Interpolate NaN values in a numpy array
Is there a quick way of replacing all NaN values in a numpy array with (say) the linearly interpolated values?
numpy
Installing scipy in Python 3.5 on 32-bit Windows 7 Machine
I have been trying to install Scipy onto my Python 3.5 (32-bit) install on my Windows 7 machine using the pre-built binaries from:
http://www.lfd.uci.edu/~gohlke/pythonlibs
Numpy: Get random set of rows from 2D array
I have a very large 2D array which looks something like this:
Numpy ‘smart’ symmetric matrix
Is there a smart and space-efficient symmetric matrix in numpy which automatically (and transparently) fills the position at [j][i] when [i][j] is written to?
how to convert an RGB image to numpy array?
I have an RGB image. I want to convert it to numpy array. I did the following
Getting the indices of several elements in a NumPy array at once
Is there any way to get the indices of several elements in a NumPy array at once?
Cython: “fatal error: numpy/arrayobject.h: No such file or directory”
I’m trying to speed up the answer here using Cython. I try to compile the code (after doing the cygwinccompiler.py hack explained here), but get a fatal error: numpy/arrayobject.h: No such file or directory...compilation terminated error. Can anyone tell me if it’s a problem with my code, or some esoteric subtlety with Cython?
SQL-like window functions in PANDAS: Row Numbering in Python Pandas Dataframe
I come from a sql background and I use the following data processing step frequently:
How do I calculate percentiles with python/numpy?
Is there a convenient way to calculate percentiles for a sequence or single-dimensional numpy array?
numpy max vs amax vs maximum
numpy has three different functions which seem like they can be used for the same things — except that numpy.maximum can only be used element-wise, while numpy.max and numpy.amax can be used on particular axes, or all elements. Why is there more than just numpy.max? Is there some subtlety to this in performance?