Package 'thinkr'

delete .test file in testthat folder

Description

Only usefull during package developpement using testthat package

Usage

.efface_test()

---

not in

Description

not in

Usage

x %ni% table

Arguments

x	vector or NULL: the values to be matched
table	the values to be matched against

Examples

"a" %ni% letters
"coucou" %ni% letters

---

Save all ggplot in a pptx

Description

Save all ggplot in a pptx

Usage

all_ggplot_to_pptx(
  out = "tous_les_graphs.pptx",
  open = TRUE,
  png = TRUE,
  folder = "dessin",
  global = TRUE
)

Arguments

out	output file name
open	booleen open file after creation
png	booleen also save as png
folder	png's folder
global	booleen use .GlobalEnv

Examples

## Not run: 
all_ggplot_to_pptx()

## End(Not run)

---

Transform a vector into numeric if meaningful, even with bad decimal, space or %

Description

Transform a vector into numeric if meaningful, even with bad decimal, space or %

Usage

as_mon_numeric(vec)

Arguments

vec

a vector

Details

Note that text and factors are not transformed as numeric (except FALSE, TRUE, F, T), contrary to R default behavior with 'as.numeric(factor())'

Value

a numeric vector

Examples

as_mon_numeric(c("1", "0", "1"))
as_mon_numeric(c("1.3", "1,5", "1;6", "16%", "17 87 "))
as_mon_numeric(c(TRUE, "A", "F"))
as_mon_numeric(c(TRUE, TRUE, FALSE))
as_mon_numeric(factor(c("toto", "tata", "toto")))

---

Clean levels label

Description

Clean levels label

Usage

clean_levels(vec, verbose = FALSE, translit = FALSE, punct = FALSE)

Arguments

vec	a factor
verbose	booleen is the function verbose
translit	booleen remove non ascii character
punct	booleen do you remove punctuation

---

clean_names

Description

clean_names

Usage

clean_names(dataset, verbose = FALSE, translit = TRUE)

Arguments

dataset	a dataframe
verbose	logical
translit	logical remove non ascii character

Value

a dataframe

Examples

data(iris)
clean_names(iris)

---

Clean character vector

Description

Clean character vector

Usage

clean_vec(
  vec,
  verbose = FALSE,
  unique = TRUE,
  keep_number = FALSE,
  translit = TRUE,
  punct = TRUE
)

Arguments

vec	character vector to clean
verbose	logical is the function verbose
unique	logical do we have to apply make_unique
keep_number	logical keep number at begining
translit	logical remove non ascii character
punct	logical do you remove punctuation

---

return R instruction to create levels

Description

return R instruction to create levels

Usage

dput_levels(vec)

Arguments

vec	a factor or character vector

Value

a R instruction

Examples

dput_levels(iris$Species)

---

Get position or excel name of column

Description

ncol_to_excel returns excel column name from a position number. excel_to_ncol returns excel column position number from a column name. excel_col returns all excel column name.

Usage

ncol_to_excel(n)

excel_to_ncol(col_name)

excel_col()

Arguments

n	the column position
col_name	the culumn name

Examples

ncol_to_excel(35)
excel_to_ncol("BF")
excel_col()
ncol_to_excel(1:6)
excel_to_ncol(c('AF', 'AG', 'AH'))

---

find pattern in name's dataset

Description

find pattern in name's dataset

Usage

find_name(dataset, pattern)

Arguments

dataset	a data.frame (or list or anything with names parameter)
pattern	pattern we are looking for

Value

a list with position and value

Examples

find_name(iris,"Sepal")

---

transform the excel numeric date format into POSIXct

Description

transform the excel numeric date format into POSIXct

Usage

from_excel_to_posixt(vec, origin = "1904-01-01")

Arguments

vec	a vector
origin	a date-time object, or something which can be coerced by as.POSIXct(tz = "GMT") to such an object.

---

like gsub but keep a factor as factor

Description

like gsub but keep a factor as factor

Usage

gsub2(x, ...)

Arguments

x	a vector
...	les parametres de la fonction gsub

Value

a vector

---

Predicate for charater vector full of figures

Description

detects if a character vector is only made with figures. Useful when you

Usage

is_full_figures(.)

Arguments

.	a vector of character (and eventually NA's)

Value

a boolean

Examples

is_full_figures(c(NA,"0","25.3"))
is_full_figures((c(NA,"0","25_3")))

---

Predicate for full NA vector

Description

is_full_na test if the vector is full of NA's

Usage

is_full_na(.)

Arguments

.

a vector

Value

a vector of boolean

Examples

is_full_na(c(NA, NA, NA))

---

is a factor a likert scale

Description

is a factor a likert scale

Usage

is_likert(vec, lev)

Arguments

vec	a factor
lev	le scale

Value

boolean

Examples

is_likert(iris$Species,c("setosa","versicolor","virginica"))
is_likert(iris$Species,c("setosa","versicolor","virginica","banana"))
is_likert(iris$Species,c("setosa","versicolor"))

---

does this vector only contains 0 and 1

Description

does this vector only contains 0 and 1

Usage

is.01(x)

Arguments

x

a vector

Value

a boolean

Examples

is.01(c(0,1,0,0,1))
is.01(c(0,1,0,0,5))

---

does this vector only contains 1 and 2

Description

does this vector only contains 1 and 2

Usage

is.12(x)

Arguments

x

a vector

Value

a boolean

Examples

is.12(c(1,1,2,1,2))
is.12(c(1,1,2,1,5))

---

return TRUE if this look like a number

Description

return TRUE if this look like a number

Usage

look_like_a_number(vec)

Arguments

vec

a vector

Value

un booleen

---

make.unique improvement

Description

make.unique improvement

Usage

make_unique(vec, sep = "_")

Arguments

vec	a vector
sep	char separator to use

Value

a vector

Examples

make_unique(c("a","a","a","b","a","b","c"))

---

peep the pipeline

Description

peep some data at one step of a pipeline.

Usage

peep(data, ..., printer = print, verbose = FALSE)

Arguments

data	some data
...	function names or expressions that use . as a placeholder for the data
printer	which function use to print
verbose	TRUE to include what is printed

Value

the input data

Examples

if( require(magrittr) ){
  # just symbols
  iris %>% peep(head,tail) %>% summary
  # expressions with .
  iris %>% peep(head(., n=2),tail(., n=3) ) %>% summary
  # or both
  iris %>% peep(head,tail(., n=3) ) %>% summary
  # use verbose to see what happens
  iris %>% peep(head,tail(., n=3), verbose = TRUE) %>% summary
}

---

Replace pattern everywhere in a data.frame

Description

Replace pattern everywhere in a data.frame

Usage

replace_pattern(dataset, pattern, replacement, exact = FALSE)

Arguments

dataset	a data.frame
pattern	Pattern to look for.
replacement	A character of replacements.
exact	a boolean if TRUE the whole value need ton match

Value

a data.frame

Examples

dataset <- data.frame(
  col_a = as.factor(letters)[1:7],
  col_b = letters[1:7],
  col_c = 1:7,
  col_d = paste0(letters[1:7], letters[1:7]),
  stringsAsFactors = FALSE
)

# replace pattern
replace_pattern(dataset, "a", "XXX-")

# With exact matching
replace_pattern(dataset, "a", "XXX-", exact = TRUE)

---

export a data.frame to csv

Description

export a data.frame to csv

Usage

save_as_csv(dataset, path, row.names = FALSE, ...)

Arguments

dataset	a data.frame
path	the path
row.names	booleen do we have to save the row names
...	other write.csv parameters

Value

file name as character

Examples

## Not run: 
iris %>% save_as_csv(file.path(tempdir(),'coucou.csv')) %>% browseURL()



## End(Not run)

---

set a given coltype to each column in a data.frame

Description

set a given coltype to each column in a data.frame

Usage

set_col_type(dataset, col_type)

Arguments

dataset	a data.frame
col_type	a character vector containing the class to apply

Value

a data.frame

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