If you’ve ever used the strptime() function to create a timestamp in DuckDB, you may be aware that it will return an error if it can’t construct the timestamp from the format string/s provided.
While such an error could be useful in some situations, it could also be annoying in others.
Fortunately, DuckDB also provides the try_strptime() function, which will suppress any error that we might ordinarily get in such cases. This function returns null instead of an error.
In DuckDB, the generate_series() function is a powerful tool for generating sequences of values, which can be very useful for data analysis, testing, and creating sample datasets. This function enables us to easily create series of numbers, dates, and timestamps with minimal code.
When working with date and time data in DuckDB, calculating the difference between two dates is a common requirement. Whether we’re determining a person’s age from their birthdate or measuring the duration between two events, DuckDB’s age() function provides a straightforward solution. This function returns an interval representing the difference between two timestamps or dates, making it especially useful for time-based analyses.
In this article, we’ll explore how to use the age() function in DuckDB. We’ll cover its syntax, and provide some simple examples.
If you’re getting an error that reads “Conversion Error: extract specifier “monthname” not recognized” in DuckDB, it appears that you’re using a function like extract() or date_part() to try to get the month name from a date.
These functions don’t accept a monthname specifier, and so that’s why the error occurs. Fortunately, DuckDB provides a monthname() function, and so you could try that instead. Also, the strftime() function has a format specifier for the month name, and so that’s another option.
So to fix this issue, try the monthname() or strftime() function instead.
In DuckDB, ISFINITE() is a function for checking whether values are finite. DuckDB supports infinite values, and so we can use this function to check whether a value is infinite or not. This can be useful when working with floating-point data that might contain special values like NaN (Not a Number) or infinity. We can also use it on date and timestamp values.
DuckDB provides us with an easy way to add one or more time intervals to date values. This includes adding one or more years to a date.
Here are two options for adding one or more years to a date in DuckDB.
Continue readingIf you’re getting an error that reads “Not implemented Error: Unknown TimeZone” in DuckDB, it appears that you’re using an unknown timezone when specifying a timezone for a timestamp value.
To fix this issue, be sure to use a supported timezone.
Continue readingSometimes we need to specify a time zone when constructing timestamp values in DuckDB. But we may not always know the exact value to use for the time zone.
Fortunately, we can use the pg_timezone_names() table function to get a list of available timezones in DuckDB.
Both AGE() and DATE_DIFF() are DuckDB functions used to calculate time differences, but they serve distinct purposes and exhibit different behaviors that are important to understand when working with temporal data.
This article explores the difference between these two functions.
Continue readingIn DuckDB, the make_date() function enables us to create date values from individual year, month, and day components. This function is particularly useful when working with data that stores date components separately or when constructing date values programmatically.