final_​exam

Exploratory Data Analysis (EDA)：

• Data Inventory: Successfully ingested raw dataset containing 10000 rows and 7 observations.

• Visual Verification: Initial profiling via Table View verified nconsistencies, spelling or formatting errors .

• Missing values : verified missing values.

• Outlier : Box Plot shows no significant outliers in price per unit and quantity.

Data cleaning：

• Integrity Enforcement: Applied Duplicate Row Filter to remove redundant records and ensure the uniqueness .

• Text Normalization:

  • Utilized String Cleaner to strip unnecessary space.

  • Used String Manipulation (Multi Column) to lower categories and maintain consistency across text-based fields.

• Temporal Formatting: Converted the Transaction Date column from string format to a standardized Date&Time format.

• Missing values: Applied Missing Value node, using mean imputation for Numbers and imputation fix value for strings

• New column: Add a new column named total price

• Correlation Verification: Validated the cleaned dataset through Linear Correlation and Heatmap nodes, confirming strong relationships between quantity, price per unit and total price.