Compare field experiment data to see if they share designs, variables, etc.

Usage

compare_df(x, y)

Arguments

x: first dataframe
y: second dataframe

Value

a dataframe with difference/similarities btwn x, y

Examples


f <- system.file("uon-trial-1.csv", package = "pbwrangler")
df <- read_workbooks(dir=NULL, file_to_read = f)[[1]]
#> Rows: 108 Columns: 32
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr  (8): unique, geno, flowering_date, flower_colour, flesh_colour, skin_co...
#> dbl (24): plot, entry, row, col, rep, ntp, npe, growth_speed, pgh, plant_uni...
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
f1 <- system.file("uon-trial-1.xlsx", package = "pbwrangler")
df1 <- read_workbooks(dir=NULL, file_to_read = f, sheet_name = "Sheet1")[[1]]
#> Rows: 108 Columns: 32
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr  (8): unique, geno, flowering_date, flower_colour, flesh_colour, skin_co...
#> dbl (24): plot, entry, row, col, rep, ntp, npe, growth_speed, pgh, plant_uni...
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
compare_df(df, df1)
#>    dim_X  dim_Y design_X design_Y cols_not_X cols_not_Y
#> 1 108,32 108,32     6*18     6*18