BUG: repr of Categorical does not distinguish int and str.

[simonjayhawkins]

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• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Code Sample, a copy-pastable example

>>> pd.Categorical([1, "2", 3, 4])
[1, 2, 3, 4]
Categories (4, object): [1, 3, 4, 2]

Problem description

does not show the string elements quoted. This is inconsistent with numpy.

>>> np.array([1, "2", 3, 4], dtype="object")
array([1, '2', 3, 4], dtype=object)

Expected Output

>>> pd.Categorical([1, "2", 3, 4])
[1, '2', 3, 4]
Categories (4, object): [1, 3, 4, '2']

Output of pd.show_versions()

[paste the output of pd.show_versions() here leaving a blank line after the details tag]

[MarcoGorelli]

Does this mean that some of the existing tests need to change?

For example

    def test_unicode_print(self):
        c = Categorical(["aaaaa", "bb", "cccc"] * 20)
        expected = """\
[aaaaa, bb, cccc, aaaaa, bb, ..., bb, cccc, aaaaa, bb, cccc]
Length: 60
Categories (3, object): [aaaaa, bb, cccc]"""

        assert repr(c) == expected

should become

    def test_unicode_print(self):
        c = Categorical(["aaaaa", "bb", "cccc"] * 20)
        expected = """\
['aaaaa', 'bb', 'cccc', 'aaaaa', 'bb', ..., 'bb', 'cccc', 'aaaaa', 'bb', 'cccc']
Length: 60
Categories (3, object): ['aaaaa', 'bb', 'cccc']"""

        assert repr(c) == expected

[simonjayhawkins]

Does this mean that some of the existing tests need to change?

Maybe more discussion needed, but IMO the current representation of the string categories without quotes is a bug and not pythonic. However, it is also a breaking change. need to see what others think as I don't know the history.

[MarcoGorelli]

This isn't limited to Categorical though, is it? Should

>>> pd.DataFrame(['a', 'b', 2])
   0
0  a
1  b
2  2

become

>>> pd.DataFrame(['a', 'b', 2])
   0
0 'a'
1 'b'
2  2

?

[simonjayhawkins]

In the OP, the values are shown inside square brackets, so for me, this implies a list literal which I would expect could be copy and pasted. I do find it frustrating that the reprs of many pandas objects cannot be used to create an object, but that's another issue.

For the Series case, the values are not shown inside square brackets, so the strings shown without quotes is more acceptable.