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Parse pipe delimited CSV Python [duplicate]

I have a text file (.txt) which could be in tab separated format or pipe separated format, and I need to convert it into CSV file format. I am using python 2.6. Can any one suggest me how to identify the delimiter in a text file, read the data and then convert that into comma separated file.
Thanks in advance

I fear that you can't identify the delimiter without knowing what it is. The problem with CSV is, that, quoting ESR:
the Microsoft version of CSV is a textbook example of how not to design a textual file format.
The delimiter needs to be escaped in some way if it can appear in fields. Without knowing, how the escaping is done, automatically identifying it is difficult. Escaping could be done the UNIX way, using a backslash '\', or the Microsoft way, using quotes which then must be escaped, too. This is not a trivial task.
So my suggestion is to get full documentation from whoever generates the file you want to convert. Then you can use one of the approaches suggested in the other answers or some variant.
Edit:
Python provides csv.Sniffer that can help you deduce the format of your DSV. If your input looks like this (note the quoted delimiter in the first field of the second row):
a|b|c
"a|b"|c|d
foo|"bar|baz"|qux
You can do this:
import csv
csvfile = open("csvfile.csv")
dialect = csv.Sniffer().sniff(csvfile.read(1024))
csvfile.seek(0)
reader = csv.DictReader(csvfile, dialect=dialect)
for row in reader:
print row,
# => {'a': 'a|b', 'c': 'd', 'b': 'c'} {'a': 'foo', 'c': 'qux', 'b': 'bar|baz'}
# write records using other dialect

Your strategy could be the following:
parse the file with BOTH a tab-separated csv reader and a pipe-separated csv reader
calculate some statistics on resulting rows to decide which resultset is the one you want to write. An idea could be counting the total number of fields in the two recordset (expecting that tab and pipe are not so common). Another one (if your data is strongly structured and you expect the same number of fields in each line) could be measuring the standard deviation of number of fields per line and take the record set with the smallest standard deviation.
In the following example you find the simpler statistic (total number of fields)
import csv
piperows= []
tabrows = []
#parsing | delimiter
f = open("file", "rb")
readerpipe = csv.reader(f, delimiter = "|")
for row in readerpipe:
piperows.append(row)
f.close()
#parsing TAB delimiter
f = open("file", "rb")
readertab = csv.reader(f, delimiter = "\t")
for row in readerpipe:
tabrows.append(row)
f.close()
#in this example, we use the total number of fields as indicator (but it's not guaranteed to work! it depends by the nature of your data)
#count total fields
totfieldspipe = reduce (lambda x,y: x+ y, [len(f) for f in piperows])
totfieldstab = reduce (lambda x,y: x+ y, [len(f) for f in tabrows])
if totfieldspipe > totfieldstab:
yourrows = piperows
else:
yourrows = tabrows
#the var yourrows contains the rows, now just write them in any format you like

Like this
from __future__ import with_statement
import csv
import re
with open( input, "r" ) as source:
with open( output, "wb" ) as destination:
writer= csv.writer( destination )
for line in input:
writer.writerow( re.split( '[\t|]', line ) )

I would suggest taking some of the example code from the existing answers, or perhaps better use the csv module from python and change it to first assume tab separated, then pipe separated, and produce two output files which are comma separated. Then you visually examine both files to determine which one you want and pick that.
If you actually have lots of files, then you need to try to find a way to detect which file is which.
One of the examples has this:
if "|" in line:
This may be enough: if the first line of a file contains a pipe, then maybe the whole file is pipe separated, else assume a tab separated file.
Alternatively fix the file to contain a key field in the first line which is easily identified - or maybe the first line contains column headers which can be detected.

for line in open("file"):
line=line.strip()
if "|" in line:
print ','.join(line.split("|"))
else:
print ','.join(line.split("\t"))

Delimiter with tab in text file

Want to find the delimiter in the text file.
The text looks:
ID; Name
1; John Mak
2; David H
4; Herry
The file consists of tabs with the delimiter.
I tried with following: by referring
with open(filename, 'r') as f1:
dialect = csv.Sniffer().sniff(f1.read(1024), "\t")
print 'Delimiter:', dialect.delimiter
The result shows: Delimiter:
Expected result: Delimiter: ;

sniff can conclude with only one single character as the delimiter. Since your CSV file contains two characters as the delimiter, sniff will simply pick one of them. But since you also pass in the optional second argument to sniff, it will only pick what's contained in that value as a possible delimiter, which in your case, is '\t' (which is not visible from your print output).
From sniff's documentation:
If the optional delimiters parameter is given, it is interpreted as a
string containing possible valid delimiter characters.

Sniffing is not guaranteed to work.
Here is one approach that will work with any kind of delimiter.
You start with what you assume is the most common delimiter ; if that fails, then you try others until you manage to parse the row.
import csv
with open('sample.csv') as f:
reader = csv.reader(f, delimiter=';')
for row in reader:
try:
a,b = row
except ValueError:
try:
a,b = row[0].split(None, 1)
except ValueError:
a,b = row[0].split('\t', 1)
print('{} - {}'.format(a.strip(), b.strip()))
You can play around with this at this replt.it link, play with the sample.csv file if you want to try out different delimiters.
You can combine sniffing with this to catch any odd delimiters that are not known to you.

Trying to copy column1 from a csv file to another empty file using python

I'm looking for a way using python to copy the first column from a csv into an empty file. I'm trying to learn python so any help would be great!
So if this is test.csv
A 32
D 21
C 2
B 20
I want this output
A
D
C
B
I've tried the following commands in python but the output file is empty
f= open("test.csv",'r')
import csv
reader = csv.reader(f,delimiter="\t")
names=""
for each_line in reader:
names=each_line[0]

First, you want to open your files. A good practice is to use the with statement (that, technically speaking, introduces a context manager) so that when your code exits from the with block all the files are automatically closed
with open('test.csv') as inpfile, open('out.csv', 'w') as outfile:
next you want a loop on the lines of the input file (note the indentation, we are inside the with block), line splitting is automatic when you read a text file with lines separated by newlines…
for line in inpfile:
each line is a string, but you think of it as two fields separated by white space — this situation is so common that strings have a method to deal with this situation (note again the increasing indent, we are in the for loop block)
fields = line.split()
by default .split() splits on white space, but you can use, e.g., split(',') to split on commas, etc — that said, fields is a list of strings, for your first record it is equal to ['A', '32'] and you want to output just the first field in this list… for this purpose a file object has the .write() method, that writes a string, just a string, to the file, and fields[0] IS a string, but we have to add a newline character to it because, in this respect, .write() is different from print().
outfile.write(fields[0]+'\n')
That's all, but if you omit my comments it's 4 lines of code
with open('test.csv') as inpfile, open('out.csv', 'w') as outfile:
for line in inpfile:
fields = line.split()
outfile.write(fields[0]+'\n')
When you are done with learning (some) Python, ask for an explanation of this...
with open('test.csv') as ifl, open('out.csv', 'w') as ofl:
ofl.write('\n'.join(line.split()[0] for line in ifl))
Addendum
The csv module in such a simple case adds the additional conveniences of
auto-splitting each line into a list of strings
taking care of the details of output (newlines, etc)
and when learning Python it's more fruitful to see how these steps can be done using the bare language, or at least that it is my opinion…
The situation is different when your data file is complex, has headers, has quoted strings possibly containing quoted delimiters etc etc, in those cases the use of csv is recommended, as it takes into account all the gory details. For complex data analisys requirements you will need other packages, not included in the standard library, e.g., numpy and pandas, but that is another story.

This answer reads the CSV file, understanding a column to be demarked by a space character. You have to add the header=None otherwise the first row will be taken to be the header / names of columns.
ss is a slice - the 0th column, taking all rows as denoted by :
The last line writes the slice to a new filename.
import pandas as pd
df = pd.read_csv('test.csv', sep=' ', header=None)
ss = df.ix[:, 0]
ss.to_csv('new_path.csv', sep=' ', index=False)

import csv
reader = csv.reader(open("test.csv","rb"), delimiter='\t')
writer = csv.writer(open("output.csv","wb"))
for e in reader:
writer.writerow(e[0])

The best you can do is create a empty list and append the column and then write that new list into another csv for example:
import csv
def writetocsv(l):
#convert the set to the list
b = list(l)
print (b)
with open("newfile.csv",'w',newline='',) as f:
w = csv.writer(f, delimiter=',')
for value in b:
w.writerow([value])
adcb_list = []
f= open("test.csv",'r')
reader = csv.reader(f,delimiter="\t")
for each_line in reader:
adcb_list.append(each_line)
writetocsv(adcb_list)
hope this works for you :-)

Remove double quotes from iterator when using csv writer

I want to create a csv from an existing csv, by splitting its rows.
Input csv:
A,R,T,11,12,13,14,15,21,22,23,24,25
Output csv:
A,R,T,11,12,13,14,15
A,R,T,21,22,23,24,25
So far my code looks like:
def update_csv(name):
#load csv file
file_ = open(name, 'rb')
#init first values
current_a = ""
current_r = ""
current_first_time = ""
file_content = csv.reader(file_)
#LOOP
for row in file_content:
current_a = row[0]
current_r = row[1]
current_first_time = row[2]
i = 2
#Write row to new csv
with open("updated_"+name, 'wb') as f:
writer = csv.writer(f)
writer.writerow((current_a,
current_r,
current_first_time,
",".join((row[x] for x in range(i+1,i+5)))
))
#do only one row, for debug purposes
return
But the row contains double quotes that I can't get rid of:
A002,R051,02-00-00,"05-21-11,00:00:00,REGULAR,003169391"
I've tried to use writer = csv.writer(f,quoting=csv.QUOTE_NONE) and got a _csv.Error: need to escape, but no escapechar set.
What is the correct approach to delete those quotes?

I think you could simplify the logic to split each row into two using something along these lines:
def update_csv(name):
with open(name, 'rb') as file_:
with open("updated_"+name, 'wb') as f:
writer = csv.writer(f)
# read one row from input csv
for row in csv.reader(file_):
# write 2 rows to new csv
writer.writerow(row[:8])
writer.writerow(row[:3] + row[8:])

writer.writerow is expecting an iterable such that it can write each item within the iterable as one item, separate by the appropriate delimiter, into the file. So:
writer.writerow([1, 2, 3])
would write "1,2,3\n" to the file.
Your call provides it with an iterable, one of whose items is a string that already contains the delimiter. It therefore needs some way to either escape the delimiter or a way to quote out that item. For example,
write.writerow([1, '2,3'])
Doesn't just give "1,2,3\n", but e.g. '1,"2,3"\n' - the string counts as one item in the output.
Therefore if you want to not have quotes in the output, you need to provide an escape character (e.g. '/') to mark the delimiters that shouldn't be counted as such (giving something like "1,2/,3\n").
However, I think what you actually want to do is include all of those elements as separate items. Don't ",".join(...) them yourself, try:
writer.writerow((current_a, current_r,
current_first_time, *row[i+2:i+5]))
to provide the relevant items from row as separate items in the tuple.

Sorting CSV file with delimiter in Python

How to do read a .csv file with the following content
$C=2$A=3$B=1$
Then create a new .csv file with the same content but the $ changed into , and sorted alphabetically like the following:
A=3,B=1,C=2
Thank you!
Edit:
Here's my following code. It ended up giving an extra comma at the beginning of the output.
input = csv.reader(open('inputfile.csv','r'), delimiter='$')
output = open('outputfile.csv','w')
try:
writer = csv.writer(output)
for column in input:
writer.writerow(sorted(column))
print (sorted(column))
finally:
out.close()
Right now my input is:
$C=2$A=3$B=1$
and my output is:
,A=3,B=1,C=2
I want it to be:
A=3,B=1,C=2
Thanks!

with open('test.csv') as in_file, open('new.csv', 'w') as out_file:
for line in csv.reader(in_file, delimiter='$'):
out_file.write(','.join(sorted(line)[2:])+'\n')
Basically what this does is:
open the input as in_file
open the output as out_file
initializes a CSV reader with $ as the delimiter using in_file as the input file
iterates through each row doing the following:
sort all of the elements (after parsing)
discard the first 2 (since they'll always be empty strings due to the start/end delimiters on each line)
recombine those elements using , as the delimiter
write that out to the file with a trailing newline \n
edit: fixed for the start/end $ symbols by removing the empty elements that get parsed out of the CSV (the [2:] bit)

You can use a csv.reader to read the file with the delimiter set to '$'. Then for each row returned, strip out the empty elements and sort the rest:
row = sorted([item for item in row if item])