Conditional statements in Python#
While there are many strategies for improving efficiency and removing repetition in code, three commonly used DRY strategies are conditional statements, loops, and functions.
This lesson introduces Python conditional statements which can be used to control the flow of code by executing code only when certain conditions are met.
Why Use Conditional Statements#
A conditional statement is used to determine whether a certain condition exists before code is executed.
Conditional statements can help improve the efficiency of your code by providing you with the ability to control the flow of your code, such as when or how code is executed.
This can be very useful for checking whether a certain condition exists before the code begins to execute, as you may want to only execute certain code lines when certain conditions are met.
For example, conditional statements can be used to check that a certain variable or file exists before code is executed, or to execute more code if some criteria is met, such as a calculation resulting in a specific value.
Structure of Conditional Statements#
A conditional statement uses a syntax structure based on if and else statements (each ending with a colon :) that define the potential actions that can be completed based on whether the condition is true or not:
if condition:
# some code here
else:
# some other code here
If the condition provided with the if statement is satisfied (i.e. results in a value of True), then a certain code will execute. If that condition is not met (i.e. results in a value of False), then the code provided with the else statement will execute.
For example:
Indentation and Execution of Code Lines#
Note that the indentations for the code lines after if and else are an important part of the syntax of conditional statements. These indentations indicate which code should be executed with which statement, and they make the code easier to read.
In the examples above, the print() code can actually be replaced by any code that will execute in Python. For example, you could choose to add values, select data, plot data, etc. depending on whether the condition is satisfied.
To help you get familiar with conditional statements first, the examples on this page simply execute different print statements depending on whether the condition is satisfied.
Compare Numeric Values Using Conditional Statements#
You can write conditional statements that use comparison operators (e.g. equal to ==, less than <) to check the value of a variable against some other value or variable.
For example, you can check whether the value of a variable is equal (==) to a certain value.
You can also use other comparison operators to check whether the value of variable is less than (<) or greater (>) than a certain value or another variable.
Check For Values Using Conditional Statements#
You can use membership operators (e.g. in or not in) to write conditional statements to check whether certain values are contained within a data structure, such as a list, or even a text string.
The condition above could also be checked in the opposite manner using not in to check that the value is not in the list:
You can also use membership operators to check for specific words within a text string.
Note that with this syntax, you are simply checking whether one text string is contained within another text string.
Thus, if you check for a specific text string within the name of an object, such as a list (e.g. avg_monthly_precip), you are not actually checking the values contained with the object.
Instead, specifying the object name using quotations "" (e.g. "list_name") identifies that you are referring to the name as text string.
Checking for specific text strings within the names of objects, such as lists or data structures, can be helpful when you have a long, automated workflow for which you want to execute code on only those objects that have a particular word in the name.
Check Object Type Using Conditional Statements#
You can also use identity operators (e.g. is or is not) to write conditional statements to check whether an object is of a certain type (e.g. int, str, list).
With identity operators, you can also check that an object is a certain data structure, such as a list, and even compare its type to the type of another object.
Note in the example above that you are not checking whether the objects are lists, but rather whether they are both of the same type. Because both of the objects are indeed lists, the condition is satisfied.
Check Paths Using Conditional Statements#
You can also use conditional statements to check paths using a familiar function: os.path.exists().
In the example below, you will download a .txt file that contains the average monthly precipitation values for Boulder, Colorado, provided by the U.S. National Oceanic and Atmospheric Administration (NOAA).
Begin by importing the necessary packages and writing the code needed to download the data (earthpy) and set the working directory (os). You will also use numpy package to import the data into a numpy array.
# Import necessary packages
import os
# TODO: open a .json file here
Next, define a relative path to the downloaded file, which you will use in the conditional statement.
# Path relative to working directory
Last, add the defined path to the conditional statement to check whether the path exists.
# Check path
if os.path.exists(avg_month_precip_path):
print("This is a valid path.")
else:
print("This path does not exist.")
You can expand on the conditional statement to execute additional code if the path is valid, such as code to import the file into a numpy array.
# Import data into array if path exists
if os.path.exists(avg_month_precip_path):
avg_month_precip = np.loadtxt(avg_month_precip_path)
print(avg_month_precip)
else:
print("This path does not exist.")
Using this syntax, you can check whether any defined path exists and then execute additional code as needed.
In the next lesson, you will learn how to write conditional statements that check for multiple conditions.