Printing floats

Scientific notation is a powerful tool for representing numbers, but it can be confusing to handle when trying to print float values. However, we can use the f strings we learned about previously to make sure we get them printed properly every time by using a format specifier. For example, if we wanted to format a variable in an f string as a float, we can use the f format specifier, such as: print(f"{some_variable:f}"). It also takes an operation precision on the float format specifier, for example, print(f"{some_variable:.4f}") would print four decimal places of precision.

This is a part of the course

“Data Types in Python”

Exercise instructions

Print float1, float2, and float3 notice where the jump to scientific notation occurs.
Print float2 and float3 using the default float format specifier, and notice what happened to float3.
Print float3 with the float format specifier and a precision of 7.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Print floats 1, 2, and 3
print(____)
print(____)
print(____)

# Print floats 2 and 3 using the f string formatter
print(f"{____}")
print(f"{____}")

# Print float 3 with a 7 f string precision
print(f"{____}")

Edit and Run Code

This exercise is part of the course

Data Types in Python

IntermediateSkill Level

4.3+

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

Start Course for Free

This chapter will introduce you to the fundamental Python data types - lists, sets, and strings. These data containers are critical as they provide the basis for storing and looping over ordered data. To make things interesting, you'll apply what you learn about these types to answer questions about the New York Baby Names dataset!

Exercise 1: Introduction and lists Exercise 2: Manipulating lists for fun and profit Exercise 3: Looping over lists Exercise 4: Meet the tuples Exercise 5: Data type usage Exercise 6: Using and unpacking tuples Exercise 7: Making tuples by accident Exercise 8: Strings Exercise 9: Formatted String Literals ("f" strings)Exercise 10: Combining multiple strings Exercise 11: Finding strings in other strings

At the root of all things Python is a dictionary. Herein, you'll learn how to use them to safely handle data that can viewed in a variety of ways to answer even more questions about the New York Baby Names dataset. You'll explore how to loop through data in a dictionary, access nested data, add new data, and come to appreciate all of the wonderful capabilities of Python dictionaries.

Exercise 1: Using dictionaries Exercise 2: Creating and looping through dictionaries Exercise 3: Safely finding by key Exercise 4: Altering dictionaries Exercise 5: Adding and extending dictionaries Exercise 6: Popping and deleting from dictionaries Exercise 7: Pythonically using dictionaries Exercise 8: Working with dictionaries more pythonically Exercise 9: Checking dictionaries for data Exercise 10: Mixed data types in dictionaries Exercise 11: Dealing with nested dictionaries Exercise 12: Dealing with nested mixed types

Let's take a step away from dictionaries and look at some other common numeric and boolean data types along with sets.

Exercise 1: Numeric data types Exercise 2: Choosing when to use integers and floats Exercise 3: Printing floats

Exercise 4: Division with integers and floats Exercise 5: Booleans - The logical data type Exercise 6: More than just true and false Exercise 7: Comparisons Exercise 8: Truthy, True, Falsey, and False Exercise 9: Sets (unordered data with optimized logic operations)Exercise 10: Determining set differences Exercise 11: Finding all the data and the overlapping data between sets

Some data types are composites of other data types and give me even more capabilities than a fundamental data type. Let's explore a few complex types from the collections module and data classes.

Exercise 1: Counting made easy Exercise 2: Using Counter on lists Exercise 3: Finding most common elements Exercise 4: Dictionaries of unknown structure - Defaultdict Exercise 5: Creating dictionaries of an unknown structure Exercise 6: Safely appending to a key's value list Exercise 7: What do you mean I don't have any class? Namedtuple Exercise 8: Creating namedtuples for storing data Exercise 9: Leveraging attributes on namedtuples Exercise 10: Dataclasses Exercise 11: Creating a dataclass Exercise 12: Using dataclasses Exercise 13: Wrap-up