metan (version 1.2.1)

utils_num_str: Utilities for handling with numbers and strings

Description

• all_lower_case(): Translate all non-numeric strings of a data frame to lower case.

• all_upper_case(): Translate all non-numeric strings of a data frame to upper case.

• extract_number(): Extract the number(s) of a string.

• extract_string(): Extract all strings, ignoring case.

• remove_strings(): Remove all strings of a variable.

• replace_number(): Replace numbers with a replacement.

• replace_string(): Replace all strings with a replacement, ignoring case.

• round_cols(): Round a selected column or a whole data frame to significant figures.

Usage

all_upper_case(.data)
all_lower_case(.data)
extract_number(
  .data,
  var,
  new_var = new_var,
  drop = FALSE,
  pull = FALSE,
  .before = NULL,
  .after = NULL
)
extract_string(
  .data,
  var,
  new_var = new_var,
  drop = FALSE,
  pull = FALSE,
  .before = NULL,
  .after = NULL
)
remove_strings(.data, ...)
replace_number(
  .data,
  var,
  new_var = new_var,
  pattern = NULL,
  replacement = "",
  drop = FALSE,
  pull = FALSE,
  .before = NULL,
  .after = NULL
)
replace_string(
  .data,
  var,
  new_var = new_var,
  pattern = NULL,
  replacement = "",
  drop = FALSE,
  pull = FALSE,
  .before = NULL,
  .after = NULL
)
round_cols(.data, ..., digits = 2)

Arguments

.data

A data frame

var

The variable to extract or replace numbers or strings.

new_var

The name of the new variable containing the numbers or strings extracted or replaced. Defaults to new_var.

drop

Logical argument. If TRUE keeps the new variable new_var and drops the existing ones. Defaults to FALSE.

pull

Logical argument. If TRUE, returns the last column (on the assumption that's the column you've created most recently), as a vector.

.before, .after

For replace_sting(), replace_number(), extract_string(), ,and extract_number() one-based column index or column name where to add the new columns.

...

The argument depends on the function used.

• For round_cols() ... are the variables to round. If no variable is informed, all the numeric variables from data are used.

• For remove_strings() ... are the variables to remove the strings. If no variable is informed, the strings of all non-numeric variables will be removed, keeping the numbers. If variables contains only strings, they will be replaced with NA.

pattern

A string to be matched. Regular Expression Syntax is also allowed.

replacement

A string for replacement.

digits

The number of significant figures.

Examples

# NOT RUN {
library(metan)

################ Rounding numbers ###############
# All numeric columns
round_cols(data_ge2, digits = 1)

# Round specific columns
round_cols(data_ge2, EP, digits = 1)

########### Extract or replace numbers ##########
# Extract numbers
extract_number(data_ge, GEN)
extract_number(data_ge,
               var = GEN,
               drop = TRUE,
               new_var = g_number)

# Replace numbers

replace_number(data_ge, GEN)
replace_number(data_ge,
               var = GEN,
               pattern = "1",
               replacement = "_one",
               pull = TRUE)

########## Extract, replace or remove strings ##########
# Extract strings
extract_string(data_ge, GEN)
extract_string(data_ge,
               var = GEN,
               drop = TRUE,
               new_var = g_name)

# Replace strings
replace_string(data_ge, GEN)
replace_string(data_ge,
               var = GEN,
               new_var = GENOTYPE,
               pattern = "G",
               replacement = "GENOTYPE_")
# Remove strings
remove_strings(data_ge)
remove_strings(data_ge, ENV)
############# upper and lower cases ############
all_lower_case("GENOTYPE")
lc <- all_lower_case(data_ge)
lc
all_lower_case("GENOTYPE")

all_upper_case("Genotype")
all_upper_case(lc)
# }