How to access the ith column of a NumPy multidimensional array?
Suppose I have:
arrays
Store different datatypes in one NumPy array?
I have two different arrays, one with strings and another with ints. I want to concatenate them, into one array where each column has the original datatype. My current solution for doing this (see below) converts the entire array into dtype = string, which seems very memory inefficient.
Replace all elements of Python NumPy Array that are greater than some value
I have a 2D NumPy array and would like to replace all values in it greater than or equal to a threshold T with 255.0. To my knowledge, the most fundamental way would be:
numpy: most efficient frequency counts for unique values in an array
In numpy / scipy, is there an efficient way to get frequency counts for unique values in an array?
Performance of Pandas apply vs np.vectorize to create new column from existing columns
I am using Pandas dataframes and want to create a new column as a function of existing columns. I have not seen a good discussion of the speed difference between df.apply() and np.vectorize(), so I thought I would ask here.
Computing the correlation coefficient between two multi-dimensional arrays
I have two arrays that have the shapes N X T and M X T. I’d like to compute the correlation coefficient across T between every possible pair of rows n and m (from N and M, respectively).
Finding indices of matches of one array in another array
I have two numpy arrays, A and B. A conatains unique values and B is a sub-array of A.
Now I am looking for a way to get the index of B’s values within A.
Python/NumPy first occurrence of subarray
In Python or NumPy, what is the best way to find out the first occurrence of a subarray?
Numpy array assignment with copy
For example, if we have a numpy array A, and we want a numpy array B with the same elements.
What is the difference between contiguous and non-contiguous arrays?
In the numpy manual about the reshape() function, it says