String manipulation is an important activity in all programming endeavours, for numerous reasons. Traditionally, programmers had to manually write the string manipulations methods and invoke them when needed.

However, as programming languages got more versatile, methods were added to them to save the programmer’s time. These methods are essential to perform the basic tasks often needed in any programming environment. For example, in the case of Python, you get several built-in functions to perform various tasks. Plus, you can create your custom functions, too. 

In this article, we’ll be looking at one such method available in Python for string manipulation: the split() method. But before we get into the working and example of the split() method, let’s first understand the basics of Strings in Python. 

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Basics of Strings in Python

String data type in Python, abbreviated as ‘str’, holds the text type data. Here’s an example to understand Strings better: 

my_name = "Ron"
print(type(my_name))

We can also use single quotes instead of double quotes, as follows: 

my_name = 'Ron’
print(type(my_name))

Another way to declare a String variable in Python, by setting it explicitly, goes as follows: 

my_name= str("Ron")
print(type(my_name))

The print() method in all three examples will return the same results as below: 

Output:

<class 'str'>
<class 'str'>
<class 'str'>

This shows that all three variables are of ‘str’ type, regardless of how we have defined the variable. Now that we have Strings in place, it’s important to realise that sometimes, we need to perform various manipulations or modifications on these strings. For that, Python provides built-in string methods. Some of the more commonly used string methods include: 

• Replace()
• Strip()
• Split()
• Join()
• Capitalize()
• Casefold/Lower()
• Count()
• Endswith()
• Startswith()
• Index(), and more. 

Here’s a list of all the String methods available in Python. 

This article will look at the split() method in detail, so let’s get started with that! 

String split() method in Python

Python’s split() method breaks a large string into smaller chunks of substrings. Unlike concatenation, which merges different strings, the split method breaks one string into different sections. The split() method divides the string into substrings and adds the data to an array with the help of the defined separator. If the programmer doesn’t define a separator while calling the split() method, the white space is used by default as the separator. 

Let’s understand the working of the String split() method in Python from the very basics for the uninitiated. Suppose we have the following input – “A; B; C”. The split() method will break this input into an array with three elements, as follows: 

[“A”, “B”, “C”]

The punctuation marks in our initial input (semi-colons) are the separators or delimiters in this case. For example, ‘,’, ‘;’, ‘@’, ‘&’, ‘:’, ‘(‘, ‘>’ etc., all these are delimiters. 

Parameters of String split() method

The split() method in Python takes the following parameters: 

• Separator – This is the delimiter at which the string split occurs. If this is not mentioned, the split() method breaks the strings based on whitespaces. 
• Maxsplit – This refers to the maximum number of splits. If this isn’t specified, the method does not take any value, and there is no limit on the number of possible splits. The default value of maxsplit is ‘-1’, which refers to all occurrences. 

Here is the syntax of the split() method using both the parameters: 

str.split(separator, maxsplit)

Now that you’ve understood the split() method and the parameters it takes, let’s look at the situations where you will need this method. 

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The requirement of the split() function in Python

The split() function is useful in several cases where you require string manipulation. Some of those cases are when we need to perform splitting based on: 

• The delimiter space, comma, tab, and so on
• Multiple delimiters
• Occurrence of characters
• File into a list
• String into a character array
• File manipulation activities
• Substrings from the given string as the delimiter, etc. 

Let’s now look at some hands-on examples of using the split() function in various cases.

Python String split() method – Examples

Example 1 – Splitting the string using space as the delimiter: 

data = "upGrad is here for you"
splitdata = data.split()
print(splitdata)

Running the above code will give the following output: 

['upGrad', 'is’, ‘here’, ‘for’, ‘you’]

Example 2 – Splitting the string using a comma as the delimiter: 

data = "upGrad, Data Science, Data Analytics, Big Data”
splitdata = data.split(‘,’)
print(splitdata)

The output will be as follows: 

[‘upGrad’, ‘Data Science’, ‘Data Analytics’, ‘Big Data’]

Example 3 – Splitting the string using hash as the delimiter:

data = "#upGrad#Data Science#Data Analytics#Big Data”
splitdata = data.split("#")
print(split)

The output will be as follows: 

[‘upGrad’, ‘Data Science’, ‘Data Analytics’, ‘Big Data’]

Example 4 – Splitting the data in a given file into a list (using splitlines()):

Supposing our text file had the following content – “This is the first line of the file. Welcome to upGrad!”. 

#opening a file in read mode using open() function

fp = open("example.txt", "r")

#reading the contents of the file 

fr = fp.read()

Displaying the content of the file as a list

print(fr.splitlines())
fp.close()

The output of this program is as follows: 

[‘This is the first line of the file’, ‘Welome’, ‘To’, ‘upGrad’]

Example 5 – Splitting a given string into several characters with one of the substrings being the delimiter:

str_to_split = “upGrad, is, for, you”
splitstring = str_to_split(“is”)
print(splitstring)

The output of the above program will be: 

[‘upGrad, ‘, ’ ‘, for’ ‘, you’]

Handling Empty Elements

It is possible to get across situations when a string has consecutive delimiters or where the string begins or ends with a delimiter while dividing it. In certain circumstances, the split() method adds empty strings to the list’s elements. Additional strategies, like list comprehensions or filter functions, can change this behavior.

Example 6 – Handling empty elements using list comprehension:

```Python
data = "Python,,programming,,language"
splitdata = [x for x in data.split(",") if x]
print(splitdata)
```

Output:

```
['Python', 'programming', 'language']
```

The string in this example has consecutive commas acting as delimiters. The empty entries in the resulting list are removed using list comprehension and an if statement (‘if x’).

Limiting the Number of Splits

The split() method limits the number of splits performed on the string. By specifying the `maxsplit` parameter, developers can control the maximum number of splits that occur. This feature is particularly beneficial when dealing with large strings or when only a certain number of splits is required.

Example 7 – Limiting the number of splits:

```Python
data = "Python String Split Method Example"
splitdata = data.split(maxsplit=2)
print(splitdata)
```

Output:

```
['Python', 'String', 'Split Method Example']
```

In this example, `maxsplit` is set to 2, so the split() method only performs two splits on the string. The resulting list contains three elements; the last element retains any remaining parts of the string.

Controlling the Number of Splits

The ability to set the highest number of splits is crucial while utilizing the split() method. The highest number of splits that can take place can be managed by using the maxsplit parameter. The number of splits that can be executed is unbounded if maxsplit is left blank. The number of splits can be limited by specifying a positive integer value for maxsplit. With this capability, the substrings that are produced can be controlled more precisely.

Handling Multiple Delimiters

The split() method may manage several delimiters concurrently, increasing its applicability in complicated situations. If you do, the procedure will split the string at any instance of the delimiters you supply. This capability is quite useful when working with different data formats or extracting data from strings with different delimiters.

Efficiently Splitting Large Files

Splitting large files into manageable sections is a common requirement in programming. The splitlines() method, closely related to split(), provides a convenient way to split a file into lines and store them as elements in a list. This approach simplifies file processing tasks and enables developers to work with file content more efficiently.

Advanced Extraction Techniques

In addition to its fundamental functionality, the split() method can be combined with other string manipulation techniques to extract specific information from strings. For instance, when working with CSV files or extracting data from APIs, splitting a string on commas and processing the resulting substrings individually can be highly advantageous. This approach allows for efficient data extraction and further processing.

Leveraging Regular Expressions

Regular expressions can be used along with the split() method to split strings based on intricate patterns. Regular expressions are a powerful and adaptable method for matching and modifying strings by predetermined patterns. Regular expressions can be used with the split() method to split a string based on complex patterns instead of basic delimiters, offering more sophisticated string manipulation options.

In Conclusion

We hope this article helped you with understanding and getting hands-on with the String split() method available in Python. Like split(), there are various other methods, too, that can be used as easily as this one. All you need to know is the correct scenario where you need to invoke which method, and then it’s all straightforward and intuitive.

These methods give the power and versatility to the Python programming language that makes it one of the most sought after languages today. No wonder the language is handy in so many varied contexts – from software development to data analytics, data visualisation to statistical computations, and so much more.

If you’d want to dive deeper into working with Python, especially for data science, upGrad brings you the Executive PGP in Data Science. This program is designed for mid-level IT professionals, software engineers looking to explore Data Science, non-tech analysts, early career professionals, etc. Our structured curriculum and extensive support ensure our students reach their full potential without difficulties.