I'm at a total loss of how to do this.
My Question: I want to take this:
"A, two words with comma","B","C word without comma","D"
"E, two words with comma","F","G more stuff","H no commas here!"
... (continue)
To this:
"A, two words with comma",B,C word without comma,D
"E, two words with comma",F,G more stuff,H no commas here!
... (continue)
I used software that created 1,900 records in a text file and I think it was supposed to be a CSV but whoever wrote the software doesn't know how CSV files work because it only needs quotes if the cell contains a comma (right?). At least I know that in Excel it puts everything in the first cell...
I would prefer this to be solvable using some sort of command line tool like perl or python (I'm on a Mac). I don't want to make a whole project in Java or anything to take care of this.
Any help is greatly appreciated!
Shot in the dark here, but I think that Excel is putting everything in the first column because it doesn't know it's being given comma-separated data.
Excel has a "text-to-columns" feature, where you'll be able to split a column by a delimiter (make sure you choose the comma).
There's more info here:
http://support.microsoft.com/kb/214261
edit
You might also try renaming the file from *.txt to *.csv. That will change the way Excel reads the file, so it better understands how to parse whatever it finds inside.
If just bashing is an option, you can try this one-liner in a terminal:
cat file.csv | sed 's/"\([^,]*\)"/\1/g' >> new-file.csv
That technically should be fine. It is text delimited with the " and separated via the ,
I don't see anything wrong with the first at all, any field may be quoted, only some require it. More than likely the writer of the code didn't want to over complicate the logic and quoted everything.
One way to clean it up is to feed the data to csv and dump it back.
import csv
from cStringIO import StringIO
bad_data = """\
"A, two words with comma","B","C word without comma","D"
"E, two words with comma","F","G more stuff","H no commas here!"
"""
buffer = StringIO()
writer = csv.writer(buffer)
writer.writerows(csv.reader(bad_data.split('\n')))
buffer.seek(0)
print buffer.read()
Python's csv.writer will default to the "excel" dialect, so it will not write the commas when not necessary.
Related
I'm aware this is a much discussed topic and even though there are similar questions I haven't found one that covers my particular case.
I have a csv file that is as follows:
alarm_id,alarm_incident_id,alarm_sitename,alarm_additionalinfo,alarm_summary
"XXXXXXX","XXXXXXXXX","XXXXX|4G_Availability_Issues","TTN-XXXX","XXXXXXX;[{"severity":"CRITICAL","formula":"${XXXXX} < 85"}];[{"name":"XXXXX","value":"0","updateTimestamp":"Oct 27, 2021, 2:00:00 PM"}];[{"coName":{"XXXX/XXX":"MRBTS-XXXX","LNCEL":"XXXXXX","LNBTS":"XXXXXXX"}}]||"
It has more lines but this is the trouble line. If you notice, the fifth field has within it several quotes and commas, which is also the separator. The quotes are also single instead of double quotes which are normally used to signal a quote character that should be kept in the field. What this is doing is splitting this last field into several when reading with pandas.read_csv() method, which throws an error of extra fields. I've tried several configurations and parameters regarding quoting in pandas.read_csv() but none works...
The csv is badly formatted, I just wanted to know if there is a way to still read it, even if using a roundabout way or it really is just hopeless.
Edit: This can happen to more than one column and I never know in which column(s) this may happen
Thank you for your help.
I think I've got what you're looking for, at least I hope.
You can read the file as regular, creating a list of the lines in the csv file.
Then iterate through the lines variable and split it into 4 parts, since you have 4 columns in the csv.
with open("test.csv", "r") as f:
lines = f.readlines()
for item in lines:
new_ls = item.strip().split(",", 4)
for new_item in new_ls:
print(new_item)
Now you can iterate through each lines' column item and do whatever you have/want to do.
If all your lines fields are consistently enclosed in quotes, you can try to split the line on ",", and to remove the initial and terminating quote. The current line is correctly separated with:
row = line.strip('"').split('","', 4)
But because of the incorrect formatting of your initial file, you will have to manually control it matches all the lines...
Can't post a comment so just making a post:
One option is to escape the internal quotes / commas, or use a regex.
Also, pandas.read_csv has a quoting parameter where you can adjust how it reacts to quotes, which might be useful.
I am having trouble simply saving items into a file for later reading. When I save the file, instead of listing the items as single items, it appends the data together as one long string. According to my Google searches, this should not be appending the items.
What am I doing wrong?
Code:
with open('Ped.dta','w+') as p:
p.write(str(recnum)) # Add record number to top of file
for x in range(recnum):
p.write(dte[x]) # Write date
p.write(str(stp[x])) # Write Steps number
Since you do not show your data or your output I cannot be sure. But it seems you are trying to use the write method like the print function, but there are important differences.
Most important, write does not follow its written characters with any separator (like space by default for print) or end (like \n by default for print).
Therefore there is no space between your data and steps number or between the lines because you did not write them and Python did not add them.
So add those. Try the lines
p.write(dte[x]) # Write date
p.write(' ') # space separator
p.write(str(stp[x])) # Write Steps number
p.write('\n') # line terminator
Note that I do not know the format of your "date" that is written, so you may need to convert that to text before writing it.
Now that I have the time, I'll implement #abarnert's suggestion (in a comment) and show you how to get the advantages of the print function and still write to a file. Just use the file= parameter in Python 3, or in Python 2 after executing the statement
from __future__ import print_function
Using print you can do my four lines above in one line, since print automatically adds the space separator and newline end:
print(dte[x], str(stp[x]), file=p)
This does assume that your date datum dte[x] is to be printed as text.
Try adding a newline ('\n') character at the end of your lines as you see in docs. This should solve the problem of 'listing the items as single items', but the file you create may not be greatly structured nonetheless.
For further of your google searches you may want to check serialization, as well as json and csv formats, covered in python standard library.
You question would have befited if you gave very small example of recnum variable + original f.close() is not necessary as you have a with statement, see here at SO.
When exporting excel/libreoffice sheets where the cells can contain new lines as CSV, the resulting file will have those new lines preserved as literal newline characters not something like the char string "\n".
The standard csv module in Python 3 apparently does not handle this as would be necessary. The documentation says "Note The reader is hard-coded to recognise either '\r' or '\n' as end-of-line, and ignores lineterminator. This behavior may change in the future." . Well, duh.
Is there some other way to read in such csv files properly? What csv really should do is ignore any new lines withing quoted text fields and only recognise new line characters outside a field, but since it does not, is there a different way to solve this short of implementing my own CSV parser?
Try using pandas with something like df = pandas.read_csv('my_data.csv'). You'll have more granular control over how the data is read in. If you're worried about formatting, you can also set the delimiter for the csv from libreoffice to something that doesn't occur in nature like ;;
How can I compile a string from selected rows of a file, run some operations on the string and then split that string back to the original rows into that same file?
I only need certain rows of the file. I cannot do the operations to the other parts of the file. I have made a class that separates these rows from the file and runs the operations on these rows, but I'm thinking this would be even faster to run these operations on a single string containing parts of the file that can be used in these operations...
Or, if I can run these operations on a whole dictionary, that would help too. The operations are string replacements and RegEx replacements.
I am using python 3.3
Edit:
I'm going to explain this in greater detail here since my original post was so vague (thank you Paolo for pointing that out).
For instance, if I would like to fix a SubRipper (.srt-file), which is a common subtitle file, I would take something like this as an input (this is from an actual srt-file):
Here you can find correct example, submitting the file contents here messes newlines:
http://pastebin.com/ZdWUpNZ2
...And then I would only fix those rows which have the actual subtitle lines, not those ordering number rows or those hide/show rows of the subtitle file. So my compiled string might be:
"They're up on that ridge.|They got us pinned down."
Then I would run operations on that string. Then I would have to save those rows back to the file. How can I get those subtitle rows back into my original file after they are fixed? I could split my compiled and fixed string using "|" as a row delimiter and put them back to the original file, but how can I be certain what row goes where?
You can use pysrt to edit SubRip files:
from pysrt import SubRipFile
subs = SubRipFile.open('some/file.srt')
for sub in subs:
# do something with sub.text
pass
# save changes to a new file
subs.save('other/path.srt', encoding='utf-8')
I have a CSV file that has data like this
15,"I",2,41301888,"BYRNESS RAW","","BYRNESS VILLAGE","NORTHUMBERLAND","ENG"
11,"I",3,41350101,2,2935,2,2008-01-09,1,8,0,2003-02-01,,2009-12-22,2003-02-11,377016.00,601912.00,377105.00,602354.00,10
I am reading this and then writing different rows to different CSV files.
However, in the original data there are quotes around the non-numeric fields, as some of them contain commas within the field.
I am not able to keep the quotes.
I have researched lots and discovered the quoting=csv.QUOTE_NONNUMERIC however this now results in a quote mark around every field and I dont know why??
If i try one of the other quoting options like MINIMAL I end up with an error message regarding the date value, 2008-01-09, not being a float.
I have tried to create a dialect, add the quoting on the csv reader and writer but nothing I have tried results in the getting an exact match to the original data.
Anyone had this same problem and found a solution.
When writing, quoting=csv.QUOTE_NONNUMERIC keeps values unquoted as long as they're numbers, ie. if their type is int or float (for example), which means it will write what you expect.
Your problem could be that, when reading, a csv.reader will turn every row it reads into a list of strings (if you read the documentation carefully enough, you'll see a reader does not perform automatic data type conversion!
If you don't perform any kind of conversion after reading, then when you write you'll end up with everything on quotes... because everything you write is a string.
Edit: of course, date fields will be quoted, because they are not numbers, meaning you cannot get the exact expected behaviour using the standard csv.writer.
Are you sure you have a problem? The behavior you're describing is correct: The csv module will enclose strings in quotes only if it's necessary for parsing them correctly. So you should expect to see quotes only around strings containing a comma, newlines, etc. Unless you're getting errors reading your output back in, there is no problem.
Trying to get an "exact match" of the original data is a difficult and potentially fruitless endeavor. quoting=csv.QUOTE_NONNUMERIC put quotes around everything because every field was a string when you read it in.
Your concern that some of the "quoted" input fields could have commas is usually not that big a deal. If you added a comma to one of your quoted fields and used the default writer, the field with the comma would be automatically quoted in the output.