rbind_loop {neatStats}

Merge by Columns in Loops

Description

Merges rows by columns in a loop using the enum function. On first iteration, indicated by enum, initiates a new data.table with the data to merge as first row. On all following iterations, adds data to merge as subsequent rows (using data.table::rbindlist).

Usage

rbind_loop(merged, ..., hush = FALSE)

Arguments

merged

The name of the data.table for the merged data (without quotes).

...

Any number of data to be merged. Each argument must be one of the following: a data.frame (or data.table) with either single row or two column; a named vector or a named list (with single elements); or a single value with parameter name (e.g. date = 1989 or id = "jdoe"). Data with two columns will be transposed using first column as column names and second column as corresponding values. See Details, Examples.

hush

Logical. If TRUE (default), prints message when the data frame for merging is initiated.

Details

In each call, all data passed to the function (via ...) will be merged into a single row, and that single row will be added to the "merged" data table.

See an extensive example via https://github.com/gasparl/neatstats.

See Also

enum

Examples

my_vector = c('aa', 'bb', 'cxyz', 'last')
for (elem in enum(my_vector)) {
    cat(elem, fill = TRUE)
    rbind_loop(
        merged_data, # data frame name for merging
        item = elem[2],
        number = elem[1],
        whatever = paste0('number (', elem[1], ')')
    )
}
# merged_data now contains all merged rows
print(merged_data)
# item number   whatever
# 1   aa      1 number (1)
# 2   bb      2 number (2)
# 3 cxyz      3 number (3)
# 4 last      4 number (4)


# example with other data types
for (elem in enum(my_vector)) {
    cat(elem, fill = TRUE)
    dframe1 = data.frame(item = elem[2],
                         number = elem[1])
    print(elem[1])
    asnum = as.numeric(elem[1])
    dframe2 = data.frame(
        my_cols = c('index', 'squared', 'multiple'),
        my_vals = c(elem[1], asnum ** 2, asnum * 10)
    )
    my_list = list(ls_item = elem[2], ls_num = elem[1])
    my_vec = c(v_item = elem[2], v_num = elem[1])
    rbind_loop(
        merged_data,
        dframe1, # data frame with single row
        dframe2, # data frame with two columns
        my_list, # named list
        my_vec, # named vector
        single_val = elem[2], # single element
        constant = "whatever" # other single element
    )
}

# again merged_data contains all merged rows
# (previous content, if any, were removed)
print(merged_data)


# example with differring columns
for (elem in enum(my_vector)) {
    cat(elem, fill = TRUE)
    dframe = data.frame(item = elem[2],
                        number = elem[1])
    asnum = as.numeric(elem[1])
    if (asnum %% 2 == 0) {
        dframe$sqr = asnum ** 2
    }
    rbind_loop(merged_data,
               dframe)
}

# merged_data contains all new merged rows
# with NAs where sqr was not added
print(merged_data)

# example with data.table added
library('data.table')
for (elem in enum(my_vector)) {
    cat(elem, fill = TRUE)
    dframe = data.frame(item = elem[2],
                        number = elem[1])
    asnum = as.numeric(elem[1])
    dtable = data.table(item2 = paste('DT', elem[2]),
                        number2 = asnum + 9)
    if (asnum %% 2 == 0) {
        dframe$sqr = asnum ** 2
    }
    rbind_loop(merged_data,
               dframe,
               dtable)
}

print(merged_data)

# an extensive example to show how to collect and aggregate raw data is
# available via the README file at the repository:
# https://github.com/gasparl/neatstats