If/Else - Conditional Statements in Julia

Last updated on 2026-01-27 | Edit this page

Overview

Questions

How can my programs make decisions and behave differently depending on data values?

Objectives

Write conditional statements including if, elseif, and else branches.

Correctly evaluate expressions containing && (and) and || (or).

In our last lesson, we noticed some suspicious patterns in our inflammation data by creating plots. How can we use Julia to automatically detect the kinds of features we saw, and take different actions depending on the results?

In this lesson, we’ll learn how to write code that only runs when certain conditions are met.

Conditionals

We can ask Julia to take different actions depending on a condition with an if statement:

JULIA

num = 37
if num > 100
    println("greater")
else
    println("not greater")
end
println("done")

OUTPUT

not greater
done

The second line of this code uses the keyword if to tell Julia that we want to make a choice. If the test that follows the if statement is true, the body of the if (the indented lines beneath it) is executed, and "greater" is printed.

If the test is false, the body of the else branch is executed instead, and "not greater" is printed. Only one branch is ever taken before continuing execution to print "done":

Conditional statements don’t have to include an else. If there isn’t one, Julia simply does nothing if the test is false:

JULIA

num = 53
println("before conditional...")
if num > 100
    println(num, " is greater than 100")
end
println("...after conditional")

OUTPUT

before conditional...
...after conditional

We can also chain several tests together using elseif The following Julia code uses elseif to print the sign of a number:

JULIA

num = -3

if num > 0
    println(num, " is positive")
elseif num == 0
    println(num, " is zero")
else
    println(num, " is negative")
end

OUTPUT

-3 is negative

Note that to test for equality we use a double equals sign == rather than a single equals sign =, which is used to assign values.

Comparing in Julia

To compare values we can use the following operators:

> : greater than
< : less than
== : equal to
!= : not equal to
>= : greater than or equal to
<= : less than or equal to

We can also combine comparisons using logical operators:

&& : logical AND (true if both conditions are true)
|| : logical OR (true if at least one condition is true)
! : logical NOT (inverts the truth value)

The syntax to combine operators looks like this:

JULIA

if (1 > 0) && (-1 >= 0)
    println("both parts are true")
else
    println("at least one part is false")
end

OUTPUT

at least one part is false

JULIA

if (1 < 0) || (1 >= 0)
    println("at least one test is true")
end

OUTPUT

at least one test is true

Callout

`true` and `false`

true and false are special values in Julia called Booleans, which represent truth values. A statement such as 1 < 0 returns false, while -1 < 0 returns true.

Checking Our Data

Now that we’ve learned how conditionals work, we can use them to check for the suspicious features we observed in our inflammation data. We’ll load the CSV file using Julia’s standard library module DelimitedFiles.

JULIA

using DelimitedFiles

data = readdlm("inflammation-01.csv", ',')

From the first plots, we noticed that the maximum daily inflammation increases by one unit each day. We can check for this suspicious pattern by comparing the maximum values at the start (day 0) and in the middle (day 20) of the study. We also noticed a different issue in the third dataset: the daily minima were all zero (as if a healthy participant had been included in the study). We can check for this using an elseif branch. If neither the maxima check nor the minima check is true, we can use else to give the all-clear.

JULIA

max_inflam_0 = maximum(data[:, 1])
max_inflam_20 = maximum(data[:, 21])

if max_inflam_0 == 0 && max_inflam_20 == 20
    println("Suspicious looking maxima!")
elseif sum(minimum(data, dims=1)) == 0
    println("Minima add up to zero!")
else
    println("Seems OK!")
end

We can test it with another dataset:

JULIA

data = readdlm("inflammation-03.csv", ',')

max_inflam_0 = maximum(data[:, 1])
max_inflam_20 = maximum(data[:, 21])

if max_inflam_0 == 0 && max_inflam_20 == 20
    println("Suspicious looking maxima!")
elseif sum(minimum(data, dims=1)) == 0
    println("Minima add up to zero!")
else
    println("Seems OK!")
end

OUTPUT

Minima add up to zero!

Using this approach, Julia evaluates the conditions in order:

If the first condition is true, it executes the corresponding block.
If not, it checks the elseif condition.
If neither condition is true, the else block provides a default action.

This allows us to automatically flag suspicious datasets without manually inspecting every plot, saving time and catching patterns systematically.

Challenge

How Many Paths?

Consider this code:

JULIA

if 4 > 5
    println("A")
elseif 4 == 4
    println("B")
elseif 4 < 5
    println("C")
end

Which of the following would be printed if you were to run this code? Why did you pick this answer?

A
B
C
B and C

Show me the solution

B gets printed because 4 > 5 is false, and 4 == 4 is the first true condition. Even though 4 < 5 is also true, it is not executed because in an if / elseif chain, only the first true branch runs.

Even if multiple elseif conditions could theoretically be true, Julia will execute just the first one that is true, starting from the top of the conditional section.

This contrasts with multiple independent if statements, where every condition that is true will execute its block, not just the first.

Challenge

Close Enough

Write conditions that print true if the variable a is within 10% of the variable b, and false otherwise. Compare your implementation with a partner: do you get the same result for all possible pairs of numbers?

Hint

Julia has a built-in function abs() that returns the absolute value of a number:

JULIA

println(abs(-12))

OUTPUT

Solution 1

JULIA

a = 5
b = 5.1

if abs(a - b) <= 0.1 * abs(b)
    println(true)
else
    println(false)
end

Solution 2

JULIA

a = 5
b = 5.1

println(abs(a - b) <= 0.1 * abs(b))

This works because the Boolean values true and false can be printed directly.

Challenge

In-Place Operators

Julia also provides in-place operators that modify a variable in place. For example:

JULIA

x = 1   # original value
x += 1  # add one to x
x *= 3  # multiply x by 3
println(x)

OUTPUT

Write some code that sums the positive and negative numbers in a vector separately, using in-place operators. Do you think this is more or less readable than writing it without in-place operators?

Show me the solution

JULIA

positive_sum = 0
negative_sum = 0
test_vector = [3, 4, 6, 1, -1, -5, 0, 7, -8]

for num in test_vector
    if num > 0
        positive_sum += num
    elseif num == 0
        # do nothing
    else
        negative_sum += num
    end
end

println("Sum of positives: ", positive_sum)
println("Sum of negatives: ", negative_sum)

Here, the elseif num == 0 branch is optional since neither sum changes for zero values, but it illustrates the use of elseif.

Challenge

Sorting Filenames Into Buckets

In our data folder, large datasets are stored in files whose names start with "inflammation-" and small datasets are in files whose names start with "small-". Other files can be ignored for now.

Your task is to sort these filenames into three separate vectors: large_files, small_files, and other_files.

Hint:

use startswith:

JULIA

println(startswith("string", "str"))   
println(startswith("string", "abc"))

OUTPUT

true
false

Starting Point

JULIA

filenames = ["inflammation-01.csv",
             "myscript.jl",
             "inflammation-02.csv",
             "small-01.csv",
             "small-02.csv"]

large_files = String[]
small_files = String[]
other_files = String[]

Your Task

Loop over the filenames.
Determine which category each filename belongs to.
Append the filename to the corresponding vector.

Show me the solution

JULIA

for filename in filenames
    if startswith(filename, "inflammation-")
        push!(large_files, filename)
    elseif startswith(filename, "small-")
        push!(small_files, filename)
    else
        push!(other_files, filename)
    end
end

println("large_files: ", large_files)
println("small_files: ", small_files)
println("other_files: ", other_files)

large_files: ["inflammation-01.csv", "inflammation-02.csv"]
small_files: ["small-01.csv", "small-02.csv"]
other_files: ["myscript.jl"]

Challenge

Counting Vowels

Write a loop that counts the number of vowels in a string.
Test it on a few words and full sentences.
Compare your solution with a neighbor’s — did you handle the letter y the same way?

Show me the solution

JULIA

vowels = "aeiouAEIOU"
sentence = "Hallo World!."
count = 0

for char in sentence
    if char in vowels
        count += 1
    end
end

println("The number of vowels in this string is ", count)

OUTPUT

The number of vowels in this string is 3

Key Points

Use if condition to start a conditional statement, elseif condition to provide additional tests, and else to provide a default.
The bodies of the branches of conditional statements must be enclosed within if/elseif/else and end.
Use == to test for equality.
X && Y is only true if both X and Y are true.
X || Y is true if either X or Y, or both, are true.

If/Else - Conditional Statements in Julia

Overview

Questions

Objectives

Conditionals

JULIA

OUTPUT

JULIA

OUTPUT

JULIA

OUTPUT

Comparing in Julia

JULIA

OUTPUT

JULIA

OUTPUT

true and false

Checking Our Data

JULIA

JULIA

JULIA

OUTPUT

How Many Paths?

JULIA

Show me the solution

Close Enough

Hint

JULIA

OUTPUT

Solution 1

JULIA

Solution 2

JULIA

In-Place Operators

JULIA

OUTPUT

Show me the solution

JULIA

Sorting Filenames Into Buckets

JULIA

OUTPUT

Starting Point

JULIA

Your Task

Show me the solution

JULIA

Counting Vowels

Show me the solution

JULIA

OUTPUT

`true` and `false`