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.table
s 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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