In this tutorial, we will look at how to get the number of rows of a 2D array in Numpy with the help of some examples.
How to get the number of rows in Numpy?
You can use the Python built-in
len() function or the
numpy.ndarray.shape property to get the number of rows of a 2d Numpy array.
The following is the syntax –
# num rows using the len() function len(ar) # num rows using the .shape property ar.shape
Let’s now look at both the methods with the help of some examples –
First, we will create a 2d Numpy array that we will be using throughout this tutorial.
import numpy as np # create a 2d array ar = np.array([ [1, 2, 3, 4], [1, 1, 0, 0], [5, 6, 7, 8] ]) # display the array print(ar)
[[1 2 3 4] [1 1 0 0] [5 6 7 8]]
Here, we used the
numpy.array() function to create a 2d array with three rows and four columns.
Method 1 – Number of rows using the
len() is a Python built-in function that returns the length of an object. It is used on sequences or collections. If you apply the
len() function on a 2d Numpy array, it will return the number of rows in the array.
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# number of rows of array print(len(ar))
We get the number of rows in the above array as 3.
Method 2 – Number of rows using the
You can also get the number of rows in a 2d Numpy array by accessing its
.shape property which returns the tuple
(row_count, column_count). To only get the row count, access the value at the index 0 from the shape property.
# number of rows of array print(ar.shape)
We get the same result as above, 3.
In this tutorial, we looked at two methods to get the row count for a 2d array in Numpy.
- Use the Python built-in
- Via the
.shapeproperty of the array. (Value at the 0th index of the shape tuple is the row count)
You might also be interested in –
- Numpy – Create a Diagonal Matrix (With Examples)
- Get the First N Rows of a 2D Numpy Array
- Get the Last N Rows of a 2D Numpy Array
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