How to read data from a CSV file into a structured NumPy array?
NumPy: I/O Operations Exercise-3 with Solution
Write a NumPy program that reads data from a CSV file into a structured NumPy array with specified data types for each column.
Content of data.csv ------------------------- 1,Jorah Liina,95.5 2,Basil Aisha,90.0 3,Helga Myrthe,80.0 4,Lehi Piero,91.5
Sample Solution:
Python Code:
import numpy as np
# Define the path to the CSV file
csv_file_path = 'data.csv'
# Define the data types for each column
dtype = [('ID', 'i4'), ('Name', 'U10'), ('Score', 'f4')]
# Read the CSV file into a structured NumPy array
structured_array = np.genfromtxt(csv_file_path, delimiter=',', dtype=dtype, names=True)
# Print the structured NumPy array
print(structured_array)
Output:
[(11, 'Zayden Jer', 90.) (12, 'Luna Marci', 85.) (13, 'Kord Shane', 96.) (14, 'Coeus Zora', 95.)]
Explanation:
- Import the NumPy Library: Import the NumPy library to handle arrays.
- Define CSV File Path: Specify the path to the CSV file containing the data.
- Define Data Types: Define a list of tuples, where each tuple specifies the name and data type of a column. For example, 'i4' for a 4-byte integer, 'U10' for a Unicode string of length 10, and 'f4' for a 4-byte float.
- Read CSV File into Structured Array: Use np.genfromtxt() to read the contents of the CSV file into a structured NumPy array, specifying the delimiter and the data types. The names=True parameter indicates that the first row of the CSV file contains column names.
- Finally print the structured array.
Python-Numpy Code Editor: