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I am working on a machine learning task and trying to convert all strings in a set of data to floats using hash() to do this I need to iterate over all the elements of a numpy array whilst not knowing if it is a 2D 3D or 4D array and then change each element. Is there any way to do this without using nested loops?
You can try numpu.vectorize, already mentioned here
Note:
The vectorize function is provided primarily for convenience, not for performance. The implementation is essentially a for loop.here
arr = np.array([['aba', 'baa', 'bbb'],
['xxy', 'xyy', 'yyy']])
v_hash = np.vectorize(hash)
v_hash(arr)
array([[-1538054455328520296, -1528482088733019667, -7962229468338304433],
[ 5621962119614158870, 1918700875003591346, -3216770211373729154]])
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I was doing a project in python and I would like to create a global variable which must be a two-dimensional array, but the dimension must be assigned when the user enters it.
how can i declare it initially? and then resize it when I want?
thanks for your attention
You can declare two-dimensional array doing simply this:
a = [[]]
If you print it out, you're gonna get something like this: [[]] which is two-dimensional array. Then you can append to this array and get elements using a[y][x]
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I'm trying to do an iteration with Pandas or any built-in function to display multiple of 10 rows for example.
So e.g. there are 50 records and I want to display the multiple of 10 records which will be record ID 0,10,20,30,40,50.
Use iloc:
df.iloc[::10, :]
This method takes a row/column slice, both based on integer position. More details from documenation:
Purely integer-location based indexing for selection by position.
.iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array.
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I have some large matrices and vectors calculated in R. I want to transfer this data to Python (2.7) in order to do some further data analysis.
What is a recommended way to do this?
I am very familiar with R, but a beginner in Python.
Use write.csv(matrix, "~/filename.csv) in R and then in Python either (if you want to use pandas)
import pandas as pd
new_matrix = pd.read_csv("~/filename.csv")
or (if you want to use numpy)
import numpy as np
new_matrix = np.genfromtxt("~/filename.csv", delimiter = ",")
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I have three C++ matrices called myMatrix, myMatrix2 and canvas respectively using OpenCV. I'm pretty new to C++, so it's unclear to me what Range::all() does. I understand the second Range statement, and I'm wondering if Range::all() is equivalent to Range(0,myMatrix.rows)?
myMatrix.copyTo(canvas(Range::all(), Range(0, myMatrix2.cols)));
I'm thinking it should be something like:
canvas = np.copy(myMatrix[:][:myMatrix2.cols])
If I did understand properly, the numpy equivalent can be written as:
canvas = np.copy(myMatrix[:, :myMatrix2.shape[1]])
Assuming that both myMatrix and myMatrix2 exist. If canvas also exists in python beforehand, you can update it inplace (rather than creating a new copy) as:
canvas[:] = myMatrix[:, :myMatrix2.shape[1]]
The : is the equivalent to Range::all() while :myMatrix2.shape[1] is equivalent to Range(0, myMatrix2.cols).
You should first learn how to use numpy (it has a great manual) rather than trying to make something work blindly.
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I always use lists when coding but can never put into words when analyzing my own work. what is the definition of a list in detail?
It's a datatype that stores a bunch of stuff. The more general term is an 'array.'
In python, they are represented like so:
[1, 2, 3, 4, 'elem5', ['sub-list-item-1', 'sub-list-item-2'], {}]
One important aspect of lists is that they can contain any type of data, or mixed data types.
Python docs define a list thusly:
list
A built-in Python sequence. Despite its name it is more akin to
an array in other languages than to a linked list since access to
elements are O(1).
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