| mash_table | R Documentation | 
mash_tables() makes it easy to put together multidimensional
tables from data.frames with the same number of rows and columns. You
can mash tables together with either alternating rows or columns.
mash_table(
  ...,
  mash_method = "row",
  id_vars = NULL,
  insert_blank_row = FALSE,
  sep_height = 24,
  meta = NULL,
  rem_ext = NULL
)
mash_table_list(
  tables,
  mash_method = "row",
  id_vars = NULL,
  insert_blank_row = FALSE,
  sep_height = 24,
  meta = NULL,
  rem_ext = NULL
)
| ... | 
 | 
| mash_method | either  | 
| id_vars | Only if mashing columns: one ore more colnames of the tables
to be mashed. If supplied, columns of both input tables are combined with
 | 
| insert_blank_row | Only if mashing rows: logical. Whether to insert blank rows between mash-groups. Warning: this converts all columns to character. Use with care. | 
| sep_height | Only has an effect when exporting to  | 
| meta | A TT_meta object. if supplied, output will also be a Tagged_table. | 
| rem_ext | 
 | 
| tables | 
 | 
a Mashed_table: a list of data.tables with additional
mash_method, insert_blank_row and sep_height attributes, that
influence how the table looks when it is printed or exported.
Attribute setters: mash_method<-
Other Tatoo tables: 
comp_table(),
stack_table(),
tag_table(),
tatoo_table()
df_mean <- data.frame(
  Species = c("setosa", "versicolor", "virginica"),
  length = c(5.01, 5.94, 6.59),
  width = c(3.43, 2.77, 2.97)
)
df_sd <- data.frame(
  Species = c("setosa", "versicolor", "virginica"),
  length = c(0.35, 0.52, 0.64),
  width = c(0.38, 0.31, 0.32)
)
# Mash by row
mash_table(df_mean, df_sd)
#       Species length width
# 1:     setosa   5.01  3.43
# 2:     setosa   0.35  0.38
# 3: versicolor   5.94  2.77
# 4: versicolor   0.52  0.31
# 5:  virginica   6.59  2.97
# 6:  virginica   0.64  0.32
# Mash by column
mash_table(
  df_mean, df_sd,
  mash_method = 'col',
  id_vars = 'Species'
)
#       Species    Species length length width width
# 1:     setosa     setosa   5.01   0.35  3.43  0.38
# 2: versicolor versicolor   5.94   0.52  2.77  0.31
# 3:  virginica  virginica   6.59   0.64  2.97  0.32
# Use the id_vars argument to prevent undesired dpulicated columns,
# and name the input data.frames to get multi-col headings.
mash_table(
  mean = df_mean, sd = df_sd,
  mash_method = 'col',
  id_vars = 'Species'
)
#    ..........     ..length...     ...width...
# 1    Species     mean     sd     mean     sd
# 2     setosa     5.01   0.35     3.43   0.38
# 3 versicolor     5.94   0.52     2.77   0.31
# 4  virginica     6.59   0.64     2.97   0.32
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