Issue 1:
Code Sample, a copy-pastable example if possible

import pandas as pd
pd.qcut(pd.Series([True, False, False, False, False, False, True]), 6, duplicates="drop", precision=2)

Problem description

Pandas throws a TypeError:

Traceback (most recent call last):
File "/tmp/pandas/env/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 52, in _wrapfunc
return getattr(obj, method)(*args, **kwds)
TypeError: Cannot cast ufunc multiply output from dtype('float64') to dtype('bool') with casting rule 'same_kind'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 210, in qcut
dtype=dtype, duplicates=duplicates)
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 254, in _bins_to_cuts
dtype=dtype)
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 351, in _format_labels
precision = _infer_precision(precision, bins)
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 429, in _infer_precision
levels = [_round_frac(b, precision) for b in bins]
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 429, in <listcomp>
levels = [_round_frac(b, precision) for b in bins]
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 422, in _round_frac
return np.around(x, digits)
File "/tmp/pandas/env/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 2837, in around
return _wrapfunc(a, 'round', decimals=decimals, out=out)
File "/tmp/pandas/env/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 62, in _wrapfunc
return _wrapit(obj, method, *args, **kwds)
File "/tmp/pandas/env/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 42, in _wrapit
result = getattr(asarray(obj), method)(*args, **kwds)
TypeError: Cannot cast ufunc multiply output from dtype('float64') to dtype('bool') with casting rule 'same_kind'

If the second parameter for qcut is changed from 6 to 7, a different TypeError is raised:

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/tmp/pandas/env/src/pandas/pandas/core/reshape/tile.py", line 207, in qcut
bins = algos.quantile(x, quantiles)
File "/tmp/pandas/env/src/pandas/pandas/core/algorithms.py", line 903, in quantile
return algos.arrmap_float64(q, _get_score)
File "pandas/_libs/algos_common_helper.pxi", line 416, in pandas._libs.algos.arrmap_float64
File "/tmp/pandas/env/src/pandas/pandas/core/algorithms.py", line 888, in _get_score
idx % 1)
File "/tmp/pandas/env/src/pandas/pandas/core/algorithms.py", line 876, in _interpolate
return a + (b - a) * fraction
TypeError: numpy boolean subtract, the `-` operator, is deprecated, use the bitwise_xor, the `^` operator, or the logical_xor function instead.

Expected Output

Something like

0 (0.29, 1.0]
1 (-0.01, 0.29]
2 (-0.01, 0.29]
3 (-0.01, 0.29]
4 (-0.01, 0.29]
5 (-0.01, 0.29]
6 (0.29, 1.0]
dtype: category
Categories (2, interval[float64]): [(-0.01, 0.29] < (0.29, 1.0]]

Output of pd.show_versions()

Using Pandas 0.23.0.dev0+516.g74e6c78, also reproducable with 0.22.0. In Pandas 0.20.3, the first TypeError is also reproducable, but the second command (with 7 instead of 6) works.

INSTALLED VERSIONS

commit: None

python: 3.5.2.final.0

python-bits: 64

OS: Linux

OS-release: 4.13.0-36-generic

machine: x86_64

processor: x86_64

byteorder: little

LC_ALL: None

LANG: de_DE.UTF-8

LOCALE: de_DE.UTF-8

pandas: 0.23.0.dev0+516.g74e6c78

pytest: None

pip: 9.0.1

setuptools: 38.5.2

Cython: 0.27.3

numpy: 1.14.1

scipy: None

pyarrow: None

xarray: None

IPython: None

sphinx: None

patsy: None

dateutil: 2.7.0

pytz: 2018.3

blosc: None

bottleneck: None

tables: None

numexpr: None

feather: None

matplotlib: None

openpyxl: None

xlrd: None

xlwt: None

xlsxwriter: None

lxml: None

bs4: None

html5lib: None

sqlalchemy: None

pymysql: None

psycopg2: None

jinja2: None

s3fs: None

fastparquet: None

pandas_gbq: None

pandas_datareader: None

Issue 2:
skipfooter : "This line here says I am the right choice."

skip_footer : "This line here says I am the right choice."

Whatever the case is, something should certainly be done to avoid having duplicate arguments for the same thing, as can be seen here