6 Python Built-in Functions Which You Should Know While Learning Data Science

In this article, we’re going to take a look at some of the Python built-in functions which you should know while learning data science. We’ll be covering the functions Max() and Min(), Len() and Range(), as well as Input() and Print(). By the end of this post, you should have a better understanding of how these functions can be used in data science and what they can do for you.

So, whether you’re a beginner data scientist or you’ve been doing data science for a while, make sure you take a look at these functions and learn how to use them. They’ll be a valuable addition to your data science toolkit.

Max And Min

Data science is a rapidly growing field that is full of mathematical and statistical concepts. However, sometimes it can be difficult to understand these concepts without examples. That's where the max() and min() functions come in handy.

The max and min functions are used to find the highest and lowest values in an iterable. These functions can be used on list, tuple, set, and dictionary data types. Python also has a built-in function called max() which can be used on strings.

Syntax for max() and min() function in Python:

max()

For a single positional argument provided, it's iterable and the largest item in it is returned. Here it is:

max(iterable, *[, key, default])

For two or more arguments provided, the largest value is returned. Here it is:

max(arg1, arg2, *args[, key])

min()

For a single positional argument provided, it's iterable and the smallest item in it is returned. Here it is:

min(iterable, *[, key, default])

For two or more arguments provided, the smallest value is returned. Here it is:

min(arg1, arg2, *args[, key])

The max() and min() functions will return the element with the highest and lowest value, respectively. Next time you're trying to understand a data science concept, don't forget about this helpful Python function.

Len

Len is another important built-in function in Python that can be used to find the length of a list, string, dictionary, or tuple. This function is particularly useful when you need to know how many items are in a collection or when you want to find out how long a particular string or object is.

To use len(), you first need to specify which type of object you are looking for. For example, if you want to find the length of a list, you would use len(list). If you want to know the length of a string, you would use len(string). If you want to find the length of a dictionary, you would use len(dictionary) and so on.

There is one important difference between len() and sum(). sum() returns the total number of items in a collection while len() only returns the length of that particular type of object. For example, if a list has three items and sum(list) is 4, then len(list) will be 3 because sum(list) only counts the number of unique values in list (in this case 3).

Finally, Len can be used in your Python program just like any other function. You can call it using parentheses just like any other command. For example, if we wanted to print out the length of our sample list above we could do something like this: print(The length of our sample list is,len(sample_list))

Range

In data science, it's important to be able to generate sequences of numbers. This is usually done in for loops, where each number in the sequence is generated by running the code one after the other. The range() function is the third important built-in Python function that you should be aware of while learning data science.

The range() function takes three arguments: start, stop, and step; start is the starting number of the sequence, stop is the end number of the sequence, and step is the difference between each number in the sequence. If no argument is given, then start defaults to 0 and stop defaults to infinity, and step defaults to 1. Negative step values can be used to generate a sequence in reverse order (start=-1, stop=0, step=1).

Generally speaking, you'll use range() in for loops to iterate through a sequence of numbers. For example:

for num in range(10): # Generates a list containing 10 numbers

print(num)

Input

Python is a powerful language that is used to write data science algorithms. One of the most important functions that you need to know when learning data science is the input function. The input function takes a single parameter as the prompt string.

The return value of the input function is always a string. Even if the user enters a number, the return value is a string. Therefore, if we want to store the input as an integer, we have to typecast it. We can also specify the datatype which the input function should return by using the eval function. However, be aware that using eval is risky because it can run arbitrary Python code.

Print

When you're learning data science, it's important to know the built-in functions that are available to you. One of these functions is print(), and it's a valuable tool for displaying the output of various data types.

Print can be used to display the output of strings, lists, tuples, dictionaries, sets, and even lists of objects. It can take multiple arguments and can be displayed in a separate line by using a separator (,) as an argument. If you want to display the output without any spaces or newlines, you can use an end argument.

You can also format the output of print() by using a format argument. This argument allows you to specify how the data should be displayed – for example, as text or as a list of values. By formatting your data this way, you make it easier for other people who are working with your data to understand it.

To Sum Things Up

Python is a versatile language that you can use for a variety of tasks. In this blog, we looked at some of the most commonly used functions in Python. We hope you found this information helpful and that you'll be able to put it to good use in your projects.

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