Suppose I have two arrays (after import numpy as np),
suppose I have:
test = numpy.array([[1, 2], [3, 4], [5, 6]])
[1, 3, 5]
Suppose I have the following numpy array:
a = [[1, 5, 6],
[2, 4, 1],
[3, 1, 5]]
from numpy import *
def swap_columns(my_array, col1, col2):
temp = my_array[:,col1]
my_array[:,col1] = my_array[:,col2]
my_array[:,col2] = temp
swap_columns(data, 0, 1)
I have a NumPy array, i want to accumulate the values of one column, say the 2nd column.
a = np.array([[1,2],[2,4]])
# some kind of accumulate function that accumulates just one column:
I have a problem with lists/arrays/matrix at Python.
I have a list of matrix (or arrays if it need to be) and i want to add to every single of of them ...
I have a numpy structured array with a dtype such as:
A = numpy.empty(10, dtype=([('segment', '<i8'), ('material', '<i8'), ('rxN', '<i8')]))
A[A['segment'] == 42] = ...
I have a massive data array (500k rows) that looks like:
id value score
1 20 20
1 10 30
I just started to play with numpy/scipy a bit and I'm having trouble finding a feature in the documentation and I was wondering if you could help:
If I have an array ...
I have an array like this numpy array
dd =[[0.567 2 0.611]
[0.469 1 0.479]
[0.220 2 0.269]