# How to compute Euclidean distance between two Pandas Series?

I was calculating Euclidean distance between two `series` objects in Python using a custom function which is attached below:

Since computing the Euclidean distance involves taking the square of the difference between corresponding elements of the two `series`, summing the squares, and then taking the square root of the result, I was able to create and understand this function. However, I think this is not an efficient way and that there are more faster and efficient methods of doing this, please provide such methods and techniques, I would highly appreciate it.

Hi @mubashir_rizvi! I would recommend that you follow this technique:

• In this technique, we use simple mathematical expressions where we first subtract the two series element-wise and then square the result.

• Then, we use Pandasâ€™ `sum()` function to sum the squares, and then get the square root of this result using `**0.5`.

I would recommend using the `euclidean_distances()` method provided by Scikit-Learn to calculate the Euclidean distance between two sequences or 2D arrays. It is important to note that this method requires the sequences to be enclosed in an additional set of square brackets, as it works with 2D arrays and sequences.