String Functions Explained

Introduction

STRINGs are a crucial part of any dataset and being able to confidently manipulate and transform them can make all the difference in your analysis. This notebook covers the common STRING manipulations in BigQuery.

The Basics

STRINGs are their own data type in Big Query. They are the most flexible type - often our dates if not formatted exactly right will be read in as a STRING, or our survey results will be listed as STRINGs of responses. Therefore it's crucial to know how to master them.

Manipulating Strings

How to modify and transform entire STRINGs. Each of these functions returns a STRING.

Removing and adding characters

There are several functions available in BigQuery to add and remove whitespace to your STRINGs. They either involve:

trimming: removing whitespace

padding: adding whitespace

For trimming, the functions are:

TRIM(value1[, value2]) -> Removes all leading and trailing characters that match value2 (whitespace if not specified)

LTRIM(value1[, value2]) -> Removes only leading characters that match value2 (whitespace if not specified)

RTRIM(value1[, value2]) -> Removes only trailing characters that match value2 (whitespace if not specified)

SELECT
  '  Original String__',
  TRIM('  Original String__') AS trimmed,
  LTRIM('  Original String__') AS left_trim,
  RTRIM('  Original String__', "__") AS right_trim

f0_	trimmed	left_trim	right_trim
Original String__	Original String__	Original String__	Original String

💡 TRIM is very useful when dealing Substrings as shown in the next section.

For padding, the functions available are:

RPAD(original_value, return_length[, pattern]) -> Returns the original_value appended with the pattern up to the return_length number of characters.

LPAD(original_value, return_length[, pattern])-> Returns the original_value prepended with the pattern up to the return_length number of characters.

SELECT
  RPAD('abc', 5) AS right_spaces,
  LPAD('abc', 5, '--') AS left_pad_hypen

right_spaces	left_pad_hypen
abc	--abc

Changing case

A common way to re-format STRINGs is to change the case. To do that in BigQuery, you can use:

LOWER(value)-> Returns value in lowercase

UPPER(value) -> Returns value in uppercase

INITCAP(value[, delimiters]) -> Returns the first character in each word as uppercase and the rest as lowercase

SELECT
  UPPER('AbCd ef') AS upper,
  LOWER('AbCd ef') AS lower,
  INITCAP('AbCd ef') AS word_caps

upper	lower	word_caps
ABCD EF	abcd ef	Abcd Ef

Re-arranging values

To re-arrange the characters in a STRING, the most common function is:

REVERSE(value)-> Returns string in reverse order

SELECT
  REVERSE('racecar') AS palindrome,
  REVERSE('palindrome') AS not_palindrome

palindrome	not_palindrome
racecar	emordnilap

Analysing Strings

How to get information about each STRING. These functions may return INT64 or BOOL.

String length

To find the length of a STRING, there are a surprising number of options in BigQuery:

BYTE_LENGTH(value) -> Returns the length of the STRING in BYTEs

CHAR_LENGTH(value) or CHARACTER_LENGTH(value) -> Returns the length of the STRING in characters

LENGTH(value) -> Returns number of characters

SELECT
  BYTE_LENGTH('Hello! 👪') AS bytes,
  CHAR_LENGTH('Hello! 👪') AS characters,
  LENGTH('Hello! 👪') AS length

bytes	characters	length
11	8	8

Comparing strings

When building filters or CASE statements, it's common to check whether a STRING is or is similar to another string or substring. To do that we can use one of the STRING comparison functions:

STARTS_WITH(value1, value2)-> Returns True/False if value1 starts with the substring value2

ENDS_WITH(value1, value2)-> Returns True/False if value1 ends with with the substring value2

REGEXP_CONTAINS(value, regexp)-> Returns True/False if value contains the pattern matched in the regexp expression

You can see BigQuery's regex library here.

in combination with one of the following comparison operators:

=, !=

IN, NOT IN

LIKE, NOT LIKE

SELECT
  STARTS_WITH('Hello, there', 'Hello') AS starts_with_hello,
  'Bob' IN ('Mary', 'John', 'Barry') AS in_list,
  ('xyzFind Mejf3' LIKE '%Find Me%') AS like_string,
  REGEXP_CONTAINS('xyzFind Mejf3', r'Find Me') AS regex_contains

starts_with_hello	in_list	like_string	regex_contains
true	false	true	true

💡 For LIKE, the % is a wildcard character

Substrings

How to find, extract, and modify substrings, or parts of STRINGs. These functions may return INT64, ARRAY or STRING.

Finding substrings

When dealing with substrings you often want to first locate a substring within a STRING. To do that, we can use:

REGEXP_INSTR(source_value, regexp [, position[, occurrence, [occurrence_position]]])-> Returns the lowest 1-based index of a regular expression, regexp, in source_value

STRPOS(value1, value2)-> Returns the 1-based index of the first occurrence of value2 inside value1. Returns 0 if value2 is not found.

SELECT
  REGEXP_INSTR('hello@cool_stuff.com', r'@[^.]+.') AS regex_position,
  STRPOS('racecar', 'car') AS string_position

regex_position	string_position
6	5

These functions tell you which index the substring first appears, useful for replacing or extracting substrings given this index.

Replacing substrings

Once you've found a substring, you likely want to either extract it or replace it. To replace a substring, you can use one of the following:

REPLACE(original_value, from_value, to_value)->Replaces all occurrences of from_value with to_value in original_value.

REGEXP_REPLACE(value, regexp, replacement) -> Returns a STRING where all substrings of value that match regular expression regexp are replaced with replacement.

SELECT REPLACE('My Name is ____', '____', 'Judge') AS replace, REGEXP_REPLACE('My Name is ____', r'(_+)', 'Judge') AS regex_replace

SELECT
  REPLACE('My Name is ____', '____', 'Judge') AS replace,
  REGEXP_REPLACE('My Name is ____', r'(_+)', 'Judge') AS regex_replace

replace	regex_replace
My Name is Judge	My Name is Judge

Extracting substrings

Perhaps the most valuable manipulation to perform on substrings is to extract them to their own column or entity. To do that, there are several options:

LEFT(value, length)-> Returns a STRING value that consists of the specified number of leftmost characters or bytes from value

RIGHT(value, length)-> Returns a STRING value that consists of the specified number of rightmost characters or bytes from value

SPLIT(value[, delimiter]) -> Returns an ARRAY of STRINGs split by the delimiter (or space if omitted)

SUBSTR(value, position[, length]) -> Returns a substring of value from the position index up to the length of characters specified

REGEXP_EXTRACT(value, regexp[, position[, occurrence]]) or REGEXP_SUBSTR(value, regexp[, position[, occurrence]]) -> Returns a substring of value that matches the regexp expression starting at position index.

REGEXP_EXTRACT_ALL(value, regexp)-> Returns an ARRAY of substrings that match the regexp expression

SELECT
  RIGHT('@hello.com',9) domain,
  SPLIT('This is a sentence',' ') words,
  SUBSTR('_xyz_',2,3) substring, 
  REGEXP_EXTRACT_ALL('anything in CAPS is SPECIAL',r'([A-Z]+)') special_words

domain	words	substring	special_words
hello.com	This,is,a,sentence	xyz	CAPS,SPECIAL

Combining substrings

To combine substrings together you can use:

CONCAT(value1[, ...])-> Concatenates 2 or more STRINGs into a single result.

SELECT
  CONCAT('Hello', " ", "World")

f0_
Hello World

How Do I...

Count the number of occurrences of a character in a string?

To do this we can make use of REGEXP_EXTRACT_ALL and ARRAY_LENGTH.

SELECT
  ARRAY_LENGTH(REGEXP_EXTRACT_ALL("how many a's in this sentence?", r'(a)')) AS a_count

a_count
2

Extract numbers from string using regex?

To do this we can again use REGEXP_EXTRACT_ALL

We can choose to make our regex greedy, meaning once it found one number it will look for another one. This is the difference between:

r'([0-9]+)' : which says find 1 or more digits together and r'([0-9])' which says find any digits. Depending on what you want, both can be useful.

SELECT
  REGEXP_EXTRACT_ALL('12x12=144', r'([0-9]+)') AS greedy_number_count,
  REGEXP_EXTRACT_ALL('12x12=144', r'([0-9])') AS not_greedy_number_count

greedy_number_count	not_greedy_number_count
12,12,144	1,2,1,2,1,4,4

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