Package 'ds4psy'

Description

base_digits provides numeral symbols (digits) for notational place-value systems with arbitrary bases (as a named character vector).

Usage

base_digits

Format

An object of class character of length 62.

Details

Note that the elements (digits) are character symbols (i.e., numeral digits "0"-"9", "A"-"F", etc.), whereas their names correspond to their numeric values (from 0 to length(base_digits) - 1).

Thus, the maximum base value in conversions by base2dec or dec2base is length(base_digits).

See Also

base2dec converts numerals in some base into decimal numbers; dec2base converts decimal numbers into numerals in another base; as.roman converts integers into Roman numerals.

Other numeric functions: base2dec(), dec2base(), is_equal(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Other utility functions: base2dec(), dec2base(), is_equal(), is_vect(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Examples

base_digits          # named character vector, zero-indexed names
length(base_digits)  # 62 (maximum base value)
base_digits[10]      # 10. element ("9" with name "9") 
base_digits["10"]    # named element "10" ("A" with name "10")
base_digits[["10"]]  # element named "10" ("A")

Description

base2dec converts a sequence of numeral symbols (digits) from its notation as positional numerals (with some base or radix) into standard decimal notation (using the base or radix of 10).

Usage

base2dec(x, base = 2)

Arguments

Details

The individual digits provided in x (e.g., from "0" to "9", "A" to "F") must be defined in the specified base (i.e., every digit value must be lower than the base or radix value). See base_digits for the sequence of default digits.

base2dec is the complement of dec2base.

Value

An integer number (in decimal notation).

See Also

dec2base converts decimal numbers into numerals in another base; as.roman converts integers into Roman numerals.

Other numeric functions: base_digits, dec2base(), is_equal(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Other utility functions: base_digits, dec2base(), is_equal(), is_vect(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Examples

# (a) single string input:
base2dec("11")   # default base = 2
base2dec("0101")
base2dec("1010")

base2dec("11", base = 3)
base2dec("11", base = 5)
base2dec("11", base = 10)

base2dec("11", base = 12)
base2dec("11", base = 14)
base2dec("11", base = 16)

# (b) numeric vectors as inputs:
base2dec(c(0, 1, 0))
base2dec(c(0, 1, 0), base = 3)

# (c) character vector as inputs:
base2dec(c("0", "1", "0"))
base2dec(c("0", "1", "0"), base = 3)

# (d) multi-digit vectors:
base2dec(c(1, 1))
base2dec(c(1, 1), base = 3)

# Extreme values:
base2dec(rep("1", 32))          # 32 x "1"
base2dec(c("1", rep("0", 32)))  # 2^32
base2dec(rep("1", 33))          # 33 x "1"
base2dec(c("1", rep("0", 33)))  # 2^33
 
# Non-standard inputs:
base2dec("  ", 2)      # no non-spaces: NA
base2dec(" ?! ", 2)    # no base digits: NA
base2dec(" 100  ", 2)  # remove leading and trailing spaces
base2dec("-  100", 2)  # handle negative inputs (value < 0)
base2dec("- -100", 2)  # handle double negations
base2dec("---100", 2)  # handle multiple negations

# Special cases:
base2dec(NA)
base2dec(0)
base2dec(c(3, 3), base = 3)  # Note message!

# Note: 
base2dec(dec2base(012340, base =  9), base =  9)
dec2base(base2dec(043210, base = 11), base = 11)

Description

Bushisms contains phrases spoken by or attributed to U.S. president George W. Bush (the 43rd president of the United States, in office from January 2001 to January 2009).

Usage

Bushisms

Format

A vector of type character with length(Bushisms) = 22.

Source

Data based on https://en.wikipedia.org/wiki/Bushism.

See Also

Other datasets: Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

capitalize converts the first n initial characters of each element of a text string x (i.e., characters or words) to upper- or lowercase.

Usage

capitalize(x, n = 1, upper = TRUE, as_text = FALSE)

Arguments

Details

If as_text = TRUE, the input x is merged into one string of text and the arguments are applied to each word.

Value

A character vector.

See Also

caseflip for converting the case of all letters; words_to_text and text_to_words for converting character vectors and texts.

Other text objects and functions: Umlaut, caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

x <- c("Hello world!", "this is a TEST sentence.", "the end.")
capitalize(x)
capitalize(tolower(x))

# Options: 
capitalize(x, n = 3)                  # leaves strings intact
capitalize(x, n = 3, as_text = TRUE)  # treats strings as text
capitalize(x, n = 3, upper = FALSE)   # first n in lowercase

Description

caseflip flips the case of all characters in a string of text x.

Usage

caseflip(x)

Arguments

Details

Internally, caseflip uses the letters and LETTERS constants of base R and the chartr function for replacing characters in strings of text.

Value

A character vector.

See Also

capitalize for converting the case of initial letters; chartr for replacing characters in strings of text.

Other text objects and functions: Umlaut, capitalize(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

x <- c("Hello world!", "This is a 1st sentence.", "This is the 2nd sentence.", "The end.")
caseflip(x)

Description

cclass provides different character classes (as a named character vector).

Usage

cclass

Format

An object of class character of length 6.

Details

cclass allows illustrating matching character classes via regular expressions.

See ?base::regex for details on regular expressions and ?"'" for a list of character constants/quotes in R.

See Also

metachar for a vector of metacharacters.

Other text objects and functions: Umlaut, capitalize(), caseflip(), chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

cclass["hex"]  # select by name
writeLines(cclass["pun"])
grep("[[:alpha:]]", cclass, value = TRUE)

Description

change_time changes the time and time zone without changing the time display.

Usage

change_time(time, tz = "")

Arguments

Details

change_time expects inputs to time to be local time(s) (of the "POSIXlt" class) and a valid time zone argument tz (as a string) and returns the same time display (but different actual times) as calendar time(s) (of the "POSIXct" class).

Value

A calendar time of class "POSIXct".

See Also

change_tz function which preserves time but changes time display; Sys.time() function of base R.

Other date and time functions: change_tz(), cur_date(), cur_time(), days_in_month(), diff_dates(), diff_times(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

change_time(as.POSIXlt(Sys.time()), tz = "UTC")

# from "POSIXlt" time:
t1 <- as.POSIXlt("2020-01-01 10:20:30", tz = "Europe/Berlin")
change_time(t1, "Pacific/Auckland")
change_time(t1, "America/Los_Angeles")

# from "POSIXct" time:
tc <- as.POSIXct("2020-07-01 12:00:00", tz = "UTC")
change_time(tc, "Pacific/Auckland")

# from "Date":
dt <- as.Date("2020-12-31", tz = "Pacific/Honolulu")
change_time(dt, tz = "Pacific/Auckland")

# from time "string":
ts <- "2020-12-31 20:30:45"
change_time(ts, tz = "America/Los_Angeles")

# from other "string" times:
tx <- "7:30:45"
change_time(tx, tz = "Asia/Calcutta")
ty <- "1:30"
change_time(ty, tz = "Europe/London")

# convert into local times:
(l1 <- as.POSIXlt("2020-06-01 10:11:12"))
change_tz(change_time(l1, "Pacific/Auckland"), tz = "UTC")
change_tz(change_time(l1, "Europe/Berlin"), tz = "UTC")
change_tz(change_time(l1, "America/New_York"), tz = "UTC")

# with vector of "POSIXlt" times:
(l2 <- as.POSIXlt("2020-12-31 23:59:55", tz = "America/Los_Angeles"))
(tv <- c(l1, l2))              # uses tz of l1
change_time(tv, "America/Los_Angeles")  # change time and tz

Description

change_tz changes the nominal time zone (i.e., the time display) without changing the actual time.

Usage

change_tz(time, tz = "")

Arguments

Details

change_tz expects inputs to time to be calendar time(s) (of the "POSIXct" class) and a valid time zone argument tz (as a string) and returns the same time(s) as local time(s) (of the "POSIXlt" class).

Value

A local time of class "POSIXlt".

See Also

change_time function which preserves time display but changes time; Sys.time() function of base R.

Other date and time functions: change_time(), cur_date(), cur_time(), days_in_month(), diff_dates(), diff_times(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

change_tz(Sys.time(), tz = "Pacific/Auckland")
change_tz(Sys.time(), tz = "Pacific/Honolulu")

# from "POSIXct" time:
tc <- as.POSIXct("2020-07-01 12:00:00", tz = "UTC")
change_tz(tc, "Australia/Melbourne")
change_tz(tc, "Europe/Berlin")
change_tz(tc, "America/Los_Angeles")

# from "POSIXlt" time:
tl <- as.POSIXlt("2020-07-01 12:00:00", tz = "UTC")
change_tz(tl, "Australia/Melbourne")
change_tz(tl, "Europe/Berlin")
change_tz(tl, "America/Los_Angeles")

# from "Date":
dt <- as.Date("2020-12-31")
change_tz(dt, "Pacific/Auckland")
change_tz(dt, "Pacific/Honolulu")  # Note different date!

# with a vector of "POSIXct" times:
t2 <- as.POSIXct("2020-12-31 23:59:55", tz = "America/Los_Angeles")
tv <- c(tc, t2)
tv  # Note: Both times in tz of tc
change_tz(tv, "America/Los_Angeles")

Description

chars_to_text combines multi-element character inputs x into a single string of text (i.e., a character object of length 1), while preserving punctuation and spaces.

Usage

chars_to_text(x, sep = "")

Arguments

Details

chars_to_text is an inverse function of text_to_chars.

Note that using paste(x, collapse = "") would remove spaces. See collapse_chars for a simpler alternative.

Value

A character vector (of length 1).

See Also

collapse_chars for collapsing character vectors; text_to_chars for splitting text into a vector of characters; text_to_words for splitting text into a vector of words; strsplit for splitting strings.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

# (a) One string (with spaces and punctuation):
t1 <- "Hello world! This is _A   TEST_. Does this work?"
(cv <- unlist(strsplit(t1, split = "")))
(t2 <- chars_to_text(cv))
t1 == t2

# (b) Multiple strings (nchar from 0 to >1):
s <- c("Hi", " ", "", "there!", " ", "", "Does  THIS  work?")
chars_to_text(s)

# Note: Using sep argument: 
chars_to_text(c("Hi there!", "How are you today?"), sep = "  ")
chars_to_text(1:3, sep = " | ")

Description

coin generates a sequence of events that represent the results of flipping a fair coin n times.

Usage

coin(n = 1, events = c("H", "T"))

Arguments

Details

By default, the 2 possible events for each flip are "H" (for "heads") and "T" (for "tails").

See Also

Other sampling functions: dice(), dice_2(), sample_char(), sample_date(), sample_time()

Examples

# Basics: 
coin()
table(coin(n = 100))
table(coin(n = 100, events = LETTERS[1:3]))

# Note an oddity:
coin(10, events = 8:9)  # works as expected, but 
coin(10, events = 9:9)  # odd: see sample() for an explanation.

# Limits:
coin(2:3)
coin(NA)
coin(0)
coin(1/2)
coin(3, events = "X")
coin(3, events = NA)
coin(NULL, NULL)

Description

collapse_chars converts multi-element character inputs x into a single string of text (i.e., a character object of length 1), separating its elements by sep.

Usage

collapse_chars(x, sep = " ")

Arguments

Details

As collapse_chars is a wrapper around paste(x, collapse = sep). It preserves spaces within the elements of x.

The separator sep is only used when collapsing multi-element vectors and inserted between elements.

See chars_to_text for combining character vectors into text.

Value

A character vector (of length 1).

See Also

chars_to_text for combining character vectors into text; text_to_chars for splitting text into a vector of characters; text_to_words for splitting text into a vector of words; strsplit for splitting strings.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

collapse_chars(c("Hello", "world", "!"))
collapse_chars(c("_", " _ ", "  _  "), sep = "|")  # preserves spaces
writeLines(collapse_chars(c("Hello", "world", "!"), sep = "\n"))
collapse_chars(1:3, sep = "")

Description

count_chars provides frequency counts of the characters in a string of text x as a named numeric vector.

Usage

count_chars(x, case_sense = TRUE, rm_specials = TRUE, sort_freq = TRUE)

Arguments

Details

If rm_specials = TRUE (as per default), most special (or non-word) characters are removed and not counted. (Note that this currently works without using regular expressions.)

The quantification is case-sensitive and the resulting vector is sorted by name (alphabetically) or by frequency (per default).

Value

A named numeric vector.

See Also

count_words for counting the frequency of words; count_chars_words for counting both characters and words; plot_chars for a corresponding plotting function.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

# Default: 
x <- c("Hello world!", "This is a 1st sentence.", 
       "This is the 2nd sentence.", "THE END.")
count_chars(x)

# Options: 
count_chars(x, case_sense = FALSE)
count_chars(x, rm_specials = FALSE)
count_chars(x, sort_freq = FALSE)

Description

count_chars_words provides frequency counts of the characters and words of a string of text x on a per character basis.

Usage

count_chars_words(x, case_sense = TRUE, sep = "|", rm_sep = TRUE)

Arguments

Details

count_chars_words calls both count_chars and count_words and maps their results to a data frame that contains a row for each character of x.

The quantifications are case-sensitive. Special characters (e.g., parentheses, punctuation, and spaces) are counted as characters, but removed from word counts.

If input x consists of multiple text strings, they are collapsed with an added " " (space) between them.

Value

A data frame with 4 variables (char, char_freq, word, word_freq).

See Also

count_chars for counting the frequency of characters; count_words for counting the frequency of words; plot_chars for a character plotting function.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

s1 <- ("This test is to test this function.")
head(count_chars_words(s1))
head(count_chars_words(s1, case_sense = FALSE))

s3 <- c("A 1st sentence.", "The 2nd sentence.", 
        "A 3rd --- and also THE  FINAL --- SENTENCE.")
tail(count_chars_words(s3))
tail(count_chars_words(s3, case_sense = FALSE))

Description

count_words provides frequency counts of the words in a string of text x as a named numeric vector.

Usage

count_words(x, case_sense = TRUE, sort_freq = TRUE)

Arguments

Details

Special (or non-word) characters are removed and not counted.

The quantification is case-sensitive and the resulting vector is sorted by name (alphabetically) or by frequency (per default).

Value

A named numeric vector.

See Also

count_chars for counting the frequency of characters; count_chars_words for counting both characters and words; plot_chars for a character plotting function.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

# Default: 
s3 <- c("A first sentence.", "The second sentence.", 
        "A third --- and also THE FINAL --- SENTENCE.")
count_words(s3)  # case-sensitive, sorts by frequency 

# Options: 
count_words(s3, case_sense = FALSE)  # case insensitive
count_words(s3, sort_freq = FALSE)   # sorts alphabetically

Description

countries is a dataset containing the names of 197 countries (as a vector of text strings).

Usage

countries

Format

A vector of type character with length(countries) = 197.

Source

Data from https://www.gapminder.org: Original data at https://www.gapminder.org/data/documentation/gd004/.

See Also

Other datasets: Bushisms, Trumpisms, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

cur_date provides a relaxed version of Sys.time() that is sufficient for most purposes.

Usage

cur_date(rev = FALSE, as_string = TRUE, sep = "-")

Arguments

Details

By default, cur_date returns Sys.Date as a character string (using current system settings and sep for formatting). If as_string = FALSE, a "Date" object is returned.

Alternatively, consider using Sys.Date or Sys.time() to obtain the " format according to the ISO 8601 standard.

For more options, see the documentations of the date and Sys.Date functions of base R and the formatting options for Sys.time().

Value

A character string or object of class "Date".

See Also

what_date() function to print dates with more options; date() and today() functions of the lubridate package; date(), Sys.Date(), and Sys.time() functions of base R.

Other date and time functions: change_time(), change_tz(), cur_time(), days_in_month(), diff_dates(), diff_times(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

cur_date()
cur_date(sep = "/")
cur_date(rev = TRUE)
cur_date(rev = TRUE, sep = ".")

# return a "Date" object:
from <- cur_date(as_string = FALSE)
class(from)

Description

cur_time provides a satisficing version of Sys.time() that is sufficient for most purposes.

Usage

cur_time(seconds = FALSE, as_string = TRUE, sep = ":")

Arguments

Details

By default, cur_time returns a Sys.time() as a character string (in " using current system settings. If as_string = FALSE, a "POSIXct" (calendar time) object is returned.

For a time zone argument, see the what_time function, or the now() function of the lubridate package.

Value

A character string or object of class "POSIXct".

See Also

what_time() function to print times with more options; now() function of the lubridate package; Sys.time() function of base R.

Other date and time functions: change_time(), change_tz(), cur_date(), days_in_month(), diff_dates(), diff_times(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

cur_time() 
cur_time(seconds = TRUE)
cur_time(sep = ".")

# return a "POSIXct" object:
t <- cur_time(as_string = FALSE)
format(t, "%T %Z")

Description

data_1 is a fictitious dataset to practice importing data (from a DELIMITED file).

Usage

data_1

Format

A table with 100 cases (rows) and 4 variables (columns).

Source

See DELIMITED data at http://rpository.com/ds4psy/data/data_1.dat.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_2 is a fictitious dataset to practice importing data (from a FWF file).

Usage

data_2

Format

A table with 100 cases (rows) and 4 variables (columns).

Source

See FWF data at http://rpository.com/ds4psy/data/data_2.dat.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_t1 is a fictitious dataset to practice importing and joining data (from a CSV file).

Usage

data_t1

Format

A table with 20 cases (rows) and 4 variables (columns).

Source

See CSV data at http://rpository.com/ds4psy/data/data_t1.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_t1_de is a fictitious dataset to practice importing data (from a CSV file, de/European style).

Usage

data_t1_de

Format

A table with 20 cases (rows) and 4 variables (columns).

Source

See CSV data at http://rpository.com/ds4psy/data/data_t1_de.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_t1_tab is a fictitious dataset to practice importing data (from a TAB file).

Usage

data_t1_tab

Format

A table with 20 cases (rows) and 4 variables (columns).

Source

See TAB-delimited data at http://rpository.com/ds4psy/data/data_t1_tab.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_t2 is a fictitious dataset to practice importing and joining data (from a CSV file).

Usage

data_t2

Format

A table with 20 cases (rows) and 4 variables (columns).

Source

See CSV data at http://rpository.com/ds4psy/data/data_t2.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_t3 is a fictitious dataset to practice importing and joining data (from a CSV file).

Usage

data_t3

Format

A table with 20 cases (rows) and 4 variables (columns).

Source

See CSV data at http://rpository.com/ds4psy/data/data_t3.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

data_t4 is a fictitious dataset to practice importing and joining data (from a CSV file).

Usage

data_t4

Format

A table with 20 cases (rows) and 4 variables (columns).

Source

See CSV data at http://rpository.com/ds4psy/data/data_t4.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

days_in_month computes the number of days in the months of given dates (provided as a date or time dt, or number/string denoting a 4-digit year).

Usage

days_in_month(dt = Sys.Date(), ...)

Arguments

Details

The function requires dt as "Dates", rather than month names or numbers, to check for leap years (in which February has 29 days).

Value

A named (numeric) vector.

See Also

is_leap_year to check for leap years; diff_tz for time zone-based time differences; days_in_month function of the lubridate package.

Other date and time functions: change_time(), change_tz(), cur_date(), cur_time(), diff_dates(), diff_times(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

days_in_month() 

# Robustness: 
days_in_month(Sys.Date())    # Date
days_in_month(Sys.time())    # POSIXct
days_in_month("2020-07-01")  # string
days_in_month(20200901)      # number
days_in_month(c("2020-02-10 01:02:03", "2021-02-11", "2024-02-12"))  # vectors of strings

# For leap years:
ds <- as.Date("2020-02-20") + (365 * 0:4)  
days_in_month(ds)  # (2020/2024 are leap years)

Description

dec2base converts an integer from its standard decimal notation (i.e., using positional numerals with a base or radix of 10) into a sequence of numeric symbols (digits) in some other base. See base_digits for the sequence of default digits.

Usage

dec2base(x, base = 2)

Arguments

Details

To prevent erroneous interpretations of numeric outputs, dec2base returns a sequence of digits (as a character string).

dec2base is the complement of base2dec.

Value

A character string of digits (in base notation).

See Also

base2dec converts numerals in some base into decimal numbers; as.roman converts integers into Roman numerals.

Other numeric functions: base2dec(), base_digits, is_equal(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Other utility functions: base2dec(), base_digits, is_equal(), is_vect(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Examples

# (a) single numeric input:
dec2base(3)  # base = 2

dec2base(8, base = 2)
dec2base(8, base = 3)
dec2base(8, base = 7)

dec2base(100, base = 5)
dec2base(100, base = 10)
dec2base(100, base = 15)

dec2base(14, base = 14)
dec2base(15, base = 15)
dec2base(16, base = 16)

dec2base(15, base = 16)
dec2base(31, base = 16)
dec2base(47, base = 16)

# (b) single string input:
dec2base("7", base = 2)
dec2base("8", base = 3)

# Extreme values:
dec2base(base2dec(rep("1", 32)))          # 32 x "1"
dec2base(base2dec(c("1", rep("0", 32))))  # 2^32
dec2base(base2dec(rep("1", 33)))          # 33 x "1"
dec2base(base2dec(c("1", rep("0", 33))))  # 2^33

# Non-standard inputs:
dec2base("  ")          # only spaces: NA
dec2base("?")           # no decimal digits: NA
dec2base(" 10 ", 2)     # remove leading and trailing spaces
dec2base("-10", 2)      # handle negative inputs (in character strings)
dec2base(" -- 10", 2)   # handle multiple negations
dec2base("xy -10 ", 2)  # ignore non-decimal digit prefixes

# Note: 
base2dec(dec2base(012340, base =  9), base =  9)
dec2base(base2dec(043210, base = 11), base = 11)

Description

dice generates a sequence of events that represent the results of throwing a fair dice (with a given number of events or number of sides) n times.

Usage

dice(n = 1, events = 1:6)

Arguments

Details

By default, the 6 possible events for each throw of the dice are the numbers from 1 to 6.

See Also

Other sampling functions: coin(), dice_2(), sample_char(), sample_date(), sample_time()

Examples

# Basics:
dice()
table(dice(10^4))

# 5-sided dice:
dice(events = 1:5)
table(dice(100, events = 5))

# Strange dice:
dice(5, events = 8:9)
table(dice(100, LETTERS[1:3]))

# Note:
dice(10, 1)
table(dice(100, 2))

# Note an oddity:
dice(10, events = 8:9)  # works as expected, but 
dice(10, events = 9:9)  # odd: see sample() for an explanation.

# Limits:
dice(NA)
dice(0)
dice(1/2)
dice(2:3)
dice(5, events = NA)
dice(5, events = 1/2)
dice(NULL, NULL)

Description

dice_2 is a variant of dice that generates a sequence of events that represent the results of throwing a dice (with a given number of sides) n times.

Usage

dice_2(n = 1, sides = 6)

Arguments

Details

Something is wrong with this dice. Can you examine it and measure its problems in a quantitative fashion?

See Also

Other sampling functions: coin(), dice(), sample_char(), sample_date(), sample_time()

Examples

# Basics:
dice_2()
table(dice_2(100))

# 10-sided dice:
dice_2(sides = 10)
table(dice_2(100, sides = 10))

# Note:
dice_2(10, 1)
table(dice_2(5000, sides = 5))

# Note an oddity:
dice_2(n = 10, sides = 8:9)  # works, but 
dice_2(n = 10, sides = 9:9)  # odd: see sample() for an explanation.

Description

diff_dates computes the difference between two dates (i.e., from some from_date to some to_date) in human measurement units (periods).

Usage

diff_dates(
  from_date,
  to_date = Sys.Date(),
  unit = "years",
  as_character = TRUE
)

Arguments

Details

diff_dates answers questions like "How much time has elapsed between two dates?" or "How old are you?" in human time periods of (full) years, months, and days.

Key characteristics:

• If to_date or from_date are not "Date" objects, diff_dates aims to coerce them into "Date" objects.

• If to_date is missing (i.e., NA), to_date is set to today's date (i.e., Sys.Date()).

• If to_date is specified, any intermittent missing values (i.e., NA) are set to today's date (i.e., Sys.Date()). Thus, dead people (with both birth dates and death dates specified) do not age any further, but people still alive (with is.na(to_date), are measured to today's date (i.e., Sys.Date()).

• If to_date precedes from_date (i.e., from_date > to_date) computations are performed on swapped days and the result is marked as negative (by a character "-") in the output.

• If the lengths of from_date and to_date differ, the shorter vector is recycled to the length of the longer one.

By default, diff_dates provides output as (signed) character strings. For numeric outputs, use as_character = FALSE.

Value

A character vector or data frame (with dates, sign, and numeric columns for units).

See Also

Time spans (interval as.period) in the lubridate package.

Other date and time functions: change_time(), change_tz(), cur_date(), cur_time(), days_in_month(), diff_times(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

y_100 <- Sys.Date() - (100 * 365.25) + -1:1
diff_dates(y_100)

# with "to_date" argument: 
y_050 <- Sys.Date() - (50 * 365.25) + -1:1 
diff_dates(y_100, y_050)
diff_dates(y_100, y_050, unit = "d") # days (with decimals)

# Time unit and output format:
ds_from <- as.Date("2010-01-01") + 0:2
ds_to   <- as.Date("2020-03-01")  # (2020 is leap year)
diff_dates(ds_from, ds_to, unit = "y", as_character = FALSE)  # years
diff_dates(ds_from, ds_to, unit = "m", as_character = FALSE)  # months
diff_dates(ds_from, ds_to, unit = "d", as_character = FALSE)  # days

# Robustness:
days_cur_year <- 365 + is_leap_year(Sys.Date())
diff_dates(Sys.time() - (1 * (60 * 60 * 24) * days_cur_year))  # for POSIXt times
diff_dates("10-08-11", "20-08-10")   # for strings
diff_dates(20200228, 20200301)       # for numbers (2020 is leap year)

# Recycling "to_date" to length of "from_date":
y_050_2 <- Sys.Date() - (50 * 365.25)
diff_dates(y_100, y_050_2)

# Note maxima and minima: 
diff_dates("0000-01-01", "9999-12-31")  # max. d + m + y
diff_dates("1000-06-01", "1000-06-01")  # min. d + m + y

# If from_date == to_date:
diff_dates("2000-01-01", "2000-01-01")

# If from_date > to_date:
diff_dates("2000-01-02", "2000-01-01")  # Note negation "-"
diff_dates("2000-02-01", "2000-01-01", as_character = TRUE)
diff_dates("2001-02-02", "2000-02-02", as_character = FALSE)

# Test random date samples:
f_d <- sample_date(size = 10)
t_d <- sample_date(size = 10)
diff_dates(f_d, t_d, as_character = TRUE)

# Using 'fame' data:
dob <- as.Date(fame$DOB, format = "%B %d, %Y")
dod <- as.Date(fame$DOD, format = "%B %d, %Y")
head(diff_dates(dob, dod))  # Note: Deceased people do not age further.
head(diff_dates(dob, dod, as_character = FALSE))  # numeric outputs

Description

diff_times computes the difference between two times (i.e., from some from_time to some to_time) in human measurement units (periods).

Usage

diff_times(from_time, to_time = Sys.time(), unit = "days", as_character = TRUE)

Arguments

Details

diff_times answers questions like "How much time has elapsed between two dates?" or "How old are you?" in human time periods of (full) years, months, and days.

Key characteristics:

• If to_time or from_time are not "POSIXct" objects, diff_times aims to coerce them into "POSIXct" objects.

• If to_time is missing (i.e., NA), to_time is set to the current time (i.e., Sys.time()).

• If to_time is specified, any intermittent missing values (i.e., NA) are set to the current time (i.e., Sys.time()).

• If to_time precedes from_time (i.e., from_time > to_time) computations are performed on swapped times and the result is marked as negative (by a character "-") in the output.

• If the lengths of from_time and to_time differ, the shorter vector is recycled to the length of the longer one.

By default, diff_times provides output as (signed) character strings. For numeric outputs, use as_character = FALSE.

Value

A character vector or data frame (with times, sign, and numeric columns for units).

See Also

diff_dates for date differences; time spans (an interval as.period) in the lubridate package.

Other date and time functions: change_time(), change_tz(), cur_date(), cur_time(), days_in_month(), diff_dates(), diff_tz(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

t1 <- as.POSIXct("1969-07-13 13:53 CET")  # (before UNIX epoch)
diff_times(t1, unit = "years", as_character = TRUE)
diff_times(t1, unit = "secs", as_character = TRUE)

Description

diff_tz computes the time difference between two times t1 and t2 that is exclusively due to both times being in different time zones.

Usage

diff_tz(t1, t2, in_min = FALSE)

Arguments

Details

diff_tz ignores all differences in nominal times, but allows adjusting time-based computations for time shifts that are due to time zone differences (e.g., different locations, or changes to/from daylight saving time, DST), rather than differences in actual times.

Internally, diff_tz determines and contrasts the POSIX conversion specifications " (in numeric form).

If the lengths of t1 and t2 differ, the shorter vector is recycled to the length of the longer one.

Value

A character (in "HH:MM" format) or numeric vector (number of minutes).

See Also

days_in_month for the number of days in given months; is_leap_year to check for leap years.

Other date and time functions: change_time(), change_tz(), cur_date(), cur_time(), days_in_month(), diff_dates(), diff_times(), is_leap_year(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

# Time zones differences:
tm <- "2020-01-01 01:00:00"  # nominal time
t1 <- as.POSIXct(tm, tz = "Pacific/Auckland")
t2 <- as.POSIXct(tm, tz = "Europe/Berlin")
t3 <- as.POSIXct(tm, tz = "Pacific/Honolulu")

# as character (in "HH:MM"):
diff_tz(t1, t2)
diff_tz(t2, t3)
diff_tz(t1, t3)

# as numeric (in minutes):
diff_tz(t1, t3, in_min = TRUE)

# Compare local times (POSIXlt): 
t4 <- as.POSIXlt(Sys.time(), tz = "Pacific/Auckland")
t5 <- as.POSIXlt(Sys.time(), tz = "Europe/Berlin")
diff_tz(t4, t5)
diff_tz(t4, t5, in_min = TRUE)

# DSL shift: Spring ahead (on 2020-03-29: 02:00:00 > 03:00:00):
s6 <- "2020-03-29 01:00:00 CET"   # before DSL switch
s7 <- "2020-03-29 03:00:00 CEST"  # after DSL switch
t6 <- as.POSIXct(s6, tz = "Europe/Berlin")  # CET
t7 <- as.POSIXct(s7, tz = "Europe/Berlin")  # CEST

diff_tz(t6, t7)  # 1 hour forward
diff_tz(t6, t7, in_min = TRUE)

Description

Opens user guide of the ds4psy package.

Usage

ds4psy.guide()

Description

dt_10 contains precise DOB information of 10 non-existent, but definitely Danish people.

Usage

dt_10

Format

A table with 10 cases (rows) and 7 variables (columns).

Source

See CSV data file at http://rpository.com/ds4psy/data/dt_10.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

exp_num_dt is a fictitious dataset describing 1000 non-existing, but surprisingly friendly people.

Usage

exp_num_dt

Format

A table with 1000 cases (rows) and 15 variables (columns).

Details

Codebook

The table contains 15 columns/variables:

• 1. name: Participant initials.

• 2. gender: Self-identified gender.

• 3. bday: Day (within month) of DOB.

• 4. bmonth: Month (within year) of DOB.

• 5. byear: Year of DOB.

• 6. height: Height (in cm).

• 7. blood_type: Blood type.

• 8. bnt_1 to 11. bnt_4: Correct response to BNT question? (1: correct, 0: incorrect).

• 12. g_iq and 13. s_iq: Scores from two IQ tests (general vs. social).

• 14. t_1 and 15. t_2: Start and end time.

exp_num_dt was generated for analyzing test scores (e.g., IQ, numeracy), for converting data from wide into long format, and for dealing with date- and time-related variables.

Source

See CSV data files at http://rpository.com/ds4psy/data/numeracy.csv and http://rpository.com/ds4psy/data/dt.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_wide, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

exp_wide is a fictitious dataset to practice tidying data (here: converting from wide to long format).

Usage

exp_wide

Format

A table with 10 cases (rows) and 7 variables (columns).

Source

See CSV data at http://rpository.com/ds4psy/data/exp_wide.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, falsePosPsy_all, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

falsePosPsy_all is a dataset containing the data from 2 studies designed to highlight problematic research practices within psychology.

Usage

falsePosPsy_all

Format

A table with 78 cases (rows) and 19 variables (columns):

Details

Simmons, Nelson and Simonsohn (2011) published a controversial article with a necessarily false finding. By conducting simulations and 2 simple behavioral experiments, the authors show that flexibility in data collection, analysis, and reporting dramatically increases the rate of false-positive findings.

study

Study ID.

id

Participant ID.

aged

Days since participant was born (based on their self-reported birthday).

aged365

Age in years.

female

Is participant a woman? 1: yes, 2: no.

dad

Father's age (in years).

mom

Mother's age (in years).

potato

Did the participant hear the song 'Hot Potato' by The Wiggles? 1: yes, 2: no.

when64

Did the participant hear the song 'When I am 64' by The Beatles? 1: yes, 2: no.

kalimba

Did the participant hear the song 'Kalimba' by Mr. Scrub? 1: yes, 2: no.

cond

In which condition was the participant? control: Subject heard the song 'Kalimba' by Mr. Scrub; potato: Subject heard the song 'Hot Potato' by The Wiggles; 64: Subject heard the song 'When I am 64' by The Beatles.

root

Could participant report the square root of 100? 1: yes, 2: no.

bird

Imagine a restaurant you really like offered a 30 percent discount for dining between 4pm and 6pm. How likely would you be to take advantage of that offer? Scale from 1: very unlikely, 7: very likely.

political

In the political spectrum, where would you place yourself? Scale: 1: very liberal, 2: liberal, 3: centrist, 4: conservative, 5: very conservative.

quarterback

If you had to guess who was chosen the quarterback of the year in Canada last year, which of the following four options would you choose? 1: Dalton Bell, 2: Daryll Clark, 3: Jarious Jackson, 4: Frank Wilczynski.

olddays

How often have you referred to some past part of your life as “the good old days”? Scale: 11: never, 12: almost never, 13: sometimes, 14: often, 15: very often.

feelold

How old do you feel? Scale: 1: very young, 2: young, 3: neither young nor old, 4: old, 5: very old.

computer

Computers are complicated machines. Scale from 1: strongly disagree, to 5: strongly agree.

diner

Imagine you were going to a diner for dinner tonight, how much do you think you would like the food? Scale from 1: dislike extremely, to 9: like extremely.

See https://bookdown.org/hneth/ds4psy/B-2-datasets-false.html for codebook and more information.

Source

Articles

• Simmons, J.P., Nelson, L.D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366. doi: 10.1177/0956797611417632

• Simmons, J.P., Nelson, L.D., & Simonsohn, U. (2014). Data from paper "False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant". Journal of Open Psychology Data, 2(1), e1. doi: 10.5334/jopd.aa

See files at https://openpsychologydata.metajnl.com/articles/10.5334/jopd.aa/ and the archive at https://zenodo.org/record/7664 for original dataset.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, fame, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

fame is a dataset to practice working with dates.

fame contains the names, areas, dates of birth (DOB), and — if applicable — the dates of death (DOD) of famous people.

Usage

fame

Format

A table with 67 cases (rows) and 4 variables (columns).

Source

Student solutions to exercises, dates mostly from https://www.wikipedia.org/.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, flowery, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

flowery contains versions and variations of Gertrude Stein's popular phrase "A rose is a rose is a rose".

Usage

flowery

Format

A vector of type character with length(flowery) = 60.

Details

The phrase stems from Gertrude Stein's poem "Sacred Emily" (written in 1913 and published in 1922, in "Geography and Plays"). The verbatim line in the poem actually reads "Rose is a rose is a rose is a rose".

See https://en.wikipedia.org/wiki/Rose_is_a_rose_is_a_rose_is_a_rose for additional variations and sources.

Source

Data based on https://en.wikipedia.org/wiki/Rose_is_a_rose_is_a_rose_is_a_rose.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, fruits, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

fruits is a dataset containing the names of 122 fruits (as a vector of text strings).

Usage

fruits

Format

A vector of type character with length(fruits) = 122.

Details

Botanically, "fruits" are the seed-bearing structures of flowering plants (angiosperms) formed from the ovary after flowering.

In common usage, "fruits" refer to the fleshy seed-associated structures of a plant that taste sweet or sour, and are edible in their raw state.

Source

Data based on https://simple.wikipedia.org/wiki/List_of_fruits.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, outliers, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

get_set obtains a set of x/y coordinates and returns it (as a data frame).

Usage

get_set(n = 1)

Arguments

Details

Each set stems from Anscombe's Quartet (see datasets::anscombe, hence 1 <= n <= 4) and is returned as an 11 x 2 data frame.

Source

See ?datasets:anscombe for details and references.

See Also

Other data functions: make_grid()

Examples

get_set(1)
plot(get_set(2), col = "red")

Description

invert_rules allows decoding messages that were encoded by a set of rules x.

Usage

invert_rules(x)

Arguments

Details

x is assumed to be a named vector.

invert_rules replaces the elements of x by the names of x, and vice versa.

A message is issued if the elements of x are repeated (i.e., decoding is non-unique).

Value

A character vector.

See Also

transl33t for encoding text (e.g., into leet slang); l33t_rul35 for default rules used.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

invert_rules(l33t_rul35)  # Note repeated elements

# Encoding and decoding a message:
(txt_0 <- "Hello world! How are you doing today?")             # message
(txt_1 <- transl33t(txt_0, rules = l33t_rul35))                # encoding 
(txt_2 <- transl33t(txt_1, rules = invert_rules(l33t_rul35)))  # decoding

Description

is_equal tests if two vectors x and y are pairwise equal.

Usage

is_equal(x, y, ...)

Arguments

Details

If both x and y are numeric, is_equal calls num_equal(x, y, ...) (allowing for a tolerance threshold tol). Otherwise, x and y are compared by x == y.

is_equal provides a wrapper around num_equal (for numeric objects x and y) and == (otherwise).

See Also

num_equal function for comparing numeric vectors; all.equal function of the R base package; near of the dplyr package.

Other numeric functions: base2dec(), base_digits, dec2base(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Other utility functions: base2dec(), base_digits, dec2base(), is_vect(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Examples

# numeric data: 
is_equal(2, sqrt(2)^2)
is_equal(2, sqrt(2)^2, tol = 0)
is_equal(c(2, 3), c(sqrt(2)^2, sqrt(3)^2, 4/2, 9/3))

# other data types:
is_equal((1:3 > 1), (1:3 > 2))                         # logical
is_equal(c("A", "B", "c"), toupper(c("a", "b", "c")))  # character
is_equal(as.Date("2023-10-30"), Sys.Date())            # dates

# factors:
is_equal((1:3 > 1), as.factor((1:3 > 2)))  
is_equal(c(1, 2, 3), as.factor(c(1, 2, 3)))
is_equal(c("A", "B", "C"), as.factor(c("A", "B", "C")))

Description

is_leap_year checks whether a given year (provided as a date or time dt, or number/string denoting a 4-digit year) lies in a so-called leap year (i.e., a year containing a date of Feb-29).

Usage

is_leap_year(dt)

Arguments

Details

When dt is not recognized as "Date" or "POSIXt" object(s), is_leap_year aims to parse a string dt as describing year(s) in a "dddd" (4-digit year) format, as a valid "Date" string (to retrieve the 4-digit year "%Y"), or a numeric dt as 4-digit integer(s).

is_leap_year then solves the task by verifying the numeric definition of a "leap year" (see https://en.wikipedia.org/wiki/Leap_year).

An alternative solution that tried using as.Date() for defining a "Date" of Feb-29 in the corresponding year(s) was removed, as it evaluated NA values as FALSE.

Value

Boolean vector.

Source

See https://en.wikipedia.org/wiki/Leap_year for definition.

See Also

days_in_month for the number of days in given months; diff_tz for time zone-based time differences; leap_year function of the lubridate package.

Other date and time functions: change_time(), change_tz(), cur_date(), cur_time(), days_in_month(), diff_dates(), diff_times(), diff_tz(), what_date(), what_month(), what_time(), what_wday(), what_week(), what_year(), zodiac()

Examples

is_leap_year(2020)
(days_this_year <- 365 + is_leap_year(Sys.Date()))

# from dates:
is_leap_year(Sys.Date())
is_leap_year(as.Date("2022-02-28"))

# from times:
is_leap_year(Sys.time())
is_leap_year(as.POSIXct("2022-10-11 10:11:12"))
is_leap_year(as.POSIXlt("2022-10-11 10:11:12"))

# from non-integers:
is_leap_year(2019.5)

# For vectors:
is_leap_year(2020:2028)

# with dt as strings:
is_leap_year(c("2020", "2021"))
is_leap_year(c("2020-02-29 01:02:03", "2021-02-28 01:02"))

# Note: Invalid date string yields error: 
# is_leap_year("2021-02-29")

Description

is_vect tests if x is a vector.

Usage

is_vect(x)

Arguments

Details

is_vect does what the base R function is.vector is not designed to do:

• is_vect() returns TRUE if x is an atomic vector or a list (irrespective of its attributes).

• is.vector() returns TRUE if x is a vector of the specified mode having no attributes other than names, otherwise FALSE.

Internally, the function is a wrapper for is.atomic(x) | is.list(x).

Note that data frames are also vectors.

See the is_vector function of the purrr package and the base R functions is.atomic, is.list, and is.vector, for details.

See Also

is_vect function of the purrr package; is.atomic function of the R base package; is.list function of the R base package; is.vector function of the R base package.

Other utility functions: base2dec(), base_digits, dec2base(), is_equal(), is_wholenumber(), num_as_char(), num_as_ordinal(), num_equal()

Examples

# Define 3 types of vectors:
v1 <- 1:3  # (a) atomic vector
names(v1) <- LETTERS[v1]  # with names

v2 <- v1   # (b) copy vector
attr(v2, "my_attr") <- "foo"  # add an attribute
ls <- list(1, 2, "C")  # (c) list

# Compare:
is.vector(v1)
is.list(v1)
is_vect(v1)

is.vector(v2)  # FALSE
is.list(v2)
is_vect(v2)  # TRUE

is.vector(ls)
is.list(ls)
is_vect(ls)

# Data frames are also vectors: 
df <- as.data.frame(1:3)
is_vect(df)  # is TRUE

Description

is_wholenumber tests if x contains only integer numbers.

Usage

is_wholenumber(x, tol = .Machine$double.eps^0.5)

Arguments

Details

is_wholenumber does what the base R function is.integer is not designed to do:

• is_wholenumber() returns TRUE or FALSE depending on whether its numeric argument x is an integer value (i.e., a "whole" number).

• is.integer() returns TRUE or FALSE depending on whether its argument is of integer type, and FALSE if its argument is a factor.

See the documentation of is.integer for definition and details.

See Also

is.integer function of the R base package.

Other numeric functions: base2dec(), base_digits, dec2base(), is_equal(), num_as_char(), num_as_ordinal(), num_equal()

Other utility functions: base2dec(), base_digits, dec2base(), is_equal(), is_vect(), num_as_char(), num_as_ordinal(), num_equal()

Examples

is_wholenumber(1)    # is TRUE
is_wholenumber(1/2)  # is FALSE
x <- seq(1, 2, by = 0.5)
is_wholenumber(x)

# Compare:
is.integer(1+2) 
is_wholenumber(1+2)

Description

l33t_rul35 specifies rules for translating characters into other characters (typically symbols) to mimic leet/l33t slang (as a named character vector).

Usage

l33t_rul35

Format

An object of class character of length 13.

Details

Old (i.e., to be replaced) characters are paste(names(l33t_rul35), collapse = "").

New (i.e., replaced) characters are paste(l33t_rul35, collapse = "").

See https://en.wikipedia.org/wiki/Leet for details.

See Also

transl33t for a corresponding function.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), map_text_chars(), map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Description

make_grid generates a grid of x/y coordinates and returns it (as a data frame).

Usage

make_grid(x_min = 0, x_max = 2, y_min = 0, y_max = 1)

Arguments

See Also

Other data functions: get_set()

Examples

make_grid()
make_grid(x_min = -3, x_max = 3, y_min = -2, y_max = 2)

Description

map_text_chars parses text (from a text string x) into a table that contains a row for each character and x/y-coordinates corresponding to the character positions in x.

Usage

map_text_chars(x, flip_y = FALSE)

Arguments

Details

map_text_chars creates a data frame with 3 variables: Each character's x- and y-coordinates (from top to bottom) and a variable char for the character at these coordinates.

Note that map_text_chars was originally a part of read_ascii, but has been separated to enable independent access to separate functionalities.

Note that map_text_chars is replaced by the simpler map_text_coord function.

Value

A data frame with 3 variables: Each character's x- and y-coordinates (from top to bottom) and a variable char for the character at this coordinate.

See Also

read_ascii for parsing text from file or user input; plot_chars for a character plotting function.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_coord(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Description

map_text_coord parses text (from a text string x) into a table that contains a row for each character and x/y-coordinates corresponding to the character positions in x.

Usage

map_text_coord(x, flip_y = FALSE, sep = "")

Arguments

Details

map_text_coord creates a data frame with 3 variables: Each character's x- and y-coordinates (from top to bottom) and a variable char for the character at these coordinates.

Note that map_text_coord was originally a part of read_ascii, but has been separated to enable independent access to separate functionalities.

Value

A data frame with 3 variables: Each character's x- and y-coordinates (from top to bottom) and a variable char for the character at this coordinate.

See Also

map_text_regex for mapping text to a character table and matching patterns; plot_charmap for plotting character maps; plot_chars for creating and plotting character maps; read_ascii for parsing text from file or user input.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_regex(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

map_text_coord("Hello world!")             # 1 line of text
map_text_coord(c("Hello", "world!"))       # 2 lines of text
map_text_coord(c("Hello", " ", "world!"))  # 3 lines of text
 

## Read text from file:

## Create a temporary file "test.txt":
# cat("Hello world!", "This is a test.",
#     "Can you see this text?", "Good! Please carry on...",
#      file = "test.txt", sep = "\n")
 
# txt <- read_ascii("test.txt")
# map_text_coord(txt)

# unlink("test.txt")  # clean up (by deleting file).

Description

map_text_regex parses text (from a file or user input) into a data frame that contains a row for each character of x.

Usage

map_text_regex(
  x = NA,
  file = "",
  lbl_hi = NA,
  lbl_lo = NA,
  bg_hi = NA,
  bg_lo = "[[:space:]]",
  lbl_rotate = NA,
  case_sense = TRUE,
  lbl_tiles = TRUE,
  col_lbl = "black",
  col_lbl_hi = pal_ds4psy[[1]],
  col_lbl_lo = pal_ds4psy[[9]],
  col_bg = pal_ds4psy[[7]],
  col_bg_hi = pal_ds4psy[[4]],
  col_bg_lo = "white",
  col_sample = FALSE,
  rseed = NA,
  angle_fg = c(-90, 90),
  angle_bg = 0
)

Arguments

Details

map_text_regex allows for regular expression (regex) to match text patterns and create corresponding variables (e.g., for color or orientation).

Five regular expressions and corresponding color and angle arguments allow identifying, marking (highlighting or de-emphasizing), and rotating those sets of characters (i.e, their text labels or fill colors). that match the provided patterns.

The plot generated by plot_chars is character-based: Individual characters are plotted at equidistant x-y-positions and the aesthetic settings provided for text labels and tile fill colors.

map_text_regex returns a plot description (as a data frame). Using this output as an input to plot_charmap plots text in a character-based fashion (i.e., individual characters are plotted at equidistant x-y-positions). Together, both functions replace the over-specialized plot_chars and plot_text functions.

Value

A data frame describing a plot.

See Also

map_text_coord for mapping text to a table of character coordinates; plot_charmap for plotting character maps; plot_chars for creating and plotting character maps; plot_text for plotting characters and color tiles by frequency; read_ascii for reading text inputs into a character string.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), metachar, read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

## (1) From text string(s): 
ts <- c("Hello world!", "This is a test to test this splendid function",
        "Does this work?", "That's good.", "Please carry on.")
sum(nchar(ts))

# (a) simple use:
map_text_regex(ts) 

# (b) matching patterns (regex):
map_text_regex(ts, lbl_hi = "\\b\\w{4}\\b", bg_hi = "[good|test]",
               lbl_rotate = "[^aeiou]", angle_fg = c(-45, +45))

## (2) From user input:
# map_text_regex()  # (enter text in Console)
 
## (3) From text file:
# cat("Hello world!", "This is a test file.",
#     "Can you see this text?",
#     "Good! Please carry on...",
#     file = "test.txt", sep = "\n")
# 
# map_text_regex(file = "test.txt")  # default
# map_text_regex(file = "test.txt", lbl_hi = "[[:upper:]]", lbl_lo = "[[:punct:]]",
#                col_lbl_hi = "red", col_lbl_lo = "blue")
# 
# map_text_regex(file = "test.txt", lbl_hi = "[aeiou]", col_lbl_hi = "red",
#                col_bg = "white", bg_hi = "see")  # mark vowels and "see" (in bg)
# map_text_regex(file = "test.txt", bg_hi = "[aeiou]", col_bg_hi = "gold")  # mark (bg of) vowels
# 
# # Label options:
# map_text_regex(file = "test.txt", bg_hi = "see", lbl_tiles = FALSE)
# map_text_regex(file = "test.txt", angle_bg = c(-20, 20))
# 
# unlink("test.txt")  # clean up (by deleting file).

Description

metachar provides the metacharacters of extended regular expressions (as a character vector).

Usage

metachar

Format

An object of class character of length 12.

Details

metachar allows illustrating the notion of meta-characters in regular expressions (and provides corresponding exemplars).

See ?base::regex for details on regular expressions and ?"'" for a list of character constants/quotes in R.

See Also

cclass for a vector of character classes.

Other text objects and functions: Umlaut, capitalize(), caseflip(), cclass, chars_to_text(), collapse_chars(), count_chars(), count_chars_words(), count_words(), invert_rules(), l33t_rul35, map_text_chars(), map_text_coord(), map_text_regex(), read_ascii(), text_to_chars(), text_to_sentences(), text_to_words(), transl33t(), words_to_text()

Examples

metachar
length(metachar)  # 12
nchar(paste0(metachar, collapse = ""))  # 12

Description

num_as_char converts a number into a character sequence (of a specific length).

Usage

num_as_char(x, n_pre_dec = 2, n_dec = 2, sym = "0", sep = ".")

Arguments

Details

The arguments n_pre_dec and n_dec set a number of desired digits before and after the decimal separator sep. num_as_char tries to meet these digit numbers by adding zeros to the front and end of x. However, when n_pre_dec is lower than the number of relevant (pre-decimal) digits, all relevant digits are shown.

n_pre_dec also works for negative numbers, but the minus symbol is not counted as a (pre-decimal) digit.

Caveat: Note that this function illustrates how numbers, characters, for loops, and paste() can be combined when writing functions. It is not written efficiently or well.

See Also

Other numeric functions: base2dec(), base_digits, dec2base(), is_equal(), is_wholenumber(), num_as_ordinal(), num_equal()

Other utility functions: base2dec(), base_digits, dec2base(), is_equal(), is_vect(), is_wholenumber(), num_as_ordinal(), num_equal()

Examples

num_as_char(1)
num_as_char(10/3)
num_as_char(1000/6) 

# rounding down:
num_as_char((1.3333), n_pre_dec = 0, n_dec = 0)
num_as_char((1.3333), n_pre_dec = 2, n_dec = 0)
num_as_char((1.3333), n_pre_dec = 2, n_dec = 1)

# rounding up: 
num_as_char(1.6666, n_pre_dec = 1, n_dec = 0)
num_as_char(1.6666, n_pre_dec = 1, n_dec = 1)
num_as_char(1.6666, n_pre_dec = 2, n_dec = 2)
num_as_char(1.6666, n_pre_dec = 2, n_dec = 3)

# Note: If n_pre_dec is too small, actual number is kept:
num_as_char(11.33, n_pre_dec = 0, n_dec = 1)
num_as_char(11.66, n_pre_dec = 1, n_dec = 1)

# Note:
num_as_char(1, sep = ",")
num_as_char(2, sym = " ")
num_as_char(3, sym = " ", n_dec = 0)

# for vectors:
num_as_char(1:10/1, n_pre_dec = 1, n_dec = 1)
num_as_char(1:10/3, n_pre_dec = 2, n_dec = 2)

# for negative numbers (adding relevant pre-decimals):
mix <- c(10.33, -10.33, 10.66, -10.66)
num_as_char(mix, n_pre_dec = 1, n_dec = 1)
num_as_char(mix, n_pre_dec = 1, n_dec = 0)

# Beware of bad inputs:
num_as_char(4, sym = "8")
num_as_char(5, sym = "99")

Description

num_as_ordinal converts a given (cardinal) number into an ordinal character sequence.

Usage

num_as_ordinal(x, sep = "")

Arguments

Details

The function currently only works for the English language and does not accepts inputs that are characters, dates, or times.

Note that the toOrdinal() function of the toOrdinal package works for multiple languages and provides a toOrdinalDate() function.

Caveat: Note that this function illustrates how numbers, characters, for loops, and paste() can be combined when writing functions. It is instructive, but not written efficiently or well (see the function definition for an alternative solution using vector indexing).

See Also

toOrdinal() function of the toOrdinal package.

Other numeric functions: base2dec(), base_digits, dec2base(), is_equal(), is_wholenumber(), num_as_char(), num_equal()

Other utility functions: base2dec(), base_digits, dec2base(), is_equal(), is_vect(), is_wholenumber(), num_as_char(), num_equal()

Examples

num_as_ordinal(1:4)
num_as_ordinal(10:14)    # all with "th"
num_as_ordinal(110:114)  # all with "th"
num_as_ordinal(120:124)  # 4 different suffixes
num_as_ordinal(1:15, sep = "-")  # using sep

# Note special cases:
num_as_ordinal(NA)
num_as_ordinal("1")
num_as_ordinal(Sys.Date())
num_as_ordinal(Sys.time())
num_as_ordinal(seq(1.99, 2.14, by = .01))

Description

num_equal tests if two numeric vectors x and y are pairwise equal (within a tolerance value 'tol').

Usage

num_equal(x, y, tol = .Machine$double.eps^0.5)

Arguments

Details

num_equal verifies that x and y are numeric and then evaluates abs(x - y) < tol. Thus, num_equal provides a safer way to verify the (near) equality of numeric vectors than == (due to possible floating point effects).

See Also

is_equal function for generic vectors; all.equal function of the R base package; near function of the dplyr package.

Other numeric functions: base2dec(), base_digits, dec2base(), is_equal(), is_wholenumber(), num_as_char(), num_as_ordinal()

Other utility functions: base2dec(), base_digits, dec2base(), is_equal(), is_vect(), is_wholenumber(), num_as_char(), num_as_ordinal()

Examples

num_equal(2, sqrt(2)^2)

# Recycling: 
num_equal(c(2, 3), c(sqrt(2)^2, sqrt(3)^2, 4/2, 9/3))

# Contrast:
.1 == .3/3
num_equal(.1, .3/3)

# Contrast:
v <- c(.9 - .8, .8 - .7, .7 - .6, .6 - .5, 
       .5 - .4, .4 - .3, .3 - .2, .2 -.1, .1)
unique(v)
.1 == v
num_equal(.1, v)

Description

outliers is a fictitious dataset containing the id, sex, and height of 1000 non-existing, but otherwise normal people.

Usage

outliers

Format

A table with 100 cases (rows) and 3 variables (columns).

Details

Codebook

id

Participant ID (as character code)

sex

Gender (female vs. male)

height

Height (in cm)

Source

See CSV data at http://rpository.com/ds4psy/data/out.csv.

See Also

Other datasets: Bushisms, Trumpisms, countries, data_1, data_2, data_t1, data_t1_de, data_t1_tab, data_t2, data_t3, data_t4, dt_10, exp_num_dt, exp_wide, falsePosPsy_all, fame, flowery, fruits, pi_100k, posPsy_AHI_CESD, posPsy_long, posPsy_p_info, posPsy_wide, t3, t4, t_1, t_2, t_3, t_4, table6, table7, table8, table9, tb

Description

pal_ds4psy provides a dedicated color palette.

Usage

pal_ds4psy

Format

An object of class data.frame with 1 rows and 11 columns.

Details

By default, pal_ds4psy is based on pal_unikn of the unikn package.

See Also

Other color objects and functions: pal_n_sq()

Description

pal_n_sq returns n^2 dedicated colors of a color palette pal (up to a maximum of n = "all" colors).

Usage

pal_n_sq(n = "all", pal = pal_ds4psy)

Arguments

Details

Use the more specialized function unikn::usecol for choosing n dedicated colors of a known color palette.

See Also

plot_tiles to plot tile plots.

Other color objects and functions: pal_ds4psy

Examples

pal_n_sq(1)  #  1 color: seeblau3
pal_n_sq(2)  #  4 colors
pal_n_sq(3)  #  9 colors (5: white)
pal_n_sq(4)  # 11 colors (6: white)