# NOT RUN {
library(metan)
################# Adding columns #################
# Variables x and y .after last column
data_ge %>%
add_cols(x = 10,
y = 30)
# Variables x and y .before the variable GEN
data_ge %>%
add_cols(x = 10,
y = 30,
.before = "GEN")
# Creating a new variable based on the existing ones.
data_ge %>%
add_cols(GY2 = GY^2,
GY2_HM = GY2 + HM,
.after = "GY")
############### Reordering columns ###############
reorder_cols(data_ge2, NKR, .before = "ENV")
reorder_cols(data_ge2, ENV, GEN, .after = "ED")
######## Selecting and removing columns ##########
select_cols(data_ge2, GEN, REP)
remove_cols(data_ge2, GEN, REP)
########## Selecting and removing rows ###########
select_rows(data_ge2, 2:3)
remove_rows(data_ge2, 2:3)
########### Concatenating columns ################
concatenate(data_ge, ENV, GEN, REP)
concatenate(data_ge, ENV, GEN, REP, drop = TRUE)
# Combine with add_cols() and replace_string()
data_ge2 %>%
add_cols(ENV_GEN = concatenate(., ENV, GEN, pull = TRUE),
.after = "GEN") %>%
replace_string(ENV_GEN,
pattern = "H",
replacement = "HYB_",
.after = "ENV_GEN")
################### Adding rows ##################
data_ge %>%
add_rows(ENV = "E_TEST",
GEN = "G_TEST",
REP = 3,
GY = 10.3,
HM = 100.11,
.after = 1)
########## checking if a column exists ###########
column_exists(data_g, "GEN")
####### get the levels and size of levels ########
get_levels(data_g, GEN)
get_level_size(data_g, GEN)
############## all possible pairs ################
all_pairs(data_g, GEN)
########## select numeric variables only #########
select_numeric_cols(data_g)
select_non_numeric_cols(data_g)
# }
Run the code above in your browser using DataCamp Workspace