In Python, you can create dictionaries using the NumPy library by leveraging its array functionalities for numerical data and then converting them into a dictionary format. Here's a simple example of how to do that:
import numpy as np
# Create a NumPy array
keys = np.array(['a', 'b', 'c'])
values = np.array([1, 2, 3])
# Create a dictionary using the keys and values
my_dict = dict(zip(keys, values))
print(my_dict)
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?