You can import them like this: scipy.math.factorial and numpy.math.factorial seem to simply be aliases/references for/to math.factorial, that is scipy.math.factorial is math.factorial and numpy.math.factorial is math.factorial should both give True.
Just to offer the alternative to the Test-Path cmdlet (since nobody mentioned it): Does (almost) the same thing as except no support for wildcard characters
and I got a question when I run my Python code. I installed Python 2.7 on Windows 7, bit 64. I got an error “No module named serial” when I compiled my code: I tried many ways to crack this problem, such as installed Canopy to setup virtual environment, make sure ‘pip’ is there, no … Read more
Use random.choice(): For cryptographically secure random choices (e.g., for generating a passphrase from a wordlist), use secrets.choice(): secrets is new in Python 3.6. On older versions of Python you can use the random.SystemRandom class:
You can import the print() function from __future__ and use sep=’\t’, print() function was introduced in python 3, and it replaced the print statement used in python 2.x: help on print():
Edited for Pandas 0.22+ considering the deprecation of the use of dictionaries in a group by aggregation. We set up a very similar dictionary where we use the keys of the dictionary to specify our functions and the dictionary itself to rename the columns. option 1use agg ← link to docs option 2more for lessuse describe ← link to … Read more
I’m trying to run this program But I’m having a problem with numpy, I’m using pyschopy along with opencv. The problem I keep getting is this error report: RuntimeError: module compiled against API version 7 but this version of numpy is 6 Traceback (most recent call last): File “C:\Users\John\Documents\EyeTracking\Programs\GetImage.py”, line 1, in ImportError: numpy.core.multiarray failed … Read more
For a dataframe df, one can use any of the following: len(df.index) df.shape[0] df[df.columns[0]].count() (== number of non-NaN values in first column) Code to reproduce the plot:
The difference is that miniconda is just shipping the repository management system. So when you install it there is just the management system without packages. Whereas with Anaconda, it is like a distribution with some built in packages. Like with any Linux distribution, there are some releases which bundles lots of updates for the included … Read more
You can use py2exe as already answered and use Cython to convert your key .py files in .pyc, C compiled files, like .dll in Windows and .so on Linux. It is much harder to revert than common .pyo and .pyc files (and also gain in performance!).