I have two large files (~10GB) as follows:
file1.csv
name,id,dob,year,age,score
Mike,1,2014-01-01,2016,2,20
Ellen,2, 2012-01-01,2016,4,35
.
.
file2.csv
id,course_name,course_id
1,math,101
1,physics,102
1,chemistry,103
2,math,101
2,physics,102
2,chemistry,103
.
.
I want to subtract 1 from the "id" columns of these files:
file1_updated.csv
name,id,dob,year,age,score
Mike,0,2014-01-01,2016,2,20
Ellen,0, 2012-01-01,2016,4,35
file2_updated.csv
id,course_name,course_id
0,math,101
0,physics,102
0,chemistry,103
1,math,101
1,physics,102
1,chemistry,103
I have tried awk '{print ($1 - 1) "," $0}' file2.csv, but did not get the correct result:
-1,id,course_name,course_id
0,1,math,101
0,1,physics,102
0,1,chemistry,103
1,2,math,101
1,2,physics,102
1,2,chemistry,103
You've added an extra column in your attempt. Instead set your first field $1 to $1-1:
awk -F"," 'BEGIN{OFS=","} {$1=$1-1;print $0}' file2.csv
That semicolon separates the commands. We set the delimiter to comma (-F",") and the Output Field Seperator to comma BEGIN{OFS=","}. The first command to subtract 1 from the first field executes first, then the print command executes second, so the entire record, $0, will now contain the new $1 value when it's printed.
It might be helpful to only subtract 1 from records that are not your header. So you can add a condition to the first command:
awk -F"," 'BEGIN{OFS=","} NR>1{$1=$1-1} {print $0}' file2.csv
Now we only subtract when the record number (NR) is greater than 1. Then we just print the entire record.
This question already has answers here:
Eliminate partially duplicate lines by column and keep the last one
(4 answers)
Closed 6 years ago.
INPUT FILE :
5,,OR1,1000,Nawras,OR,20160105T05:30:17+0400,20181231T23:59:59+0400,,user,,aaa8016058f008ddceae6329f0c5d551,50293277591,,,30001,C
5,,OR1,1000,Nawras,OR,20160105T05:30:17+0400,20181231T23:59:59+0400,20160217T01:45:18+0400,,user,aaa8016058f008ddceae6329f0c5d551,50293277591,,,30001,H
5,,OR2,2000,Nawras,OR,20160216T06:30:18+0400,20191231T23:59:59+0400,,user,,f660818af5625b3be61fe12489689601,50328589469,,,30002,C
5,,OR2,2000,Nawras,OR,20160216T06:30:18+0400,20191231T23:59:59+0400,20160216T06:30:18+0400,,user,f660818af5625b3be61fe12489689601,50328589469,,,30002,H
5,,OR1,1000,Nawras,OR,20150328T03:00:13+0400,20171230T23:59:59+0400,,user,,22bf18b024e1d4f42ac79943062cf576,50212935879,,,10001,C
5,,OR1,1000,Nawras,OR,20150328T03:00:13+0400,20171230T23:59:59+0400,20150328T03:00:13+0400,,user,22bf18b024e1d4f42ac79943062cf576,50212935879,,,10001,H
0,,OR5,5000,Nawras,OR,20160421T02:45:16+0400,20191231T23:59:59+0400,,user,,c7c501ac92d85a04bb26c575929e9317,50329769192,,,11001,C
0,,OR5,5000,Nawras,OR,20160421T02:45:16+0400,20191231T23:59:59+0400,20160421T02:45:16+0400,,user,c7c501ac92d85a04bb26c575929e9317,50329769192,,,11001,H
0,,OR1,1000,Nawras,OR,20160330T02:00:14+0400,20181231T23:59:59+0400,,user,,d4ea749306717ec5201d264fc8044201,50285524333,,,11001,C
DESIRED OUTPUT :
5,,OR1,1000,UY,OR,20160105T05:30:17+0400,20181231T23:59:59+0400,20160217T01:45:18+0400,,user,aaa8016058f008ddceae6329f0c5d551,50293277591,,,30001,H
5,,OR2,2000,UY,OR,20160216T06:30:18+0400,20191231T23:59:59+0400,20160216T06:30:18+0400,,user,f660818af5625b3be61fe12489689601,50328589469,,,30002,H
5,,OR1,1000,UY,OR,20150328T03:00:13+0400,20171230T23:59:59+0400,20150328T03:00:13+0400,,user,22bf18b024e1d4f42ac79943062cf576,50212935879,,,10001,H
0,,OR5,5000,UY,OR,20160421T02:45:16+0400,20191231T23:59:59+0400,20160421T02:45:16+0400,,user,c7c501ac92d85a04bb26c575929e9317,50329769192,,,11001,H
0,,OR1,1000,UY,OR,20160330T02:00:14+0400,20181231T23:59:59+0400,,user,,d4ea749306717ec5201d264fc8044201,50285524333,,,11001,C*
CODE USED :
for i in `cat file | awk -F, '{print $13}' | sort | uniq`
do
grep $i file | tail -1 >> TESTINGGGGGGG_SV
done
This took much time as the file has 300 million records and which has 65 million uniq records at 13th column .
So i would require a output which can traverse 13th column value - last occurrence in file as the output .
awk to the rescue!
awk -F, 'p!=$13 && p0 {print p0} {p=$13; p0=$0} END{print p0}' file
expects sorted input.
Please post the timing if you can successfully run the script.
If sorting is not possible, another option is
tac file | awk -F, '!a[$13]++' | tac
reverse the file, take the first entry for $13 and reverse the results back.
Here's a solution that should work:
awk -F, '{rows[$13]=$0} END {for (i in rows) print rows[i]}' file
Explanation:
rows is an associative array indexed by field 13 $13, the element of the array indexed by $13 gets overwritten every time there's a duplicate of field 13; its value is the whole line $0.
But this is inefficient in terms of memory because of the space needed to save the array.
An improvement to the above solution that's still not using sorting is to just save the line numbers in the associative array:
awk -F, '{rows[$13]=NR}END {for(i in rows) print rows[i]}' file|while read lN; do sed "${lN}q;d" file; done
Explanation:
rows as before but the values are the line numbers and not the whole lines
awk -F, '{rows[$13]=NR}END {for(i in rows) print rows[i]}' file outputs a list of row numbers containing the sought lines
sed "${lN}q;d" fetches line number lN from file
I have a text file with a large amount of data which is tab delimited. I want to have a look at the data such that I can see the unique values in a column. For example,
Red Ball 1 Sold
Blue Bat 5 OnSale
...............
So, its like the first column has colors, so I want to know how many different unique values are there in that column and I want to be able to do that for each column.
I need to do this in a Linux command line, so probably using some bash script, sed, awk or something.
What if I wanted a count of these unique values as well?
Update: I guess I didn't put the second part clearly enough. What I wanted to do is to have a count of "each" of these unique values not know how many unique values are there. For instance, in the first column I want to know how many Red, Blue, Green etc coloured objects are there.
You can make use of cut, sort and uniq commands as follows:
cat input_file | cut -f 1 | sort | uniq
gets unique values in field 1, replacing 1 by 2 will give you unique values in field 2.
Avoiding UUOC :)
cut -f 1 input_file | sort | uniq
EDIT:
To count the number of unique occurences you can make use of wc command in the chain as:
cut -f 1 input_file | sort | uniq | wc -l
awk -F '\t' '{ a[$1]++ } END { for (n in a) print n, a[n] } ' test.csv
You can use awk, sort & uniq to do this, for example to list all the unique values in the first column
awk < test.txt '{print $1}' | sort | uniq
As posted elsewhere, if you want to count the number of instances of something you can pipe the unique list into wc -l
Assuming the data file is actually Tab separated, not space aligned:
<test.tsv awk '{print $4}' | sort | uniq
Where $4 will be:
$1 - Red
$2 - Ball
$3 - 1
$4 - Sold
# COLUMN is integer column number
# INPUT_FILE is input file name
cut -f ${COLUMN} < ${INPUT_FILE} | sort -u | wc -l
Here is a bash script that fully answers the (revised) original question. That is, given any .tsv file, it provides the synopsis for each of the columns in turn. Apart from bash itself, it only uses standard *ix/Mac tools: sed tr wc cut sort uniq.
#!/bin/bash
# Syntax: $0 filename
# The input is assumed to be a .tsv file
FILE="$1"
cols=$(sed -n 1p $FILE | tr -cd '\t' | wc -c)
cols=$((cols + 2 ))
i=0
for ((i=1; i < $cols; i++))
do
echo Column $i ::
cut -f $i < "$FILE" | sort | uniq -c
echo
done
This script outputs the number of unique values in each column of a given file. It assumes that first line of given file is header line. There is no need for defining number of fields. Simply save the script in a bash file (.sh) and provide the tab delimited file as a parameter to this script.
Code
#!/bin/bash
awk '
(NR==1){
for(fi=1; fi<=NF; fi++)
fname[fi]=$fi;
}
(NR!=1){
for(fi=1; fi<=NF; fi++)
arr[fname[fi]][$fi]++;
}
END{
for(fi=1; fi<=NF; fi++){
out=fname[fi];
for (item in arr[fname[fi]])
out=out"\t"item"_"arr[fname[fi]][item];
print(out);
}
}
' $1
Execution Example:
bash> ./script.sh <path to tab-delimited file>
Output Example
isRef A_15 C_42 G_24 T_18
isCar YEA_10 NO_40 NA_50
isTv FALSE_33 TRUE_66