i have python file i want to solve the exercise

Exercise $1$

Your task is to implement the function that generates a dictionary, recording the frequency with which each word in the dataset appears as spam $(1)$ or ham

$(0).$

In $[1]$:

import numpy as $np$

def get$\_$word$\_$frequency $(x,Y)$:

"I"!

Calculate the frequency of each word in a set of emails categorized as spam $(1)$ or not spam $(0).$

Parameters:

X $($numpy$.$array$)$: Array of emails, where each email is represented as a list of words.

Y $($numpy$.$array$)$: Array of labels corresponding to each email in X$.1$ indicates spam, $0$ indicates ham.

Returns:

word$\_$dict $($dict$)$: A dictionary where keys are unique words found in the emails, and values

are dictionaries containing the frequency of each word for spam $(1)$ and not spam $(0)$ emails.

$"\text{'}"!$

# Creates an empty dichar lab

word$\_$dict $=\{\}$

### START CODE HERE ###

### END CODE HERE ###

return word$\_$dict

# Example usage:

# Assuming we have numpy arrays $x$ and $Y$ with the email data and corresponding labels:

# $x=$ np$.$array$([...])$ # Replace with actual email text data split into words

# $Y=$ np$.$array $[[dots])$ # Replace with actual labels $(0$ or $1)$

# word$\_$freq$\_$dict $=$ get$\_$word$\_$frequency $(x,Y)$

# print$($word$\_$freq$\_$dict$)$

In $[2]$: test$\_$output $=$ get$\_$word$\_$frequency$([\text{'}$like$\text{'},$'going','river'$],[\text{'}$love$\text{'},$ 'deep', 'river'$],[\text{'}$hate$\text{'},$ 'river'$]],[1,0,0])$

print$($test$\_$output$)$