Ege Ulgen egeulgen

Extract fields 2, 4, and 5 from file.txt:

awk '{print $2,$4,$5}' input.txt

Print each line where the 5th field is equal to ‘abc123’:

awk '$5 == "abc123"' file.txt

Print each line where the 5th field is not equal to ‘abc123’:

	##################################################
	## Project: pathfindR
	## Script purpose: Try to resolve issue 22
	## Date: Oct 15, 2019
	## Author: Ege Ulgen
	##################################################

	options(stringsAsFactors = FALSE)

	# Create M.musculus KEGG Gene Sets ----------------------------------------

	FUN <- function(x) {
	x <- as.integer(x)
	div <- seq_len(abs(x))
	factors <- div[x %% div == 0L]
	factors <- list(neg = -factors, pos = factors)
	return(factors)
	}

	multimerge <- function(mypath){
	filenames <- list.files(path=mypath, full.names=TRUE)
	datalist <- lapply(filenames, function(x) read.csv(file=x,header=T))
	result_df <- Reduce(function(x,y) merge(x,y), datalist)
	return(result_df)
	}

	### Cleaner and faster
	# import files
	files <- list.files(pattern="*.csv")

	class ProgressPercentage(object):
	''' Progress Class
	Class for calculating and displaying download progress
	'''
	def __init__(self, client, bucket, filename):
	''' Initialize
	initialize with: file name, file size and lock.
	Set seen_so_far to 0. Set progress bar length
	'''
	self._filename = filename

	def indexExcelColumnFinder(self, idx):
	''' Find Excel-style Column Name
	Given a 0-based index 'idx', returns the
	corresponding Excel-style column naming
	(eg. 3 >> D, 26 >> AA, 27 >> AB etc.)
	'''
	excelColumnNameList = []
	alphabet = map(chr, range(65, 91))

	if idx < 26:

	def splitDataFrameList(df,target_column,separator):
	''' df = dataframe to split,
	target_column = the column containing the values to split
	separator = the symbol used to perform the split
	returns: a dataframe with each entry for the target column separated, with each element moved into a new row.
	The values in the other columns are duplicated across the newly divided rows.
	'''
	def splitListToRows(row,row_accumulator,target_column,separator):
	split_row = row[target_column].split(separator)
	for s in split_row: