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Sanskar
Keen Learner and Exp... • 2d
Day 6 of learning Data Science as a beginner. Topic: creating NumPy arrays NumPy arrays can be created using various ways one of them is using python list and converting it into a numpy array however this is a long way here you first create a python list and then use np(short form of numpy).array to convert that list into a numpy array this increases the unnecessary code lines and is also not very efficient. Some other way of creating a numpy array directly are: 1. np.zeros(): this will create an array full of zeros 2. np.ones(): this will create an array full of ones 3. np.full(): here you have to input the shape of the array and what integer you want to fill it with 4. np.eye(): this will create a matrix full of ones in main diagonal (aka identity matrix) 5. np.arange(): this works just like python's range function in for loop 6. np.linspace(): this creates an evenly spaced array you can also find the shape, size, datatype and dimension of arrays using .shape .size .dtype and .ndim functions of numpy. You can even reshape the array using .reshape function and can also change its datatype using .astype function. Numpy also offers a .flatten function which converts a 2D array to 1D. In short NumPy offers some really flexible options to create arrays effectively. Also here's my code and its result.
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