numpy pandas not working in IDLE / work in Anaconda - numpy

Question

I am running Python 3.5.1 on Windows 10 and have Anaconda and IDLE installed.
If I run any Python files, pandas and numpy seem to work in Jupyter notebooks, but not in IDLE.
I have ensured that the PATH and PYTHONPATH environment variables include access to the folders where pandas and numpy are located (Lib/site-packages).
I receive the following error in IDLE when trying to import pandas:
Traceback (most recent call last):
File "<pyshell#1>", line 1, in <module>
import pandas
File "C:\Users\me\AppData\Local\Continuum\Anaconda3\Lib\site-packages\pandas\__init__.py", line 18, in <module>
raise ImportError("Missing required dependencies {0}".format(missing_dependencies))
ImportError: Missing required dependencies ['numpy']
When I try to import numpy I get the following error:
Traceback (most recent call last):
File "<pyshell#2>", line 1, in <module>
import numpy
File "C:\Users\me\AppData\Local\Continuum\Anaconda3\Lib\site-packages\numpy\__init__.py", line 180, in <module>
from . import add_newdocs
File "C:\Users\me\AppData\Local\Continuum\Anaconda3\Lib\site-packages\numpy\add_newdocs.py", line 13, in <module>
from numpy.lib import add_newdoc
File "C:\Users\me\AppData\Local\Continuum\Anaconda3\Lib\site-packages\numpy\lib\__init__.py", line 8, in <module>
from .type_check import *
File "C:\Users\me\AppData\Local\Continuum\Anaconda3\Lib\site-packages\numpy\lib\type_check.py", line 11, in <module>
import numpy.core.numeric as _nx
File "C:\Users\me\AppData\Local\Continuum\Anaconda3\Lib\site-packages\numpy\core\__init__.py", line 14, in <module>
from . import multiarray
ImportError: cannot import name 'multiarray'
Can someone help?

Answer 1

try this:
I had the same problem
https://stackoverflow.com/a/40637960/6376603
maybe the above answer will help.

Answer 2

I had similar problem. I uninstalled anaconda from my system completely.
Steps - Delete app, delete anaconda3 folder, empty trash
Then I reinstalled older version of it and it started working perfectly. Maybe it is some kind of bug in the newer version.