What does print(… sep='', '\t' ) mean?

Question

I am having a bit of trouble trying to find an answer to this. I would like to know what the syntax sep=\"\" and \\t means. I have found some infor

Answer 1

sep='' in the context of a function call sets the named argument sep to an empty string. See the print() function; sep is the separator used between multiple values when printing. The default is a space (sep=' '), this function call makes sure that there is no space between Property tax: $ and the formatted tax floating point value.

Compare the output of the following three print() calls to see the difference

>>> print('foo', 'bar')
foo bar
>>> print('foo', 'bar', sep='')
foobar
>>> print('foo', 'bar', sep=' -> ')
foo -> bar

All that changed is the sep argument value.

\t in a string literal is an escape sequence for tab character, horizontal whitespace, ASCII codepoint 9.

\t is easier to read and type than the actual tab character. See the table of recognized escape sequences for string literals.

Using a space or a \t tab as a print separator shows the difference:

>>> print('eggs', 'ham')
eggs ham
>>> print('eggs', 'ham', sep='\t')
eggs    ham

Answer 2

sep='\t' is often used for Tab-delimited file.

Answer 3

sep='' ignore whiteSpace. see the code to understand.Without sep=''

from itertools import permutations
s,k = input().split()
for i in list(permutations(sorted(s), int(k))):
    print(*i)

output:

HACK 2
A C
A H
A K
C A
C H
C K
H A
H C
H K
K A
K C
K H

using sep='' The code and output.

from itertools import permutations
s,k = input().split()
for i in list(permutations(sorted(s), int(k))):
    print(*i,sep='')

output:

HACK 2
AC
AH
AK
CA
CH
CK
HA
HC
HK
KA
KC
KH

Answer 4

The sep='\t' can be use in many forms, for example if you want to read tab separated value: Example: I have a dataset tsv = tab separated value NOT comma separated value df = pd.read_csv('gapminder.tsv'). when you try to read this, it will give you an error because you have tab separated value not csv. so you need to give read csv a different parameter called sep='\t'.

Now you can read: df = pd.read_csv('gapminder.tsv, sep='\t'), with this you can read the it.