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Showing content from https://github.com/pandas-dev/pandas/issues/14522 below:

Categorical.searchsorted() uses lexical order instead of the provided categorical order · Issue #14522 · pandas-dev/pandas · GitHub

Hi,
it seems that the searchsorted() method of Categorical series does not take into account the specific order of the categories.

x = pd.Categorical(
    ['cheese', 'apple', 'bread', 'bread',  'milk'],
    categories=['cheese', 'milk', 'apple', 'bread'],
    ordered=True)
print('Unsorted:', x)
x_sort = x.sort_values()
print('Sorted:', x_sort)
print('Searchsorted apple:', x_sort.searchsorted('apple'))
print('Searchsorted milk:', x_sort.searchsorted('milk'))

Unsorted: [cheese, apple, bread, bread, milk]
Categories (4, object): [cheese < milk < apple < bread]
Sorted: [cheese, milk, apple, bread, bread]
Categories (4, object): [cheese < milk < apple < bread]
Searchsorted apple: [0]
Searchsorted milk: [5]

As you can see, "apple" is inserted at the beginning (b/c it starts with an 'a') and "milk" is inserted at the end, even though the order of both categories is between "cheese" and "bread".
Unfortunately, the API documentation does not specify is this is the expected behavior, but it seems inconsistent with the fact that .sort_values() does use the categorical order.

commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-34-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.0
nose: None
pip: 8.1.2
setuptools: 25.1.6
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.0
statsmodels: 0.6.1
xarray: None
IPython: 5.0.0
sphinx: None
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: None
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: None
lxml: None
bs4: 4.5.1
html5lib: None
httplib2: 0.9.2
apiclient: 1.5.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None

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