CodeAndRoll2

****Package in development****

Packaged version of the core functionalities (vector, matrix and list manipulations; math) of the formerly used CodeAndRoll (v1). A standalone set of more than >130 productivity functions. Used by MarkdownReports, ggExpress, SeuratUtils.

Installation

Install directly from GitHub via devtools with one R command:

# install.packages("devtools"); # If you don't have it.
require("devtools")
devtools::install_github(repo = "vertesy/CodeAndRoll2")

…then simply load the package:

require("CodeAndRoll2")

Alternatively, you simply source it from the web. This way function help will not work, and you will have no local copy of the code on your hard drive.

source("https://raw.githubusercontent.com/vertesy/CodeAndRoll2/master/CodeAndRoll2/R/CodeAndRoll2.R")

List of Functions

• vec.fromNames

  create a vector from a vector of names

• list.fromNames

  create list from a vector with the names of the elements

• matrix.fromNames

  Create a matrix from 2 vectors defining the row- and column names of the matrix. Default

• matrix.fromVector

  Create a matrix from values in a vector repeated for each column / each row. Similar to

• array.fromNames

  create an N-dimensional array from N vectors defining the row-,

• what

  A better version of is(). It can print the first “printme” elements.

• idim

  A dim() function that can handle if you pass on a vector: then, it gives the length.

• idimnames

  A dimnames() function that can handle if you pass on a vector: it gives back the names.

• table_fixed_categories

  generate a table() with a fixed set of categories. It fills up the table with missing categories, that are relevant

• grepv

  grep returning the value

• most_frequent_elements

  Show the most frequent elements of a table

• top_indices

  Returns the position / index of the n highest values. For equal values, it maintains the original order

• trail

  A combination of head() and tail() to see both ends.

• sort.decreasing

  Sort in decreasing order.

• sstrsplit

  Alias for str_split_fixed in the stringr package

• topN.dfCol

  Find the n highest values in a named vector

• bottomN.dfCol

  Find the n lowest values in a named vector

• as.named.vector

  Convert a dataframe column or row into a vector, keeping the corresponding dimension name.

• col2named.vector

  Convert a dataframe column into a vector, keeping the corresponding dimension name.

• row2named.vector

  Convert a dataframe row into a vector, keeping the corresponding dimension name.

• tibble_summary_to_named_vec

  …

• as_tibble_from_named_vec

  Convert a vector with names into a tibble, keeping the names as rownames.

• as.numeric.wNames

  Converts any vector into a numeric vector, and puts the original character values into the names of the new vector, unless it already has

• as.numeric.wNames.old

  Converts any vector into a numeric vector, and puts the original character values into the names of the new vector, unless it already has

• as.character.wNames

  Converts your input vector into a character vector, and puts the original character values into the names of the new vector, unless it

• rescale

  linear transformation to a given range of values

• flip_value2name

  Flip the values and the names of a vector with names

• sortbyitsnames

  Sort a vector by the alphanumeric order of its names(instead of its values).

• any.duplicated

  How many entries are duplicated

• which.duplicated

  which values are duplicated?

• which.NA

  which values are NA?

• pad.na

  Fill up with a vector to a given length with NA-values at the end.

• clip.values

  Signal clipping. Cut values above or below a threshold.

• clip.outliers

  Signal clipping based on the input data’s distribution. It clips values

• as.logical.wNames

  Converts your input vector into a logical vector, and puts the original character values into the names of the new vector, unless it

• col2named.vec.tbl

  Convert a 2-column table(data frame) into a named vector. 1st column will be used as names.

• iterBy.over

  Iterate over a vector by every N-th element.

• zigzagger

  mix entries so that they differ

• numerate

  numerate from x to y with additonal zeropadding

• MaxN

  find second (third…) highest/lowest value in vector

• cumsubtract

  Cumulative subtraction, opposite of cumsum()

• sumBySameName

  Sum up vector elements with the same name

• which_names

  Return the names where the input vector is TRUE. The input vector is converted to logical.

• which_names_grep

  Return the vector elements whose names are partially matched

• na.omit.strip

  Calls na.omit() and returns a clean vector

• inf.omit

  Omit infinite values from a vector.

• zero.omit

  Omit zero values from a vector.

• pc_TRUE

  Percentage of true values in a logical vector, parsed as

• pc_in_total_of_match

  Percentage of a certain value within a vector or table.

• filter_survival_length

  Parse a sentence reporting the % of filter survival.

• remove_outliers

  Remove values that fall outside the trailing N % of the distribution.

• simplify_categories

  Replace every entry that is found in “replaceit”, by a single value provided by “to”

• lookup

  Awesome pattern matching for a set of values in another set of values. Returns a list with all kinds of

• rowMedians

  Calculates the median of each row of a numeric matrix / data frame.

• colMedians

  Calculates the median of each column of a numeric matrix / data frame.

• rowGeoMeans

  Calculates the median of each row of a numeric matrix / data frame.

• colGeoMeans

  Calculates the median of each column of a numeric matrix / data frame.

• rowCV

  Calculates the CV of each ROW of a numeric matrix / data frame.

• colCV

  Calculates the CV of each column of a numeric matrix / data frame.

• rowVariance

  Calculates the CV of each ROW of a numeric matrix / data frame.

• colVariance

  Calculates the CV of each column of a numeric matrix / data frame.

• rowMin

  Calculates the minimum of each row of a numeric matrix / data frame.

• colMin

  Calculates the minimum of each column of a numeric matrix / data frame.

• rowMax

  Calculates the maximum of each row of a numeric matrix / data frame.

• colMax

  Calculates the maximum of each column of a numeric matrix / data frame.

• rowSEM

  Calculates the SEM of each row of a numeric matrix / data frame.

• colSEM

  Calculates the SEM of each column of a numeric matrix / data frame.

• rowSD

  Calculates the SEM of each row of a numeric matrix / data frame.

• colSD

  Calculates the SEM of each column of a numeric matrix / data frame.

• rowIQR

  Calculates the SEM of each row of a numeric matrix / data frame.

• colIQR

  Calculates the SEM of each column of a numeric matrix / data frame.

• rowquantile

  Calculates the SEM of each row of a numeric matrix / data frame.

• colquantile

  Calculates the SEM of each column of a numeric matrix / data frame.

• colDivide

  See more: https://stackoverflow.com/questions/20596433/how-to-divide-each-row-of-a-matrix-by-elements-of-a-vector-in-r

• colMutliply

  See more: https://stackoverflow.com/questions/20596433/how-to-divide-each-row-of-a-matrix-by-elements-of-a-vector-in-r

• rowDivide

  divide by row

• rowMutliply

  Mutliply by row

• row.Zscore

  Calculate Z-score over rows of data frame.

• TPM_normalize

  normalize each column to 1 million

• median_normalize

  normalize each column to the median of all the column-sums

• mean_normalize

  normalize each column to the median of the columns

• rotate

  rotate a matrix 90 degrees.

• sortEachColumn

  Sort each column of a numeric matrix / data frame.

• sort.mat

  Sort a matrix. ALTERNATIVE: dd[with(dd, order(-z, b)), ]. Source: https://stackoverflow.com/

• rowNameMatrix

  Create a copy of your matrix, where every entry is replaced by the corresponding row name. Useful if you want to color by row name in a

• colNameMatrix

  Create a copy of your matrix, where every entry is replaced by the corresponding column name. Useful if you want to color by column

• rownames.trimws

  trim whitespaces from the rownames

• colsplit

  split a data frame by a factor corresponding to columns.

• rowsplit

  split a data frame by a factor corresponding to columns.

• select.rows.and.columns

  Subset rows and columns. It checks if the selected dimension names exist and reports if any of those they

• getRows

  Get the subset of rows with existing rownames, report how much it could not find.

• getCols

  Get the subset of cols with existing colnames, report how much it could not find.

• get.oddoreven

  Get odd or even columns or rows of a data frame

• combine.matrices.intersect

  combine matrices by rownames intersect

• merge_dfs_by_rn

  Merge any data frames by rownames. Required plyr package

• merge_numeric_df_by_rn

  Merge 2 numeric data frames by rownames

• remove.na.rows

  cols have to be a vector of numbers corresponding to columns

• remove.na.cols

  cols have to be a vector of numbers corresponding to columns

• na.omit.mat

  Omit rows with NA values from a matrix. Rows with any, or full of NA-s

• copy.dimension.and.dimnames

  copy dimension and dimnames

• mdlapply

  lapply for multidimensional arrays

• arr.of.lists.2.df

  simplify 2D-list-array to a DF

• mdlapply2df

  multi dimensional lapply + arr.of.lists.2.df (simplify 2D-list-array to a DF)

• any.duplicated.rownames.ls.of.df

  Check if there are any duplocated rownames in a list of dataframes.

• intersect.ls

  Intersect any number of lists.

• union.ls

  Intersect any number of list elements. Faster than reduce.

• unlapply

  lapply, then unlist

• list.wNames

  create a list with names from ALL variables you pass on to the function

• as.list.df.by.row

  Split a dataframe into a list by its columns. omit.empty for the listelments; na.omit

• as.list.df.by.col

  oSplit a dataframe into a list by its rows. omit.empty for the listelments; na.omit and

• reorder.list

  reorder elements of lists in your custom order of names / indices.

• range.list

  range of values in whole list

• intermingle2lists

  Combine 2 lists (of the same length) so that form every odd and every even element of a unified list. Useful for side-by-side comparisons,

• as.listalike

  convert a vector to a list with certain dimensions, taken from the list it wanna resemble

• reverse.list.hierarchy

  reverse list hierarchy

• list2fullDF.byNames

  …

• list2fullDF.presence

  Convert a list to a full matrix. Designed for occurence counting, think tof table(). Rows = all ENTRIES

• splitbyitsnames

  split a list by its names

• splititsnames_byValues

  split a list by its names

• intermingle2vec

  Combine 2 vectors (of the same length) so that form every odd and every even element of a unified vector.

• intermingle.cbind

  Combine 2 data frames (of the same length) so that form every odd and every even element of a unified list. Useful for side-by-side

• ls2categvec

  Convert a list to a vector repeating list-element names, while vector names are the list elements

• list.2.replicated.name.vec

  Convert a list to a vector, with list elements names replicated as many times, as many elements each

• symdiff

  Quasy symmetric difference of any number of vectors

• cv

  …

• sem

  Calculates the standard error of the mean (SEM) for a numeric vector (it

• fano

  Calculates the fano factor on a numeric vector (it excludes NA-s

• geomean

  Calculates the geometric mean of a numeric vector (it excludes NA-s by default)

• mean_of_log

  Calculates the mean of the log_k of a numeric vector (it excludes NA-s by default)

• movingAve

  Calculates the moving / rolling average of a numeric vector.

• movingAve2

  Calculates the moving / rolling average of a numeric vector, using filter().

• movingSEM

  Calculates the moving / rolling standard error of the mean (SEM) on a numeric vector.

• imovingSEM

  Calculates the moving / rolling standard error of the mean (SEM). It calculates it to the edge of the vector with incrementally smaller

• shannon.entropy

  Calculate shannon entropy