Customer Data Clustering Analysis with Python (5-day deadline)

I'm seeking a data analyst proficient in Python for performing a clustering analysis (K-means machine learning) on customer data. Students are welcome to apply.

Task Requirements:
- Deadline: 4th November 2024 (Monday)
- The use of ChatGPT is allowed, as long as code is commented.
- Deliver .py files and visualization where applicable.

Tasks:
- Data Processing: You will manipulate and prepare the data for analysis.
- K-means Implementation: The analysis should utilize the K-means clustering algorithm.
- Basic Visualization: You should be able to provide simple visual representations of the clustering outcomes within Spyder.

Data Attributes (to-be-provided):
The data to be clustered encompasses various aspects of customer information, specifically:
- Demographic Information: Age, gender, income level, etc.
- Purchase History: Previous purchases, frequency, spending habits, etc.
- Website Interaction: Pages visited, time spent, click-through rates, etc.

Ideal Skills and Experience:
- Basic proficiency in Python, particularly with libraries such as pandas, NumPy, and sklearn.
- Basic experience with K-means clustering.
- Ability to visualize data using tools like Matplotlib or Seaborn.
- Using Spyder software.