You can convert a string to a file object using io.StringIO and then pass that to the csv module:

from io import StringIO
import csv

scsv = """text,with,Polish,non-Latin,letters
1,2,3,4,5,6
a,b,c,d,e,f
gęś,zółty,wąż,idzie,wąską,dróżką,
"""

f = StringIO(scsv)
reader = csv.reader(f, delimiter=',')
for row in reader:
    print('\t'.join(row))

simpler version with split() on newlines:

reader = csv.reader(scsv.split('\n'), delimiter=',')
for row in reader:
    print('\t'.join(row))

Or you can simply split() this string into lines using \n as separator, and then split() each line into values, but this way you must be aware of quoting, so using csv module is preferred.

On Python 2 you have to import StringIO as

from StringIO import StringIO

instead.

You can use Python's StringIO() to give your data string a stream interface.

Do not attempt to use data.split('\n') as this will fail to split the lines correctly, the csv.reader() will correctly read the lines in, even if cells contain newlines:

from io import StringIO
import csv

data = '''"value1";"value2";"value3
stillvalue3"
"value4";"value5";"value6"'''

csv_input = csv.reader(StringIO(data, newline=''), delimiter=';')
rows = list(csv_input)
print("Rows", rows)    

Giving you:

Rows [['value1', 'value2', 'value3\nstillvalue3'], ['value4', 'value5', 'value6']]

This could then be loaded into Pandas, or directly using StringIO():

columns = ['col1', 'col2', 'col3']

df = pd.DataFrame(rows, columns=columns)

df = pd.read_csv(StringIO(data, newline=''), names=columns, sep=';')

print(df)

Giving:

     col1    col2                 col3
0  value1  value2  value3\nstillvalue3
1  value4  value5               value6

Your second example gives:

Rows [['value1', 'value2', 'value3\nstillvalue3\na "quote" inside the quote'], ['value4', 'value5', 'value6']]

     col1    col2                                             col3
0  value1  value2  value3\nstillvalue3\na "quote" inside the quote
1  value4  value5                                           value6