Using Python files to input arrays can use the numpy.loadtxt() function. The specific steps are as follows: Import the NumPy library and open the file. Use the loadtxt() function to read the file, specifying the data delimiter. For example, suppose there are comma-separated data 1,2,3,4,5,6,7,8,9 in my_data.txt, which can be read using the following code: import numpy as np with open('my_data.txt', 'r') as f: data = np.loadtxt(f, delimiter=',')
##How to use Python file input array
In Python, you can use thenumpy.loadtxt() function to read data from a file and convert it into an array.
Steps:
- Import NumPy library:
import numpy as np
- Open File:
with open('my_data.txt', 'r') as f: # 这里输入文件路径和读取模式('r')
- Use the loadtxt()
function to read the file:
data = np.loadtxt(f, delimiter=',')
- delimiter
The parameter specifies the delimiter of the data (default is space).
Example:
Suppose you have a text file namedmy_data.txt that contains the following data (separated by commas ):
<code>1,2,3 4,5,6 7,8,9</code>To read this data into a NumPy array, you can use the following code:
import numpy as np with open('my_data.txt', 'r') as f: data = np.loadtxt(f, delimiter=',') print(data)Output:
<code>[[1. 2. 3.] [4. 5. 6.] [7. 8. 9.]]</code>
Note:
- If the data contains a header row, you can skip it using the
- skiprows
parameter.
You can also use the - dtype
parameter to specify the type of data (default is float).
If you want to read the data in binary format, you can use the - np.load()
function.
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