Why does indexing numpy arrays with brackets and commas differ in behavior?
I tend to index numpy arrays (matrices) with brackets, but I’ve noticed when I want to slice an array (matrix) I must use the comma notation. Why is this? For example,
slice
Python slice how-to, I know the Python slice but how can I use built-in slice object for it?
What’s the use of built-in function slice and how can I use it?
The direct way of Pythonic slicing I know – l1[start:stop:step]. I want to know if I have a slice object, then how do I use it?
Extract elements of list at odd positions
So I want to create a list which is a sublist of some existing list.
Slicing of a NumPy 2d array, or how do I extract an mxm submatrix from an nxn array (n>m)?
I want to slice a NumPy nxn array. I want to extract an arbitrary selection of m rows and columns of that array (i.e. without any pattern in the numbers of rows/columns), making it a new, mxm array. For this example let us say the array is 4×4 and I want to extract a 2×2 array from it.
Slicing a list into n nearly-equal-length partitions
I’m looking for a fast, clean, pythonic way to divide a list into exactly n nearly-equal partitions. partition([1,2,3,4,5],5)->[[1],[2],[3],[4],[5]] partition([1,2,3,4,5],2)->[[1,2],[3,4,5]] (or [[1,2,3],[4,5]]) partition([1,2,3,4,5],3)->[[1,2],[3,4],[5]] (there are other ways to slice this one too) There are several answers in here Iteration over list slices that run very close to what I want, except they are focused on the … Read more
How to query MultiIndex index columns values in pandas
Code example:
Wrapping around a list as a slice operation
Consider the following simple python code
What are the default slice indices *really*?
From the python documentation docs.python.org/tutorial/introduction.html#strings:
Selecting Random Windows from Multidimensional Numpy Array Rows
I have a large array where each row is a time series and thus needs to stay in order.