In Python, “array” can mean three different things: a built-in list, the standard-library array.array, or NumPy’s ndarray. Use a list for general-purpose sequences, array.array for a typed one-dimensional sequence, and NumPy when you need multidimensional numerical data and array-oriented operations.
What does “array” mean in Python?
Python learners encounter the word in different contexts because these structures are related but not interchangeable. A list is built into Python and can hold general-purpose objects. The standard-library array.array stores mutable sequences constrained to a basic type. NumPy’s ndarray is a homogeneous array designed for numerical work, including multiple dimensions. NumPy’s official quickstart distinguishes its ndarray from array.array, which handles one dimension and offers less functionality: NumPy quickstart.
| Structure | Where it comes from | Element types | Native multidimensional shape | Typical fit |
|---|---|---|---|---|
list |
Built into Python | Can contain different Python object types | No; nested lists can represent rows, but do not provide NumPy’s array shape and operations | General-purpose collections and sequences |
array.array |
Python standard library | Constrained by a type code | No; one-dimensional | Compact typed sequence of basic values when its limited feature set is enough |
NumPy ndarray |
External package; install NumPy separately | Homogeneous element type described by dtype |
Yes | Multidimensional numerical data and array-oriented operations |
How do I create an array in Python?
For numerical arrays, import NumPy by its conventional alias, np, then pass a Python sequence to np.array. A flat sequence creates a one-dimensional array; nested sequences create multiple dimensions. The official creation guide also documents constructors such as arange, ones, and zeros: NumPy array creation.
import numpy as np
# One-dimensional array from a list
values = np.array([10, 20, 30])
# Two-dimensional array from nested lists
matrix = np.array([[1, 2, 3], [4, 5, 6]])
# Other common ways to create arrays
sequence = np.arange(5) # 0 through 4
zeros = np.zeros((2, 3)) # two rows, three columns
ones = np.ones(4) # four elementsThe basic constructor is numpy.array(object, dtype=...): object can be a sequence, including nested sequences, and dtype optionally specifies the array’s element type. See the numpy.array reference.
Free tools Windows power users keep installed
One-click scans. No signup required.
#1 Best Overall
- Read Before You Buy — No Video Output: These adapters support charging and USB 2.0 data transfer, but cannot transmit video signals. Except for standard USB webcams (which use USB data only), they are not compatible with HDMI/DisplayPort cables, video-capable USB-C hubs, or docking stations with video output.
- Convert USB-A Ports to USB-C: Designed to connect USB-C earphones, cables, flash drives, card readers, and other USB-C accessories to standard USB-A ports. Plug-and-play with no drivers or software required.
- Aluminum Alloy Housing: Built with a sturdy aluminum alloy shell that aids in heat dissipation and protects against daily wear and scratches. Designed to maintain a stable and secure connection.
- Compact & Travel-Friendly: The ultra-compact design allows the adapter to stay plugged into your device without blocking adjacent ports or adding bulk, reducing wear and tear on your original USB ports.
- 12-Month Warranty: Backed by a 12-month manufacturer warranty for peace of mind. Designed to meet strict quality control standards for reliable everyday performance.
Choose a dtype deliberately
A specified dtype is a representation constraint, not just a display preference. For example, an integer type with a limited range cannot represent every possible integer. Values outside the selected type’s range can raise an error. Use a type appropriate to the values and operations you need, rather than assuming any numeric dtype can hold any number.
counts = np.array([1, 2, 3], dtype=np.int64)
print(counts.dtype)Make a typed sequence with array.array
When a one-dimensional mutable sequence of basic values is sufficient, Python’s standard library provides array.array. Import it from array and choose a type code; the type code constrains the values stored.
Rank #2
- 5-in-1 USB-C Hub: Experience comprehensive connectivity featuring a Power Delivery input, two USB-A 2.0 ports, a USB-A 3.0 port, and an HDMI port. (Note: The USB-C power delivery input port is only for connecting an external wall charger to power your laptop and cannot power peripheral devices.)
- 90W Pass-Through Charging: Achieve optimal charging with 90W pass-through power to your laptop, supported by a total input of 100W, with the hub reserving 10W for operational efficiency. (Note: Wall charger not included.)
- Quick Data Transfers: Accelerate your productivity with rapid data transfers using a high-speed 5Gbps USB 3.0 port and two 480Mbps USB 2.0 ports.
- 4K HDMI Display: Enhance your visual experience with a hub capable of delivering 4K resolution at 30Hz in both mirror and extend modes. Please note that this hub is compatible with MacBook (macOS 12 and newer), Windows 10 and 11, ChromeOS, and laptops equipped with DP Alt Mode and Power Delivery. Note: This device is not compatible with Linux.
- What You Get: Anker USB-C Hub (5-in-1, 4K HDMI), welcome guide, 18-month warranty, and our friendly customer service.
from array import array
scores = array('i', [10, 20, 30])Type-code sizes can depend on the platform, so do not assume a universal byte layout for every code. In Python 3.14.7, type code 'u' is deprecated and scheduled for removal in Python 3.16; 'w' was added in Python 3.13. Check the documentation for the Python version you support: Python 3.14.7 array reference.
How do shape, ndim, size, and dtype work?
NumPy arrays expose attributes that describe their structure and contents. For the nested example above, there are two rows and three columns:
Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchPC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Rank #3
- Sleek 7-in-1 USB-C Hub: Features an HDMI port, two USB-A 3.0 ports, and a USB-C data port, each providing 5Gbps transfer speeds. It also includes a USB-C PD input port for charging up to 100W and dual SD and TF card slots, all in a compact design.
- Flawless 4K@60Hz Video with HDMI: Delivers exceptional clarity and smoothness with its 4K@60Hz HDMI port, making it ideal for high-definition presentations and entertainment. (Note: Only the HDMI port supports video projection; the USB-C port is for data transfer only.)
- Double Up on Efficiency: The two USB-A 3.0 ports and a USB-C port support a fast 5Gbps data rate, significantly boosting your transfer speeds and improving productivity.
- Fast and Reliable 85W Charging: Offers high-capacity, speedy charging for laptops up to 85W, so you spend less time tethered to an outlet and more time being productive.
- What You Get: Anker USB-C Hub (7-in-1), welcome guide, 18-month warranty, and our friendly customer service.
matrix = np.array([[1, 2, 3], [4, 5, 6]])
print(matrix.shape) # (2, 3)
print(matrix.ndim) # 2
print(matrix.size) # 6
print(matrix.dtype) # element type selected or inferred by NumPyshapeis a tuple giving the length of each dimension. Here,(2, 3)means two entries along the first axis and three along the second.ndimis the number of axes: this matrix has two.sizeis the total number of elements, six in this example.dtypedescribes the element type.
The official ndarray reference covers these properties and multidimensional indexing.
How do I access or slice a NumPy array?
NumPy uses familiar bracket notation. Use a comma to specify indices along separate axes. With matrix above, matrix[1, 2] selects the element in the second row and third column; indices start at zero.
Rank #4
- Dual Converters, Infinite Potential：Includes 2× USB C male to USB A female adapters and 2× USB A male to USB C female adapters. Perfect for a wide range of uses—tablets with Bluetooth keyboards, expand USB ports on macbook, and more. Two different converters for all your daily needs
- Next-Level 10Gbps & 3A Charging: No more slow 480Mbps, this usb to usb c adapter has a transfer speed of up to 10Gbps, allowing you to do more transferring in less time. This usb adapter fits both USB A and USB C charger, supporting up to 3A fast charging
- Upgraded Exquisite Craftsmanship: With an aluminum alloy housing and metal connector, the usbc to usb adapter is extremely durable and sturdy. Rigorously tested to withstand more than 10,000 times of plugging and unplugging, ensuring long-lasting performance
- Broad Compatible: The usb c to usb adapter widely supports all USB C/ USB A devices like laptops, tablets, cellphones, car chargers, and phone chargers. Such as compatible with MacBook Pro/Air 2023/2022, Thunderbolt 4/3 Devices,Apple MagSafe Watch 9/8/7/SE/Ultra, iPad Pro 2022/2021, Samsung Galaxy S23/S20/S10, and iPhone 17/16/15 Pro. Plug and play
- Please Note: To reach 10Gbps speed, keep the cable under 3.3 ft. For USB A Male to USB C adapters, try flipping the USB C connector. USB C Male to USB A adapters support bidirectional 10Gbps transfer within 3.3 ft
print(matrix[1, 2]) # 6
print(matrix[0]) # first row: [1 2 3]
print(matrix[:, 1]) # second column: [2 5]Important: a slice can be a view
A NumPy slice may be a view that shares data with its source rather than an independent copy. For example, assigning through a selected column changes the original array:
column = matrix[:, 1]
column[0] = 99
print(matrix)
# [[ 1 99 3]
# [ 4 5 6]]If you need independent values, explicitly make a copy instead of assuming a slice duplicates the data:
Best Value
- 5-in-1 Connectivity: Equipped with a 4K HDMI port, a 5 Gbps USB-C data port, two 5 Gbps USB-A ports, and a USB C 100W PD-IN port. Note: The USB C 100W PD-IN port supports only charging and does not support data transfer devices such as headphones or speakers.
- Powerful Pass-Through Charging: Supports up to 85W pass-through charging so you can power up your laptop while you use the hub. Note: Pass-through charging requires a charger (not included). Note: To achieve full power for iPad, we recommend using a 45W wall charger.
- Transfer Files in Seconds: Move files to and from your laptop at speeds of up to 5 Gbps via the USB-C and USB-A data ports. Note: The USB C 5Gbps Data port does not support video output.
- HD Display: Connect to the HDMI port to stream or mirror content to an external monitor in resolutions of up to 4K@30Hz. Note: The USB-C ports do not support video output.
- What You Get: Anker 332 USB-C Hub (5-in-1), welcome guide, our worry-free 18-month warranty, and friendly customer service.
independent_column = matrix[:, 1].copy()The NumPy reference explains indexing, slicing, and views: The N-dimensional array (ndarray).
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which Python array should I choose?
- Choose a
listwhen you need a flexible, general-purpose sequence, including one that may contain different kinds of Python objects. - Choose
array.arraywhen you need a mutable, typed, one-dimensional sequence of basic values and its narrower functionality is sufficient. - Choose NumPy’s
ndarrayfor multidimensional numerical data, explicit shape and dtype handling, or array-oriented operations.
NumPy is not part of Python’s standard library; it is a separate package. The NumPy reference identifies itself as version 2.5, released June 28, 2026: NumPy reference.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
