This is a python coding project. The answer should include $3-4$ visualizations that were created by VS code.

Overview

As part of the product development team for the Apple Vision Pro, you have been provided with a dataset containing about $80-100$ customer reviews $($see feedback.db for the data$).$ Your task is to analyze this feedback to understand customer sentiments and identify specific aspects that customers like or dislike about the product. This detailed analysis will help the team make targeted improvements in future versions.

By performing sentiment analysis and extracting key themes, you'll categorize each review as positive, negative, or neutral and identify the specific features or aspects that are frequently mentioned. This will enable data$-$driven decisions to enhance the product based on real customer experiences.

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Project Objectives

Sentiment Categorization:

Perform sentiment analysis on the provided customer reviews using Python. Use OpenAI's API for analyzing the sentiment of each review individually.

Aspect Extraction:

Identify and extract specific aspects or features mentioned in each review. Determine what customers specifically like or dislike about the product.

Data Presentation:

Summarize your findings in a clear and concise manner. Use visualizations $($e$.$g$.,$ bar charts, word clouds$)$ to represent sentiment distribution and key aspects.

Insights and Recommendations:

Interpret the results to identify key areas of customer satisfaction and dissatisfaction. Provide actionable recommendations for product improvements based on specific aspects.

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Tips

A$)$ Sentiment analysis

a$.$ Set up API key

b$.$ Define a sentiment analysis function

c$.$ Apply function to each review individually using a for loop

B$)$ Aspect Extraction

a$.$ Define aspect extraction function

b$.$ Apply function to each review individually using a for loop

c$.$ Clean and process extracted aspects

d$.$ Tag aspects with sentiment

C$)$ Analyze and visualize the results

a$.$ Sentiment distribution

b$.$ Aspect frequency analysis

c$.$ Aspect sentiment analysis

d$.$ Identify positive aspects

e$.$ Identify negative aspects

f$.$ Provide recommendations for improvement

g$.$ Highlight strengths

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Expected Output $($deliverable$)$

Your submission should be in the form of a word doc or pdf$.$ Please present visuals of your data analysis $($charts$,$ graphs, tables, figures, etc.$).$ Provide some details about the recommendations you make for future versions of the product.