Issue 1:
Reproducing code example:

python -c 'import numpy as np; np.test()'

Error message:

======================================================= FAILURES =======================================================__________________________________________ TestLinspace.test_denormal_numbers __________________________________________
self = <numpy.core.tests.test_function_base.TestLinspace object at 0x7f70ac7be2e8>

def test_denormal_numbers(self):
# Regression test for gh-5437. Will probably fail when compiled
# with ICC, which flushes denormals to zero
for ftype in sctypes['float']:
stop = nextafter(ftype(0), ftype(1)) * 5 # A denormal number
> assert_(any(linspace(0, stop, 10, endpoint=False, dtype=ftype)))
E AssertionError

ftype = <class 'numpy.float128'>
self = <numpy.core.tests.test_function_base.TestLinspace object at 0x7f70ac7be2e8>
stop = 0.0

/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_function_base.py:308: AssertionError
_____________________________________ TestFloatExceptions.test_floating_exceptions _____________________________________
self = <numpy.core.tests.test_numeric.TestFloatExceptions object at 0x7f70acbb4550>

def test_floating_exceptions(self):
# Test basic arithmetic function errors
with np.errstate(all='raise'):
# Test for all real and complex float types
for typecode in np.typecodes['AllFloat']:
ftype = np.obj2sctype(typecode)
if np.dtype(ftype).kind == 'f':
# Get some extreme values for the type
fi = np.finfo(ftype)
ft_tiny = fi.tiny
ft_max = fi.max
ft_eps = fi.eps
underflow = 'underflow'
divbyzero = 'divide by zero'
else:
# 'c', complex, corresponding real dtype
rtype = type(ftype(0).real)
fi = np.finfo(rtype)
ft_tiny = ftype(fi.tiny)
ft_max = ftype(fi.max)
ft_eps = ftype(fi.eps)
# The complex types raise different exceptions
underflow = ''
divbyzero = ''
overflow = 'overflow'
invalid = 'invalid'

self.assert_raises_fpe(underflow,
> lambda a, b: a/b, ft_tiny, ft_max)

divbyzero = 'divide by zero'
fi = finfo(resolution=1.0000000000000002641e-18, min=-inf, max=inf, dtype=float128)
ft_eps = 1.084202172485504434e-19
ft_max = inf
ft_tiny = 3.3621031431120935063e-4932
ftype = <class 'numpy.float128'>
invalid = 'invalid'
overflow = 'overflow'
self = <numpy.core.tests.test_numeric.TestFloatExceptions object at 0x7f70acbb4550>
typecode = 'g'
underflow = 'underflow'

/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_numeric.py:580:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <numpy.core.tests.test_numeric.TestFloatExceptions object at 0x7f70acbb4550>, fpeerr = 'underflow'
flop = <function TestFloatExceptions.test_floating_exceptions.<locals>.<lambda> at 0x7f70aca5a730>
x = 3.3621031431120935063e-4932, y = inf

def assert_raises_fpe(self, fpeerr, flop, x, y):
ftype = type(x)
try:
flop(x, y)
assert_(False,
> "Type %s did not raise fpe error '%s'." % (ftype, fpeerr))
E AssertionError: Type <class 'numpy.float128'> did not raise fpe error 'underflow'.

flop = <function TestFloatExceptions.test_floating_exceptions.<locals>.<lambda> at 0x7f70aca5a730>
fpeerr = 'underflow'
ftype = <class 'numpy.float128'>
self = <numpy.core.tests.test_numeric.TestFloatExceptions object at 0x7f70acbb4550>
x = 3.3621031431120935063e-4932
y = inf

/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_numeric.py:535: AssertionError
_______________________________ TestComplexFunctions.test_loss_of_precision_longcomplex ________________________________
self = <numpy.core.tests.test_umath.TestComplexFunctions object at 0x7f70ac0965c0>

@pytest.mark.skipif(is_longdouble_finfo_bogus(),
reason="Bogus long double finfo")
def test_loss_of_precision_longcomplex(self):
> self.check_loss_of_precision(np.longcomplex)

self = <numpy.core.tests.test_umath.TestComplexFunctions object at 0x7f70ac0965c0>

/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_umath.py:2642:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_umath.py:2592: in check_loss_of_precision
check(x_series, 50*eps)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

x = array([1.00000000e-20, 1.21736864e-20, 1.48198641e-20, 1.80412378e-20,
2.19628372e-20, 2.67368693e-20, 3.254862...5156e-04, 4.54267386e-04,
5.53010871e-04, 6.73218092e-04, 8.19554595e-04, 9.97700064e-04],
dtype=float128)
rtol = 5.42101086242752217e-18

def check(x, rtol):
x = x.astype(real_dtype)

z = x.astype(dtype)
d = np.absolute(np.arcsinh(x)/np.arcsinh(z).real - 1)
assert_(np.all(d < rtol), (np.argmax(d), x[np.argmax(d)], d.max(),
> 'arcsinh'))
E AssertionError: (190, 0.00016990298344866943845, 4.4408920985006261617e-16, 'arcsinh')

d = array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.000000...2302e-16, 0.00000000e+00,
3.33066907e-16, 0.00000000e+00, 2.22044605e-16, 1.11022302e-16],
dtype=float128)
dtype = <class 'numpy.complex256'>
real_dtype = dtype('float128')
rtol = 5.42101086242752217e-18
x = array([1.00000000e-20, 1.21736864e-20, 1.48198641e-20, 1.80412378e-20,
2.19628372e-20, 2.67368693e-20, 3.254862...5156e-04, 4.54267386e-04,
5.53010871e-04, 6.73218092e-04, 8.19554595e-04, 9.97700064e-04],
dtype=float128)
z = array([1.00000000e-20+0.j, 1.21736864e-20+0.j, 1.48198641e-20+0.j,
1.80412378e-20+0.j, 2.19628372e-20+0.j, 2.67...7386e-04+0.j, 5.53010871e-04+0.j, 6.73218092e-04+0.j,
8.19554595e-04+0.j, 9.97700064e-04+0.j], dtype=complex256)

/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_umath.py:2565: AssertionError
___________________________________________________ test_nextafter_0 ___________________________________________________
def test_nextafter_0():
for t, direction in itertools.product(np.sctypes['float'], (1, -1)):
tiny = np.finfo(t).tiny
> assert_(0. < direction * np.nextafter(t(0), t(direction)) < tiny)
E AssertionError

direction = 1
t = <class 'numpy.float128'>
tiny = 3.3621031431120935063e-4932

/usr/local/lib/python3.6/dist-packages/numpy-1.16.0.dev0+db5f9d3-py3.6-linux-x86_64.egg/numpy/core/tests/test_umath.py:2776: AssertionError
4 failed, 5040 passed, 409 skipped, 167 deselected, 12 xfailed, 1 xpassed in 137.51 seconds

### Numpy/Python version information:

<!-- Output from 'import sys, numpy; print(numpy.__version__, sys.version)' -->
1.16.0.dev0+db5f9d3 3.6.6

Issue 2:
I am on hackerrank, I installed anaconda before and numpy works fine on my spyder IDE but not on hackerrank. My os is windows 10 and I don't have multiple versions of python installed.

Reproducing code example:

import numpy

import numpy as np
<< your code here >>

Error message:

Numpy/Python version information: