Code optimization (sorting a large array)

Python Help
1

0
Hi,
I have a large pandas dataframe, I need to sort each row in a loop, the sort should reflect on the heading. The code is fine but it is really slow. I tried to convert pandas to NumPy 2d array, it gets a little improvement but still slow.

In my code, I have NumPy matrix, and I select one row each time and sort it with the first row. I used argsort. Is there any way to speedup the code, any suggestion?

Thanks

2

I may have found a faster way,The same data took only 0.78 seconds using the GPU.

import numpy as np
import torch
import time

n = np.random.random((100000000, 2))


def func_numpy():
    global n
    start = time.perf_counter()
    n.argsort()
    end = time.perf_counter()
    print("{:.2f} second".format(end - start))


def func_torch():
    global n
    t = torch.tensor(n)
    start = time.perf_counter()
    t.sort()
    end = time.perf_counter()
    print("{:.2f} second".format(end - start))


def func_torch_gpu():
    global n
    t = torch.tensor(n).cuda()
    start = time.perf_counter()
    t.sort()
    end = time.perf_counter()
    print("{:.2f} second".format(end - start))


func_numpy()  # 1.60 second
func_torch()  # 1.22 second
func_torch_gpu()  # 0.78 second