How To Print An Array In Python - AskPython

To print arrays in Python, you can use the print() function directly for simple output or implement loops for formatted display. This guide covers both approaches for 1D and 2D arrays with practical examples.

Array printing in Python hits different when you’re debugging at 3 AM.

What starts as a simple print() statement can turn into an entire formatting philosophy.

I’ve been down this rabbit hole. Multiple times.

What Are Python Arrays?

First things first, there are no arrays in Python.

You get lists and NumPy arrays.

• Lists are Python’s default – flexible, forgiving, and deceptively simple.
• NumPy arrays want type consistency. They reward you with performance.

This distinction becomes critical when you’re trying to make sense of your output at 2 AM.

Printing Python Arrays Using Lists

Directly Printing Arrays with print()

Sometimes the simplest approach is the right one:

# Simple 1D array numbers = [2, 4, 5, 7, 9] print("Array:", numbers) # 2D array (list of lists) matrix = [[1, 2], [3, 4]] print("2D Array:", matrix)

Output:

Array: [2, 4, 5, 7, 9] 2D Array: [[1, 2], [3, 4]]

Quick. Dirty. Perfect for those “what the hell is in this variable?” moments.

But we’re not always debugging. Sometimes we need our data to actually make sense to humans.

Custom Formatted Printing with Loops

This is where you separate the juniors from the seniors. The ability to format output properly:

# 1D array with custom spacing data = [2, 4, 5, 7, 9] print("Values: ", end="") for value in data: print(value, end=" ") print() # New line # 2D array as a grid grid = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] print("Grid format:") for row in grid: for item in row: print(f"{item:2}", end=" ") # Format with width 2 print() # New line after each row

Output:

Values: 2 4 5 7 9 Grid format: 1 2 3 4 5 6 7 8 9

Now we’re talking. Readable output. Aligned columns. The kind of formatting that won’t make your eyes bleed during code review.

Printing Python NumPy Arrays

Basic NumPy Array Printing

NumPy doesn’t mess around with formatting:

import numpy as np # 1D NumPy array vector = np.array([1, 2, 3, 4]) print("Vector:", vector) # 2D NumPy array matrix = np.array([[21, 43], [22, 55], [53, 86]]) print("Matrix:\n", matrix)

Output:

Vector: [1 2 3 4] Matrix: [[21 43] [22 55] [53 86]]

Notice the difference? No commas. Automatic alignment. NumPy gets it.

Advanced NumPy Formatting and Printing

NumPy’s formatting options are… extensive. Sometimes overwhelmingly so:

import numpy as np # Control decimal places floats = np.array([3.14159, 2.71828, 1.41421]) np.set_printoptions(precision=3) print("Formatted floats:", floats) # Large arrays with ellipsis large_array = np.arange(100) np.set_printoptions(threshold=10) print("Large array:", large_array) # Reset to default np.set_printoptions(edgeitems=3, threshold=1000, precision=8)

Output:

Formatted floats: [3.142 2.718 1.414] Large array: [ 0 1 2 ... 97 98 99]

Powerful when you need it. Overkill when you don’t.

When Your Output Actually Matters

Let’s face it – most of us aren’t printing arrays for fun. We’re trying to make sense of data:

import numpy as np # Sales data by region and quarter sales_data = np.array([ [45000, 52000, 48000, 51000], # North [38000, 41000, 43000, 46000], # South [55000, 58000, 54000, 59000], # East [42000, 44000, 47000, 49000] # West ]) regions = ['North', 'South', 'East', 'West'] quarters = ['Q1', 'Q2', 'Q3', 'Q4'] # Print formatted table print("Sales by Region and Quarter") print("-" * 40) print("Region ", end="") for q in quarters: print(f"{q:>8}", end="") print() print("-" * 40) for i, region in enumerate(regions): print(f"{region:<8}", end="") for sale in sales_data[i]: print(f"{sale:8,}", end="") print()

Output:

Sales by Region and Quarter ---------------------------------------- Region Q1 Q2 Q3 Q4 ---------------------------------------- North 45,000 52,000 48,000 51,000 South 38,000 41,000 43,000 46,000 East 55,000 58,000 54,000 59,000 West 42,000 44,000 47,000 49,000

This is what clean output looks like.

Scientific Computing Array Printing

When precision matters more than aesthetics. Let’s display a correlation matrix:

import numpy as np # Correlation matrix correlation = np.array([ [1.000, 0.812, 0.543], [0.812, 1.000, 0.721], [0.543, 0.721, 1.000] ]) variables = ['Temperature', 'Pressure', 'Volume'] print("Correlation Matrix") print("-" * 50) print(f"{'':12}", end="") for var in variables: print(f"{var[:11]:>12}", end="") print() for i, var in enumerate(variables): print(f"{var[:11]:<12}", end="") for j, value in enumerate(correlation[i]): print(f"{value:12.3f}", end="") print()

Output:

Correlation Matrix -------------------------------------------------- Temperature Pressure Volume Temperature 1.000 0.812 0.543 Pressure 0.812 1.000 0.721 Volume 0.543 0.721 1.000

Clean. Professional. The kind of output that doesn’t make your colleagues question your competence.

Best Practices and Reality Checks

Choosing the Right Array Printing Method

Your approach should fit your context:

• Debugging? print() and move on
• Code review coming up? Format that shit properly
• Scientific paper? NumPy formatting is your friend
• Teaching others? Clear examples with clean output

Conclusion

Array printing in Python isn’t hard. But the difference between amateur hour and professional output is in these details.

Start simple. Use print() when debugging. Format properly when sharing code. Use NumPy when you need precision.

The best approach? Whatever makes your output understandable to the poor soul reading it later.

Because that poor soul is usually future you.