Filter

The Filter functionality in the Edilitics Transform module empowers users to seamlessly refine datasets without writing any code. This feature allows users to apply sophisticated filters based on the column's data type, ensuring precise and efficient data analysis. Below is a comprehensive guide on leveraging the Filter functionality, including detailed steps and practical use cases.

Step-by-Step Guide to Utilizing Filter#

1. Select Column to Filter#

• Choose the column you would like to filter from the dropdown list of column names provided.

2. Select Filter Type#

• Choose the appropriate filter type based on the selected column's data type. The available filter types will automatically adjust according to whether the column is categorical, datetime/timestamp, or numerical.
• Filter Types for Categorical Columns:
  • Equal to: Filters rows where the column value exactly matches the specified value. Use this to include only rows with a specific category.
  • Not equal to: Filters rows where the column value does not match the specified value. Use this to exclude rows with a specific category.
• Filter Types for Numerical and Datetime/Timestamp Columns:
  • Equal to: Filters rows where the column value exactly matches the specified value. Useful for pinpointing specific values or dates.
  • Greater than: Filters rows where the column value is greater than the specified value. Use this to include rows above a certain threshold.
  • Less than: Filters rows where the column value is less than the specified value. Use this to include rows below a certain threshold.
  • Not equal to: Filters rows where the column value does not match the specified value. Useful for excluding specific values or dates.
  • Greater than or equal to: Filters rows where the column value is greater than or equal to the specified value. Use this to include rows at or above a certain threshold.
  • Less than or equal to: Filters rows where the column value is less than or equal to the specified value. Use this to include rows at or below a certain threshold.

3. Enter or Select Filter Value(s)#

• For Categorical and Numerical Columns
  • Enter a constant by typing it into the value field, or
  • Select value(s) from the dropdown list, which displays all unique values for the column directly fetched from the table.
• For Datetime/Timestamp Columns
  • Select a date and time from the provided date and time selector.

Note: Users can select one or multiple values/constants to filter by for categorical and numerical columns. For datetime/timestamp columns, only a single date and time can be selected.

4. Submit#

• Submit the operation to apply the filter. Users can apply filters to multiple columns in the same operation and submit them collectively.

Real-World Applications of Filter#

Here are five real-world scenarios across various industries:

1. Retail Industry#

• Objective: Filter sales data to analyze transactions for a specific product category.
• Scenario:
  • Column: ProductCategory
  • Filter Type: Equal to
  • Filter Value: "Electronics"
  • Use Case: Analyze sales data for the electronics category to identify trends and performance.
  • Example: Filtering the sales data to include only transactions where the ProductCategory is "Electronics".

2. Healthcare Industry#

• Objective: Filter patient records to review recent admissions.
• Scenario:
  • Column: AdmissionDate
  • Filter Type: Greater than or equal to
  • Filter Value: "2023-01-01"
  • Use Case: Review patient admissions from the beginning of the year to date for capacity planning.
  • Example: Filtering the patient records to include only admissions from January 1, 2023, onwards.

3. Finance Industry#

• Objective: Filter transaction data to identify high-value transactions.
• Scenario:
  • Column: TransactionAmount
  • Filter Type: Greater than
  • Filter Value: 10000
  • Use Case: Identify and analyze transactions greater than $10,000 for compliance and auditing purposes.
  • Example: Filtering the transaction data to include only transactions where the TransactionAmount is greater than $10,000.

4. Manufacturing Industry#

• Objective: Filter production data to review batches completed within a specific timeframe.
• Scenario:
  • Column: BatchCompletionTimestamp
  • Filter Type: Less than
  • Filter Value: "2023-07-01 00:00:00"
  • Use Case: Review all production batches completed before July 1, 2023, for quality control analysis.
  • Example: Filtering the production data to include only batches completed before July 1, 2023.

5. Education Industry#

• Objective: Filter student performance data to focus on a specific grade range.
• Scenario:
  • Column: FinalGrade
  • Filter Type: Between (using Greater than or equal to and Less than or equal to)
  • Filter Values: 80 and 90
  • Use Case: Analyze the performance of students scoring between 80 and 90 for targeted interventions.
  • Example: Filtering the student performance data to include only students with final grades between 80 and 90.

The Filter functionality in Edilitics provides a powerful, user-friendly solution for refining datasets based on specific criteria. With dynamic filter types based on column data types and the ability to apply multiple filters in a single operation, users can efficiently hone their datasets. This feature enhances data analysis capabilities, making it both versatile and accessible for all users.