BUG: examples for pd.interval_range do not work

[topper-123]

Code Sample, a copy-pastable example if possible

In the doc string for interval_range there are 2 of the four example that deal with time. They both fail when run:

    >>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
                          end=pd.Timestamp('2017-01-04'))
    ValueError: start, end, freq need to be the same type

    >>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
                          periods=3, freq='MS')
    TypeError: unsupported operand type(s) for +: 'Timestamp' and 'str'

Both of these give errors when run.

Problem description

The examples given seem reasonable for a IntervalIndex (unless time intervals should be PeriodIndex). My guess is that some too-strict check has crept in somewhere along the coding process.

Expected Output

In both cases IntervalIndex objects.

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.3
pytest: 3.2.2
pip: 9.0.1
setuptools: 36.5.0
Cython: 0.25.2
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.5
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: 3.7.3
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

[jorisvandenbossche]

They seem already to work on master:

In [125]: pd.interval_range(start=pd.Timestamp('2017-01-01'),
     ...:                           end=pd.Timestamp('2017-01-04'))              
Out[125]: 
IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03], (2017-01-03, 2017-01-04]]
              closed='right',
              dtype='interval[datetime64[ns]]')

In [126]: pd.interval_range(start=pd.Timestamp('2017-01-01'),
     ...:                           periods=3, freq='MS')                      
Out[126]: 
IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01], (2017-03-01, 2017-04-01]]
              closed='right',
              dtype='interval[datetime64[ns]]')

In [129]: pd.__version__
Out[129]: '0.21.0.dev+510.g62e19b2'

Tests for this have been added recently in #17482 (not sure if they were fixed there as well, or already previously. But I can confirm that they fail in 0.20.3)

[topper-123]

Ok, thanks for checking.