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How to Create a Symmetric Array in Python: A Fun Logic Exercise

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 Here's a Python program that says to write a Symmetric array transformation. A top interview question. Symmetric Array Transformation Problem: Write a Python function that transforms a given array into a symmetric array by mirroring it around its center. For example: Input: [1, 2, 3] Output: [1, 2, 3, 2, 1] Hints: Use slicing for the reverse part. Concatenate the original array with its mirrored part. Example def symmetric_array(arr):     """     Transforms the input array into a symmetric array by mirroring it around its center.     Parameters:     arr (list): The input array.     Returns:     list: The symmetric array.     """     # Mirror the array by concatenating the original with its reverse (excluding the last element to avoid duplication)     return arr + arr[-2::-1] # Example usage input_array = [1, 2, 3] symmetric_result = symmetric_array(input_array) print("Input Array:", input_arr...
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Numpy Array Vs. List: What's the Difference

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Here are the differences between List and NumPy Array. Both store data, but technically these are not the same. You'll find here where they differ from each other.

Python Lists

Here is all about Python lists:

  • Lists can have data of different data types. For instance, data = [3, 3.2, 4.6, 6, 6.8, 9, “hello”, ‘a’]
  • Operations such as subtraction, multiplying, and division allow doing through loops
  • Storage space required is more, as each element is considered an object in Python
  • Execution time is high for large datasets
  • Lists are inbuilt data types


Array vs list


NumPy Arrays

Here is all about NumPy Arrays:
  • Numpy arrays are containers for storing only homogeneous data types. For example: data= [3.2, 4.6, 6.8]; data=[3, 6, 9]; data=[‘hello’, ‘a’]
  • Numpy is designed to do all mathematical operations in parallel and is also simpler than Python
  • Numpy storage space is very much less compared to the list due to the practice of homogeneous data type
  • Execution time is very less for large datasets
  • Numpy is a third-party library that needs to be installed by Conda or PIP


References

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