It transforms hydrochemical data (cations and anions) so they can be plotted on piper_diagram().
piper_data_prep(data)
| data | A dataframe with cations and anions, with the following names: Ca, Mg, Na, K, Cl, SO4, CO3, HCO3 |
|---|
A dataframe with x and y coordinates and the rest of the original data
d = data.frame(Group = c('A','A','B','B'), Ca = c(120,150,110,52.6), Mg = c(78,160,110,28), Na = c(210,590,340,51.6), K = c(4.2,2,3.6,2.3), HCO3 = c(181,181,189,151), CO3 = 0, Cl = c(220,744,476,72.2), SO4 = c(560,1020,584,126)) piper_data_prep(d)#> # A tibble: 12 × 12 #> ID x y Group Ca Mg Na K HCO3 CO3 Cl SO4 #> <fct> <dbl> <dbl> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 1 57.4 25.9 A 120 78 210 4.2 181 0 220 560 #> 2 2 69.6 24.8 A 150 160 590 2 181 0 744 1020 #> 3 3 65.9 26.9 B 110 110 340 3.6 189 0 476 584 #> 4 4 47.7 27.8 B 52.6 28 51.6 2.3 151 0 72.2 126 #> 5 1 178. 48.3 A 120 78 210 4.2 181 0 220 560 #> 6 2 190. 40.5 A 150 160 590 2 181 0 744 1020 #> 7 3 188. 36.5 B 110 110 340 3.6 189 0 476 584 #> 8 4 167. 31.7 B 52.6 28 51.6 2.3 151 0 72.2 126 #> 9 1 124. 141. A 120 78 210 4.2 181 0 220 560 #> 10 2 134. 137. A 150 160 590 2 181 0 744 1020 #> 11 3 130. 138. B 110 110 340 3.6 189 0 476 584 #> 12 4 109. 133. B 52.6 28 51.6 2.3 151 0 72.2 126