Step 5: Distribution of ratings

Next, we want to understand the distribution of ratings. To learn more about the ratings, we will provide the output from the last code execution as a prompt:

[Prompt]

Below is the output:

• market_place unique values: [‘“US”’]
• market_place value counts: market_place “US” 100 Name: count, dtype: int64
• product_category unique values: [‘“Books”’]
• product_category value counts: product_category “Books” 100 Name: count, dtype: int64
• Sentiment_books unique values: [‘positive’ ‘negative’]
• Sentiment_books value counts: Sentiment_books positive 84 negative 16 Name: count, dtype: int64

[End of prompt]

You should receive a response similar to the response below:

[Prompt response]

Great! Now that we’ve explored the categorical variables, let’s move on to step 5: visualizing...