In this project, I analyzed a credit card spending habits dataset containing information on City, Date, Card Type, Expense Type, Gender, and Amount. I performed exploratory data analysis to gain insights into spending patterns and identify trends.
The dataset contains records of credit card transactions, including the amount spent and the date of the transaction, categorized by city, card type, expense type, and gender.
I conducted a thorough exploratory data analysis, including data cleaning, transformation, and visualization techniques. I used Python libraries such as Pandas, Matplotlib, and Seaborn to visualize and analyze the data.
The analysis provides insights into spending patterns across different categories such as city, card type, and expense type. The results can be useful for businesses and individuals looking to optimize their spending habits.
This project showcases my skills in data analysis and visualization, providing actionable insights into credit card spending habits. The code and methodology used can be easily replicated and applied to other datasets to gain insights into various financial trends.
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