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.
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.
I load some machine learning data from a CSV file. The first 2 columns are observations and the remaining columns are features.
I want to get the intersecting (common) rows across two 2D numpy arrays. E.g., if the following arrays are passed as inputs:
If I have a numpy dtype, how do I automatically convert it to its closest python data type? For example,
After I learned how to use einsum, I am now trying to understand how np.tensordot works.
I have looked up this issue and most questions are for more complex replacements. However in my case I have a very simple dataframe as a test dummy.
Using Matplotlib, I want to plot a 2D heat map. My data is an n-by-n Numpy array, each with a value between 0 and 1. So for the (i, j) element of this array, I want to plot a square at the (i, j) coordinate in my heat map, whose color is proportional to the element’s value in the array.
This works (using Pandas 12 dev)
I find myself typing import numpy as np almost every single time I fire up the python interpreter. How do I set up the python or ipython interpreter so that numpy is automatically imported?
In Python or NumPy, what is the best way to find out the first occurrence of a subarray?