Functions, Lambda Functions, Loops, and List ComprehensionsPython guides and exercises to help you increase your data analytics skills. Our exercises are business focused to help you apply your new technical skills to business concepts.
|
|
Functions, Lambda Functions, Loops, and List Comprehensions
When working with data analytics, you might need to perform advanced operations such as reading lists of lists, deleting vowels from your list, filtering column names, and many others. In Python, there are numerous ways to do this.
For example, we can create a list of values using the for loop function. The good news is that Python has an elegant way to create the list using the List Comprehension. Here, you can simply create and define a new list from an existing list.
Another way to create a list is using Lambda functions. This method allows you to create and modify lists with lesser lines of code. When combined with other programming tools, Lambda functions can be very powerful to process your dataset with less lines of code. The only challenge with this technique is the readability. List comprehension can be easily understood compared to Lambda functions.
In general, list comprehensions are more compact than using functions and loops. However, it is not also advised to create very long list comprehensions in one line of code to keep your program compact and friendly.
The goal of this tutorial is to help you gain understanding about Python comprehension lists and how you can effectively use lambda or loops functions to manipulate data. Each of the exercise included will require you to use these techniques to create lists and process your dataset.
For example, we can create a list of values using the for loop function. The good news is that Python has an elegant way to create the list using the List Comprehension. Here, you can simply create and define a new list from an existing list.
Another way to create a list is using Lambda functions. This method allows you to create and modify lists with lesser lines of code. When combined with other programming tools, Lambda functions can be very powerful to process your dataset with less lines of code. The only challenge with this technique is the readability. List comprehension can be easily understood compared to Lambda functions.
In general, list comprehensions are more compact than using functions and loops. However, it is not also advised to create very long list comprehensions in one line of code to keep your program compact and friendly.
The goal of this tutorial is to help you gain understanding about Python comprehension lists and how you can effectively use lambda or loops functions to manipulate data. Each of the exercise included will require you to use these techniques to create lists and process your dataset.