#-----------------------------------------------------------------------------
# Copyright (c) Anaconda, Inc., and Bokeh Contributors.
# All rights reserved.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#-----------------------------------------------------------------------------
''' A table of `Will Burtin's historical data`_ regarding antibiotic
efficacies.

License: `MIT license`_

Sourced from: https://bl.ocks.org/borgar/cd32f1d804951034b224

This module contains one pandas Dataframe: ``data``.

.. rubric:: ``data``

:bokeh-dataframe:`bokeh.sampledata.antibiotics.data`

.. bokeh-sampledata-xref:: antibiotics

.. _Will Burtin's historical data: https://medium.com/@harshdev_41068/burtins-legendary-data-on-antibiotics-9b32ecd5943f
'''

#-----------------------------------------------------------------------------
# Boilerplate
#-----------------------------------------------------------------------------
from __future__ import annotations

import logging # isort:skip
log = logging.getLogger(__name__)

#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------

# Standard library imports
from io import StringIO
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    import pandas as pd

#-----------------------------------------------------------------------------
# Globals and constants
#-----------------------------------------------------------------------------

__all__ = (
    'data',
)

CSV = """
bacteria,                        penicillin, streptomycin, neomycin, gram
Mycobacterium tuberculosis,      800,        5,            2,        negative
Salmonella schottmuelleri,       10,         0.8,          0.09,     negative
Proteus vulgaris,                3,          0.1,          0.1,      negative
Klebsiella pneumoniae,           850,        1.2,          1,        negative
Brucella abortus,                1,          2,            0.02,     negative
Pseudomonas aeruginosa,          850,        2,            0.4,      negative
Escherichia coli,                100,        0.4,          0.1,      negative
Salmonella (Eberthella) typhosa, 1,          0.4,          0.008,    negative
Aerobacter aerogenes,            870,        1,            1.6,      negative
Brucella antracis,               0.001,      0.01,         0.007,    positive
Streptococcus fecalis,           1,          1,            0.1,      positive
Staphylococcus aureus,           0.03,       0.03,         0.001,    positive
Staphylococcus albus,            0.007,      0.1,          0.001,    positive
Streptococcus hemolyticus,       0.001,      14,           10,       positive
Streptococcus viridans,          0.005,      10,           40,       positive
Diplococcus pneumoniae,          0.005,      11,           10,       positive
"""


#-----------------------------------------------------------------------------
# General API
#-----------------------------------------------------------------------------

#-----------------------------------------------------------------------------
# Dev API
#-----------------------------------------------------------------------------

#-----------------------------------------------------------------------------
# Private API
#-----------------------------------------------------------------------------

def _read_data() -> pd.DataFrame:
    '''

    '''
    import pandas as pd
    return pd.read_csv(StringIO(CSV), skiprows=1, skipinitialspace=True, engine='python')

#-----------------------------------------------------------------------------
# Code
#-----------------------------------------------------------------------------

data = _read_data()