Array Creation: NumPy provides functions for creating arrays of various shapes and dimensions. Some of the most commonly used functions are:
np.array():
np.zeros():
np.ones():
np.empty():
np.arange():
np.linspace():
np.eye():
np.random.rand():
np.random.randn():
np.random.randint():
np.random.shuffle():
Mathematical Functions: NumPy provides a wide range of mathematical functions for performing operations on arrays. Some of the most commonly used functions are: np.add(): np.subtract(): np.multiply(): np.divide(): np.exp(): np.log(): np.sqrt(): np.power():
Array Manipulation: NumPy provides functions for manipulating arrays in various ways. Some of the most commonly used functions are: np.reshape(): np.concatenate(): np.split(): np.transpose(): np.flatten(): np.sort():
Linear Algebra Functions: NumPy provides functions for performing linear algebra operations on arrays. Some of the most commonly used functions are:
np.dot():
np.linalg.inv():
np.linalg.det():
np.linalg.eig():
Statistical Functions: NumPy provides various statistical functions for analyzing data. Some of the most commonly used functions are:
np.mean():
np.median():
np.std():
np.var():
np.corrcoef():
EDA with Numpy