i_df[, c(1, 8, 2, 3, 12, 4:7, 9:11, 13:ncol(adiv_i_df))][[cname]], main = "", xlab = cname, breaks = length(unique(adiv_i_df[, c(1, 8, 2, 3, 12, 4:7, 9:11, 13:ncol(adiv_i_df))][[cname]])))
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149 dev.off()
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150 }
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151
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152 )
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153 par(mfrow = c(1,1))
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154
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155 div_list[[i]] <- adiv_i_df
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156
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157 rm(div_i, adiv_i_df, div_i_speciesdiv, div_i_divparam)
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158
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159 }
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160
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161 # for the error message due to richness NA data => 35 observations in 21 surveys; no reason to remove these data "...remo", was checked in the complete script.
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162
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163
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164 div_df <- do.call("rbind", div_list)
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165
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166
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167 # There is an issue with region.terri that are merged with no "_" ...
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168
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169 div_df <- tibble::add_column(div_df, rownames. = rownames(div_df), .before = "richness")
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170 div_df <- tidyr::separate(div_df, rownames., into = c("region.terri.", "site_year_month_day", "Quadrat.bis", "Type.Bloc", "Numéro.Bloc.échantillon", "Face"), sep = "_")
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171
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172 # I therefore add these lines to solve that issue
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173
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174 div_df <- tibble::add_column(div_df, terri. = substring(div_df$region.terri., nchar(div_df$region.terri.)-3), .after = "region.terri.")
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175
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176 div_df$region.terri. <- substring(div_df$region.terri., 1, nchar(div_df$region.terri)-4)
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177 div_df <- dplyr::rename(div_df, region = region.terri.)
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178
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179 div_df$site_year_month_day <- paste0(div_df$terri., "_", div_df$site_year_month_day)
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180 div_df <- subset(div_df, select = -c(terri.))
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181
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182 div_df$Type.Bloc <- as.factor(div_df$Type.Bloc)
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183 div_df$Face <- as.factor(div_df$Face)
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184 div_df$Numéro.Bloc.échantillon <- as.integer(div_df$Numéro.Bloc.échantillon)
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185
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186 saveRDS(div_df, "div_df.RDS")
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parents:
diff changeset
187 write.table(div_df, "Valeurs_stat.tabular", row.names = FALSE, quote = FALSE, sep = "\t", dec = ".", fileEncoding = "UTF-8")