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NumPy: Extract all the rows from a given array where a specific column starts with a given character

Extract rows based on column starting character.

Write a NumPy program to extract all the rows from a given array where a specific column starts with a given character.

Sample array:
[['01' 'V' 'Debby Pramod']
['02' 'V' 'Artemiy Ellie']
['03' 'V' 'Baptist Kamal']
['04' 'V' 'Lavanya Davide']
['05' 'V' 'Fulton Antwan']
['06' 'V' 'Euanthe Sandeep']
['07' 'V' 'Endzela Sanda']
['08' 'V' 'Victoire Waman']
['09' 'V' 'Briar Nur']
['10' 'V' 'Rose Lykos']]

Sample Solution:

Python Code:

# Importing NumPy library
import numpy as np

# Setting printing options to display arrays with a maximum line width of 100
np.set_printoptions(linewidth=100)

# Creating a NumPy array containing student data
student =  np.array([
    ['01', 'V', 'Debby Pramod'],
    ['02', 'V', 'Artemiy Ellie'],
    ['03', 'V', 'Baptist Kamal'],
    ['04', 'V', 'Lavanya Davide'],
    ['05', 'V', 'Fulton Antwan'],
    ['06', 'V', 'Euanthe Sandeep'],
    ['07', 'V', 'Endzela Sanda'],
    ['08', 'V', 'Victoire Waman'],
    ['09', 'V', 'Briar Nur'],
    ['10', 'V', 'Rose Lykos']
])

# Displaying the original array
print("Original array:")
print(student)

# Searching for student names starting with a specific character ('E')
char = 'E'
result = student[np.char.startswith(student[:, 2], char)]
print("\nStudent name starting with", char, ":")
print(result)

# Searching for student IDs starting with a specific character ('1')
char = '1'
result = student[np.char.startswith(student[:, 0], char)]
print("\nStudent id starting with", char, ":")
print(result)

Sample Output:

Original array:
[['01' 'V' 'Debby Pramod']
 ['02' 'V' 'Artemiy Ellie']
 ['03' 'V' 'Baptist Kamal']
 ['04' 'V' 'Lavanya Davide']
 ['05' 'V' 'Fulton Antwan']
 ['06' 'V' 'Euanthe Sandeep']
 ['07' 'V' 'Endzela Sanda']
 ['08' 'V' 'Victoire Waman']
 ['09' 'V' 'Briar Nur']
 ['10' 'V' 'Rose Lykos']]

Student name starting with E :
[['06' 'V' 'Euanthe Sandeep']
 ['07' 'V' 'Endzela Sanda']]

Student id starting with 1 :
[['10' 'V' 'Rose Lykos']]

Python-Numpy Code Editor: