TypeError: sequence item 0: expected string, int found

Question

string.join connects elements inside list of strings, not ints.

Use this generator expression instead :

values = ','.join(str(v) for v in value_list)

Although the given list comprehension / generator expression answers are ok, I find this easier to read and understand:

values = ','.join(map(str, value_list))

Replace

values = ",".join(value_list)

with

values = ','.join([str(i) for i in value_list])

OR

values = ','.join(str(value_list)[1:-1])

The answers by cval and Priyank Patel work great. However, be aware that some values could be unicode strings and therefore may cause the str to throw a UnicodeEncodeError error. In that case, replace the function str by the function unicode.

For example, assume the string Libië (Dutch for Libya), represented in Python as the unicode string u'Libi\xeb':

print str(u'Libi\xeb')

throws the following error:

Traceback (most recent call last):
  File "/Users/tomasz/Python/MA-CIW-Scriptie/RecreateTweets.py", line 21, in <module>
    print str(u'Libi\xeb')
UnicodeEncodeError: 'ascii' codec can't encode character u'\xeb' in position 4: ordinal not in range(128)

The following line, however, will not throw an error:

print unicode(u'Libi\xeb') # prints Libië

So, replace:

values = ','.join([str(i) for i in value_list])

by

values = ','.join([unicode(i) for i in value_list])

to be safe.

String interpolation is a nice way to pass in a formatted string.

values = ', '.join('$%s' % v for v in value_list)

you can convert the integer dataframe into string first and then do the operation e.g.

df3['nID']=df3['nID'].astype(str)
grp = df3.groupby('userID')['nID'].aggregate(lambda x: '->'.join(tuple(x)))