String Transforms

The String transforms allow users to manipulate textual data, standardize formats, and enrich string columns for analysis or downstream processing.

Add Prefix

Adds a custom text prefix to each value in the selected column(s).

Best Situations to Use

• Standardize identifiers or codes with common prefixes.

• Add contextual labels to string columns for feature engineering.

Steps

1. Select a string column.

2. Open Transforms > String > Add Prefix.

3. Enable Output Column Prefix (optional) to create a new column.

4. Provide the Prefix Value.

5. Select one or multiple columns to apply.

6. Click Submit.

• A new column or the original column is updated with the prefix added.

Add Suffix

Adds a custom text suffix to each value in the selected column(s).

Best Situations to Use

• Append units, labels, or contextual text to string columns.

• Standardize string formatting for reporting or analysis.

Steps

1. Select a string column.

2. Open Transforms > String > Add Suffix.

3. Enable Create New Column (optional).

4. Provide the Suffix Value.

5. Select one or multiple columns to apply.

6. Click Submit.

• A new column or the original column is updated with the suffix added.

Change to Lowercase

Converts all values in a column to lowercase.

Best Situations to Use

• Standardize text for case-insensitive comparisons.

• Prepare data for text analytics, search, or deduplication.

Steps

1. Select a string column.

2. Open Transforms > String > Change to Lowercase.

3. Enable Create New Column (optional).

4. Click Submit.

• Values are transformed to lowercase in a new column or updated in-place.

Change to Title Case

Converts values so that the first letter of each word is capitalized.

Best Situations to Use

• Improve readability and formatting of string data.

• Standardize proper nouns or textual descriptions.

Steps

1. Select a string column.

2. Open Transforms > String > Change to Title Case.

3. Enable Create New Column (optional) and provide a name.

4. Click Submit.

• Values are converted to title case in a new column or updated in-place.

Change to Upper Case

Converts all values in a column to uppercase.

Best Situations to Use

• Standardize text for visual consistency or case-sensitive operations.

• Prepare data for integration with other systems requiring uppercase text.

Steps

1. Select a string column.

2. Open Transforms > String > Change to Upper Case.

3. Enable Create New Column (optional) and provide a name.

4. Click Submit.

• Values are converted to uppercase in a new column or updated in-place.

Note: If Create New Column is not enabled, the original column is modified.

Ends With

Checks if values in a column end with a specified string or pattern, returning a Boolean result.

Best Situations to Use

• Flag rows with specific suffixes or patterns in string columns.

• Prepare features for categorical analysis or text filtering.

Steps

1. Select a string column.

2. Open Transforms > String > Ends With.

3. Select Mode: REGEX or String.

4. Provide New Column Name (if creating a new column).

5. Enter the value or pattern.

6. Enable Ignore Case (optional).

7. Click Submit.

• New column with Boolean values (True if value ends with pattern, False otherwise).

Example: Pattern .*pire in REGEX mode → True for values ending with pire.

Extract Substring at Position

Extracts a substring from a string column based on a starting position and length.

Best Situations to Use

• Retrieve specific portions of text for analysis or feature engineering.

• Standardize or parse structured strings.

Steps

1. Select a string column.

2. Open Transforms > String > Extract Substring at Position.

3. Enable Create New Column (optional).

4. Provide New Column Name.

5. Specify Position (0-indexed start).

6. Specify Length of substring.

7. Click Submit.

• New column with extracted substring values.

Extract Substring before Delimiter

Extracts a substring from a string column before a specified delimiter occurrence.

Best Situations to Use

• Parse structured strings like CSV, IDs, or codes.

• Extract leading segments before separators.

Steps

1. Select a string column with delimiters.

2. Open Transforms > String > Extract Substring before Delimiter.

3. Enable Create New Column (optional).

4. Provide New Column Name.

5. Specify Delimiter.

6. Specify the Count of delimiter occurrences.

7. Click Submit.

• New column with extracted substring.

Get Domain

Extracts the domain portion of a URL from a string column.

Best Situations to Use

• Prepare URL data for analytics or aggregation by domain.

• Feature engineering for web log or traffic analysis.

Steps

1. Select a URL column.

2. Open Transforms > String > Get Domain.

3. Click Submit.

• New column with domain values.

Example: https://www.google.com → google.

Get Host

Extracts the host (including subdomains) from a URL column, excluding path and query parameters.

Best Situations to Use

• Analyze web traffic or sources by host.

• Separate subdomains for detailed URL-based analytics.

Steps

1. Select a URL column.

2. Open Transforms > String > Get Host.

3. Click Submit.

• New column with host values.

Example: https://www.google.com → www.google.com

Get Subdomain Name

Extracts the subdomain portion from a URL column.

Best Situations to Use

• Analyze subdomain-level traffic.

• Prepare features for web analytics or segmentation.

Steps

1. Select a URL column.

2. Open Transforms > String > Get Subdomain Name.

3. Click Submit.

• New column with subdomain values.

Example: https://www.google.com → www.

Insert Character

Inserts a custom character at specified positions in a string column. Can update the original column or create a new one.

Best Situations to Use

• Format codes, IDs, or textual values with prefixes, separators, or markers.

• Standardize data for integration or display purposes.

Steps

1. Select a string column.

2. Open Transforms > String > Insert Character.

3. Enable Create New Column (optional).

4. Provide New Column Name.

5. Specify Position(s) to insert the character (comma-separated for multiple positions).

6. Enter the Character to insert.

7. Click Submit.

• New or updated column with inserted characters at specified positions.

Example: Insert $ at position 0 → $value.

Negate Boolean Value

Flips the Boolean values in a column: True → False, False → True.

Best Situations to Use

• Correct or invert Boolean flags in datasets.

• Prepare features for conditional logic or ML models.

Steps

1. Select a Boolean column.

2. Open Transforms > String > Negate Boolean Value.

3. Click Submit.

• The original column is updated with inverted Boolean values.

Remove Accents

Removes accented characters from string columns, normalizing text.

Best Situations to Use

• Standardize multilingual text for comparison or matching.

• Prepare text for search, NLP, or downstream processing.

Steps

1. Select a string column.

2. Open Transforms > String > Remove Accents.

3. Enable Create New Column (optional).

4. Click Submit.

• Accented characters are removed; a new column is added if selected.

Remove Consecutive Characters

Removes repeated characters or whitespace from a column.

Best Situations to Use

• Normalize text with duplicate characters or spaces.

• Prepare data for clean textual analysis.

Steps

1. Select a column.

2. Open Transforms > String > Remove Consecutive Characters.

3. Enable Create New Column (optional).

4. Configure:

   • Separator: Whitespace or Other

   • Custom Repeated Character (if Other is selected)

5. Click Submit.

• Column with consecutive duplicates removed, either as a new column or updated in-place.

Remove Part of Text

Removes a specific substring from a column based on a condition.

Best Situations to Use

• Delete unwanted patterns or prefixes/suffixes.

• Standardize text before analysis.

Steps

1. Select a column.

2. Open Transforms > String > Remove Part of Text.

3. Enable Create New Column (optional).

4. Specify:

   • Operator: contains, equals, starts with, ends with, regex

   • Value: Text or pattern to remove

5. Click Submit.

• Matching text is removed; a new column is added if selected.

Remove Trailing and Leading Characters

Removes leading and trailing characters, including spaces or custom padding characters.

Best Situations to Use

• Clean text with extraneous padding.

• Standardize identifiers or codes for processing.

Steps

1. Select a column.

2. Open Transforms > String > Remove Trailing and Leading Characters.

3. Enable Create New Column (optional).

4. Configure:

   • Padding Character: Space or Other

   • Custom Character (if Other selected)

   • Ignore Case (optional)

5. Click Submit.

• Column with leading/trailing characters removed, new column added if selected.

Search & Replace

Searches for a value or pattern in a column and replaces it with another value.

Best Situations to Use

• Correct inconsistent text entries.

• Standardize strings before analysis or aggregation.

Steps

1. Select a column.

2. Open Transforms > String > Search & Replace.

3. Enable Create New Column (optional).

4. Configure:

   • Operator: contains, equals, starts with, ends with, regex

   • Value: Text to search

   • Replace With: Text to replace

   • Overwrite Entire Cell (optional)

5. Click Submit.

• Column values are replaced based on configuration.

Split String

Splits a column into multiple columns based on a delimiter or specific position.

Best Situations to Use

• Separate structured text like codes, CSVs, or compound identifiers.

• Extract multiple components from a single column.

Steps

1. Select a column.

2. Open Transforms > String > Split String.

3. Configure:

   • Use With: Delimiter or Position

   • Delimiter: Character to split on (if selected)

   • Position: Character position to split (if selected)

4. Click Submit.

• New columns are created for each split segment.

Starts With

Checks if values in a column start with a specified string or pattern, returning a Boolean result.

Best Situations to Use

• Flag rows with specific prefixes or patterns.

• Prepare features for categorical analysis or filtering.

Steps

1. Select a string column.

2. Open Transforms > String > Starts With.

3. Enable Create New Column (optional).

4. Configure:

   • Mode: REGEX or String

   • Value: Text or pattern to check

   • Ignore Case (optional)

5. Click Submit.

• New column with Boolean values: True if the value starts with the pattern, False otherwise.