How to read a CSV file with missing values into a NumPy array?

Last update on December 21 2024 07:40:00 (UTC/GMT +8 hours)

NumPy: I/O Operations Exercise-5 with Solution

Write a NumPy program that reads a CSV file containing missing values into a NumPy array, handling the missing values appropriately.

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'

# Read the CSV file into a NumPy array, handling missing values as NaN
data_array = np.genfromtxt(csv_file_path, delimiter=',', dtype=float, filling_values=np.nan)

# Print the resulting NumPy array
print(data_array)

Output:

[[10. nan 95.]
 [11. nan 90.]
 [12. nan 85.]
 [13. nan 96.]
 [14. nan 95.]]

Explanation:

• Import NumPy Library: Import the NumPy library to handle arrays.
• Define CSV File Path: Specify the path to the CSV file containing the data with missing values.
• Read CSV File into NumPy Array: Use np.genfromtxt() to read the contents of the CSV file into a NumPy array. The delimiter parameter specifies the delimiter used in the CSV file, dtype=float ensures all data is treated as floating-point numbers, and filling_values=np.nan fills missing values with NaN.
• Print NumPy Array: Output the resulting NumPy array to verify the data read from the CSV file, with missing values appropriately handled.

Python-Numpy Code Editor: