indices

This is somewhat related to a question I asked not too long ago today. I am taking the intersection of two lists as follows: inter = set(NNSRCfile['datetimenew']).intersection(catdate) The two components that I am taking the intersection of belong to two lengthy lists. Is it possible to get the indices of the intersected values? (The indices of the original lists that is). I'm not quite sure where to start with this one. Any help is greatly appreciated! I would create a dictionary to hold the original indices: ind_dict = dict((k,i) for i,k in enumerate(NNSRCfile['datetimenew'])) Now, build

I facing the issue that I need only a subset of a my original dataframe that is distributed over different rows and columns. E.g.: # My Original dataframe import pandas as pd dfTest = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]]) Output: 0 1 2 0 1 2 3 1 4 5 6 2 7 8 9 I can provide a list with rows and column indices where my desired values are located: array_indices = [[0,2],[1,0],[2,1]] My desired output is a series: 3 4 8 Can anyone help? Use pd.DataFrame.lookup dfTest.lookup(*zip(*array_indices)) array([3, 4, 8]) Which you can wrap in a pd.Series constructor pd.Series(dfTest.lookup(*zip(*array

If I print a matrix, it is shown with row and column indices in the console. E.g. > print(diag(3)) [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0 0 1 How can I suppress the column and row indices? I.e. something like this: > print(diag(3), indices=FALSE) 1 0 0 0 1 0 0 0 1 I can see that the cwhmisc package should contain a printM function to do this according to the documentation but it is not there when I load cwhmisc. Also, this seems like something you should be able to to in base R. user1981275 The function prmatrix in the base package could work for this, it can take the arguments collab and

I want to find a fast way (without for loop) in Python to assign reoccuring indices of an array. This is the desired result using a for loop: import numpy as np a=np.arange(9, dtype=np.float64).reshape((3,3)) # The array indices: [2,3,4] are identical. Px = np.uint64(np.array([0,1,1,1,2])) Py = np.uint64(np.array([0,0,0,0,0])) # The array to be added at the array indices (may also contain random numbers). x = np.array([.1,.1,.1,.1,.1]) for m in np.arange(len(x)): a[Px[m]][Py[m]] += x print a %[[ 0.1 1. 2.] %[ 3.3 4. 5.] %[ 6.1 7. 8.]] When I try to add x to a at the indices Px,Py I obviously

array = some kind of list with 3 columns and unlimited amount of rows with data inside of it. Volume = array[0][2] counter = 0 for i in array: if Volume == array[i][2]: #<------ why is this line a problem? counter += 1 This is a classic mistake. i in your case is already an element from array (i.e. another list), not an index of array ( not an int ), so if Volume == i[2]: counter += 1 Please, make sure to go at least through the beginning of Python tutorial , because this is very simple and fundamental stuff. Also I would advise to stick to naming conventions: variables are normally lower-case

For two lists a and b, how can I get the indices of values that appear in both? For example, a = [1, 2, 3, 4, 5] b = [9, 7, 6, 5, 1, 0] return_indices_of_a(a, b) would return [0,4] , with (a[0],a[4]) = (1,5) . The best way to do this would be to make b a set since you are only checking for membership inside it. >>> a = [1, 2, 3, 4, 5] >>> b = set([9, 7, 6, 5, 1, 0]) >>> [i for i, item in enumerate(a) if item in b] [0, 4] def return_indices_of_a(a, b): b_set = set(b) return [i for i, v in enumerate(a) if v in b_set] For larger lists this may be of help: for item in a: index.append(bisect.bisect