- Python Dictionaries
- Comparison Operators in Python
- Logical Operators in Python
- Conditional Statements in Python
- For Loop in Python
- While Loop in Python
- How to loop over python dictionaries and Numpy arrays
- What is NumPy in Python
- ndarray - Methods and Data Type
- NumPy - Methods to Create Arrays
- Python NumPy - Numerical Operations on Arrays
- Python NumPy - Indexing and Slicing Arrays
ndarray - Methods and Data Type
Once you have created an array, you can check its various attributes using the inbuilt functions. Some of these are described below:
Returns the number of array dimensions.
>>> a array([[ 1., 2., 3.], [ 4., 5., 6.]]) >>> a.ndim 2 >>> x = np.array([1, 2, 3]) >>> x.ndim 1
Returns a tuple of array dimensions. It can also be used to "reshape" the array, as long as this would not require a change in the total number of elements.
>>> a.shape (2, 3) >>> x.shape (3,) >>> a.shape = (3,2) >>> a array([[ 1., 2.], [ 3., 4.], [ 5., 6.]])
Returns the number of elements in the array. This can also be calculated with
np.prod(a.shape), i.e., the product of the array’s dimensions.
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