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Concatenate 2D Arrays Vertically – Detailed Version #Python #HackerRank #NumPy #ArrayConcatenation

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In this problem, you are given two integer arrays representing two 2-D matrices that need to be concatenated vertically (along axis 0). The first line of input contains three space-separated integers:
X: the number of rows in the first array
Y: the number of rows in the second array
Z: the number of columns in both arrays
Following the first line, the next X lines provide the rows for the first array, and the subsequent Y lines provide the rows for the second array. Your task is to concatenate these arrays along the first axis (i.e., stack them vertically) so that the resulting array has (X + Y) rows and Z columns.
Step-by-Step Explanation:
Input Handling (#InputHandling, #DataProcessing):
Read the first line and split it to extract the integers X, Y, and Z. These represent the number of rows in the first array, the number of rows in the second array, and the number of columns for both arrays respectively.
For the next X lines, read each line, split the line into individual elements, convert them to integers, and store them as rows in the first array.
Similarly, for the following Y lines, read and process each line to form the second array.
Array Conversion (#NumPy, #ArrayConversion):
Concatenation (#ArrayConcatenation):
Output Formatting (#OutputFormatting):
Print the concatenated array. The output should exactly match the required format.
This detailed solution demonstrates how to use NumPy’s array manipulation functions to efficiently handle and concatenate multi-dimensional data. It is ideal for learning array operations in Python and preparing for coding challenges.
Code (Detailed Version):
import numpy as np
def solve():
# Read the dimensions: X = rows in first array, Y = rows in second array, Z = columns in both arrays
x, y, z = map(int, input().split())
# Read the first array of dimensions X x Z
# Read the second array of dimensions Y x Z
# Concatenate the two arrays along axis 0 (vertically)
# Print the resulting concatenated array
print(result)
if __name__ == '__main__':
solve()
X: the number of rows in the first array
Y: the number of rows in the second array
Z: the number of columns in both arrays
Following the first line, the next X lines provide the rows for the first array, and the subsequent Y lines provide the rows for the second array. Your task is to concatenate these arrays along the first axis (i.e., stack them vertically) so that the resulting array has (X + Y) rows and Z columns.
Step-by-Step Explanation:
Input Handling (#InputHandling, #DataProcessing):
Read the first line and split it to extract the integers X, Y, and Z. These represent the number of rows in the first array, the number of rows in the second array, and the number of columns for both arrays respectively.
For the next X lines, read each line, split the line into individual elements, convert them to integers, and store them as rows in the first array.
Similarly, for the following Y lines, read and process each line to form the second array.
Array Conversion (#NumPy, #ArrayConversion):
Concatenation (#ArrayConcatenation):
Output Formatting (#OutputFormatting):
Print the concatenated array. The output should exactly match the required format.
This detailed solution demonstrates how to use NumPy’s array manipulation functions to efficiently handle and concatenate multi-dimensional data. It is ideal for learning array operations in Python and preparing for coding challenges.
Code (Detailed Version):
import numpy as np
def solve():
# Read the dimensions: X = rows in first array, Y = rows in second array, Z = columns in both arrays
x, y, z = map(int, input().split())
# Read the first array of dimensions X x Z
# Read the second array of dimensions Y x Z
# Concatenate the two arrays along axis 0 (vertically)
# Print the resulting concatenated array
print(result)
if __name__ == '__main__':
solve()