Mall Customer Analysis and Segmentation Using K-Means Algorithm
Hello everyone!
In this data science project, I am gonna try to analyze and cluster mall customer from Mall Customer Segmentation dataset (https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python).
Data Information:
- 200 rows
- 5 columns
Description:
- CustomerID: Customer ID
- Gender: Whether the customer is a male or a female (Male, Female)
- Age: Customer's age
- Annual Income (k$): Annual Income of the customee (in thousand dollars)
- Spending Score (1-100): Score assigned by the mall based on customer behavior and spending nature
To extract actionable insights from the dataset. I listed all the questions that came to mind below after assessing the dataset, and I tried to investigate all of them to find the insights:
- How is the distribution of each feature in the dataset?
- How is the correlation between features in the dataset?
- Can we cluster the customer using k-means algorithm?
In order to know the answer please check the notebook!