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I have a CSV file with long multiline values as shown below
"Col1","Col2"
"val1","val2
blabla
blablula
"
"val3", "val4"
I use this code to try and read the CSV
from tempfile import NamedTemporaryFile
with open('multilined.csv', 'rb') as f:
for l in f.readlines():
if re.search(r'n', l):
parsecsv = '"' + re.sub(r'(n)(.*)(?=")', r'1', l) + '"'
# re.sub finds all newline sequences (regex). Then I
# use a lookahead assertion "?=" to know when that was
# the last one.
else:
parsecsv = '"' + l.decode('utf-8') + '"'
extcsv = NamedTemporaryFile(mode='w+')
extcsv.write(parsecsv)
extcsv.seek(0)
df = pd.read_csv(extcsv.name)
print df
This code then correctly prints one DataFrame correctly which looks like this
Col1 Col2
0 val1 val2
1 blabla
2 blablula
3 val3 val4
I then try to print df again but note that I do not read the file again but simply try to print the df again. Instead of printing the entire DataFrame it just prints first row (in this case it prints "val1" without "val2") My guess is because somewhere it sees newlines in one record as new records.
I tried using various dialects as described here (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html) but I have not been able to overcome this problem.
I hope my problem illustrates well!
I would be glad for any help!
Edit:
Answer below suggested using StringIO which immediately solved my problem!