Numpy astype

1. What is Astype NumPy?
2. How do you use Astype NumPy?
3. What is the difference between .dtypes and Astype () function?
4. Does Astype return copy?

What is Astype NumPy?

Practical Data Science using Python

We have a method called astype(data_type) to change the data type of a numpy array. If we have a numpy array of type float64, then we can change it to int32 by giving the data type to the astype() method of numpy array. We can check the type of numpy array using the dtype class.

How do you use Astype NumPy?

The astype() function creates a copy of the array, and allows you to specify the data type as a parameter. The data type can be specified using a string, like 'f' for float, 'i' for integer etc. or you can use the data type directly like float for float and int for integer.

What is the difference between .dtypes and Astype () function?

If the function accepts the dtype parameter then use it. If it doesn't accept that parameter you'll have to use the astype . The effect should be the same (in most cases). The function that accepts dtype might be using astype (or equivalent) in its return expression.

Does Astype return copy?

By default, astype always returns a newly allocated array. If this is set to false, and the dtype , order, and subok requirements are satisfied, the input array is returned instead of a copy.