Develop Reference

How to replace characters in a csv file

I'm doing some measurements in the lab and want to transform them into some nice Python plots. The problem is the way the software exports CSV files, as I can't find a way to properly read the numbers. It looks like this:
-10;-0,0000026
-8;-0,00000139
-6;-0,000000546
-4;-0,000000112
-2;-5,11E-09
0,0000048;6,21E-09
2;0,000000318
4;0,00000304
6;0,0000129
8;0,0000724
10;0,000268
Separation by ; is fine, but I need every , to be ..
Ideally I would like Python to be able to read numbers such as 6.21E-09 as well, but I should be able to fix that in excel...
My main issue: Change every , to . so Python can read them as a float.

The simplest way would be for you to convert them to string and then use the .replace() method to pretty much do anything. For i.e.
txt = "0,0000048;6,21E-09"
txt = txt.replace(';', '.')
You could also read the CSV file (I don't know how you are reading the file) but depending on the library, you could change the 'delimiter' (to : for example). CSV is Comma-separated values and as the name implies, it separates columns by means of '.

You can do whatever you want in Python, for example:
import csv
with open('path_to_csv_file', 'r') as csv_file:
data = list(csv.reader(csv_file, delimiter=';'))
data = [(int(raw_row[0]), float(raw_row[1].replace(',', '.'))) for row in data]
with open('path_to_csv_file', 'w') as csv_file:
writer = csv.writer(csv_file, delimiter=';')
writer.writerows(data)

Can you consider a regex to match the ',' all in the text, then loop the match results in a process that takes ',' to '.'.

Why is my csv file separated by " \t " instead of commas (" , ")?

I downloaded data from internet and saved as a csv (comma delimited) file. The image shows what the file looks like in excel.
Using csv.reader in python, I printed each row. I have shown my code below along with the output in Spyder.
import csv
with open('p_dat.csv', 'r') as file:
reader = csv.reader(file)
for row in reader:
print(row)
I am very confused as to why my values are not comma separated. Any help will be greatly appreciated.

As pointed out in the comments, technically this is a TSV (tab-separated values) file, which is actually perfectly valid.
In practice, of course, not all libraries will make a "hard" distinction between a TSV and CSV file. The way you parse a TSV file is basically the same as the way you parse a CSV file, except that the delimiter is different.
There are actually multiple valid delimiters for this kind of file, such as tabs, commas, and semicolons. Which one you choose is honestly a matter of preference, not a "hard" technical limit.

See the specification for csvs. There are many options for the delimiter in the file. In this case you have a tab, \t.
The option is important. Suppose your data had commas in it, then a , as a delimiter would not be a good choice.

Even though they're named comma-separated values, they're sometimes separated by different symbols (like the tab character that you have currently).
If you want to use Python to view this as a comma-separated file, you can try something like:
import csv
...
with open('p_dat.csv', 'r') as file:
reader = csv.reader(file)
for row in reader:
commarow = row.replace("\t",",")
print(commarow)

Python: Write output in a csv-file

I have the following text (as string, \t = Tab):
Article_1 \t Title of Article \t author of article \n
Article_2 \t Title of Art 2 \t author of article 2 \n
I'd like to save this in a csv-file s.t. I can open it in Excel. In fact, it is possible to open the file I got in Excel, but the program writes everything in the first column, but I'd like to have "art_1, art_2, ..." in the first column, the titles in the second and the authors in the third column. How can I do this?
Thanks for any help! :)

If you have a string, str, one easy way is just:
with open("file.csv","w") as f:
f.write(','.join(str.split()))
If you have multiple strings, and they are stored in a list, str_list, you could do this:
with open("file.csv","w") as f:
for line in str_list:
f.write(','.join(line.split()))
f.write('\n')
If the question is how to split one monolithic string into manageable sub-strings, then that's a different question. In that case you'd want to split() on the \t and then go through the list 3 at a time.
There's also a csv python package that provides a clean way of creating csv files from python data structures.

In case you want to use the csv module
import csv
with open("csv_file.csv", "wb") as csv_file:
csv_writer = csv.writer(csv_file, delimiter=",")
for str in list_of_articles:
csv_writer.writerow(str.split("\t"))

How to write lines in a txt file, with data from a csv file

How can I tell Python to open a CSV file, and merge all columns per line, into new lines in a new TXT file?
To explain:
I'm trying to download a bunch of member profiles from a website, for a research project. To do this, I want to write a list of all the URLs in a TXT file.
The URLs are akin to this: website.com-name-country-title-id.html
I have written a script that takes all these bits of information for each member and saves them in columns (name/country/title/id), in a CSV file, like this:
mark japan rookie married
john sweden expert single
suzy germany rookie married
etc...
Now I want to open this CSV and write a TXT file with lines like these:
www.website.com/mark-japan-rookie-married.html
www.website.com/john-sweden-expert-single.html
www.website.com/suzy-germany-rookie-married.html
etc...
Here's the code I have so far. As you can probably tell I barely know what I'm doing so help will be greatly appreciated!!!
import csv
x = "http://website.com/"
y = ".html"
csvFile=csv.DictReader(open("NameCountryTitleId.csv")) #This file is stored on my computer
file = open("urls.txt", "wb")
for row in csvFile:
strArgument=str(row['name'])+"-"+str(row['country'])+"-"+str(row['title'])+"-"+str(row['id'])
try:
file.write(x + strArgument + y)
except:
print(strArgument)
file.close()
I don't get any error messages after running this, but the TXT file is completely empty.

Rather than using a DictReader, use a regular reader to make it easier to join the row:
import csv
url_format = "http://website.com/{}.html"
csv_file = 'NameCountryTitleId.csv'
urls_file = 'urls.txt'
with open(csv_file, 'rb') as infh, open(urls_file, 'w') as outfh:
reader = csv.reader(infh)
for row in reader:
url = url_format.format('-'.join(row))
outfh.write(url + '\n')
The with statement ensures the files are closed properly again when the code completes.
Further changes I made:
In Python 2, open a CSV files in binary mode, the csv module handles line endings itself, because correctly quoted column data can have embedded newlines in them.
Regular text files should be opened in text mode still though.
When writing lines to a file, do remember to add a newline character to delineate lines.
Using a string format (str.format()) is far more flexible than using string concatenations.
str.join() lets you join a sequence of strings together with a separator.

its actually quite simple, you are working with strings yet the file you are opening to write to is being opened in bytes mode, so every single time the write fails and it prints to the screen instead. try changing this line:
file = open("urls.txt", "wb")
to this:
file = open("urls.txt", "w")
EDIT:
i stand corrected, however i would like to point out that with an absence of newlines or some other form of separator, how do you intend to use the URLs later on? if you put newlines between each URL they would be easy to recover

How to convert tab separated, pipe separated to CSV file format in Python

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"))