添加Numpy数组不成功

Question

I am trying to iterate through a CSV file and create a numpy array for each row in the file, where the first column represents the x-coordinates and the second column represents the y-coordinates. I then am trying to append each array into a master array and return it.

import numpy as np 

thedoc = open("data.csv")
headers = thedoc.readline()


def generatingArray(thedoc):
    masterArray = np.array([])

    for numbers in thedoc: 
        editDocument = numbers.strip().split(",")
        x = editDocument[0]
        y = editDocument[1]
        createdArray = np.array((x, y))
        masterArray = np.append([createdArray])


    return masterArray


print(generatingArray(thedoc))

I am hoping to see an array with all the CSV info in it. Instead, I receive an error: "append() missing 1 required positional argument: 'values' Any help on where my error is and how to fix it is greatly appreciated!

Answer 1

Numpy arrays don't magically grow in the same way that python lists do. You need to allocate the space for the array in your "masterArray = np.array([])" function call before you add everything to it.

The best answer is to import directly to a numpy array using something like genfromtxt ( https://docs.scipy.org/doc/numpy-1.10.1/user/basics.io.genfromtxt.html ) but...

If you know the number of lines you're reading in, or you can get it using something like this.

file_length = len(open("data.csv").readlines())

Then you can preallocate the numpy array to do something like this:

masterArray = np.empty((file_length, 2))

for i, numbers in enumerate(thedoc): 
    editDocument = numbers.strip().split(",")
    x = editDocument[0]
    y = editDocument[1]
    masterArray[i] = [x, y]

I would recommend the first method but if you're lazy then you can always just build a python list and then make a numpy array.

masterArray = []

for numbers in thedoc: 
    editDocument = numbers.strip().split(",")
    x = editDocument[0]
    y = editDocument[1]
    createdArray = [x, y]
    masterArray.append(createdArray)

return np.array(masterArray)