The as_string function converts various data types into a string format. This function is particularly useful when you need to ensure that data is in a consistent, readable format for display, concatenation, or further text-based operations.
Working with text data is a common task, but it can be challenging to find and select the necessary parts of data from the text. This is especially true when dealing with large datasets or unstructured text. Extracting specific information, such as email addresses, phone numbers, or dates, requires efficient and accurate methods.
Allows navigation and retrieval of specific data from JSON objects or arrays based on a specified path or query.
The regex_extract function takes an input string and a regular expression (regex) pattern and extracts all the substrings that match the pattern. It returns a list of these matching substrings. This function is useful for parsing text and extracting specific data based on patterns, such as extracting email addresses, phone numbers, dates, or any other patterns from a given text.
Returns TRUE if a column or expression contains the specified pattern.
The trim function removes leading and trailing whitespace and new line characters from a string. This is useful for cleaning and standardizing text data, ensuring there are no extra spaces or lines at the beginning or end of the strings.
The tasks related to dates usually include three groups: