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In Python, “array” can mean a few different things. For the usual list conversion, use list(data) for keys, list(data.values()) for values, or list(data.items()) for key/value tuples. If you specifically need a NumPy array, first select the dictionary content you want and pass that sequence to np.array().
Choose what you want the result to contain
Given this dictionary:
data = {"name": "Ada", "age": 36}Use the expression that matches the desired output:
| Desired result | Expression | What each element contains |
|---|---|---|
| Keys | list(data) or list(data.keys()) |
One key per element |
| Values | list(data.values()) |
One value per element, in the same insertion order as the keys |
| Key/value pairs | list(data.items()) |
A two-element (key, value) tuple for each entry |
| NumPy array of values | np.array(list(data.values())) |
An ndarray created from the values sequence |
keys = list(data) # ["name", "age"]
values = list(data.values()) # ["Ada", 36]
pairs = list(data.items()) # [("name", "Ada"), ("age", 36)]Convert dictionary keys, values, or pairs to a list
Get the keys
list(data) returns the dictionary’s keys. You can also write list(data.keys()); both produce a list of keys.
Get the values
Call values() and wrap its result in list() to materialize the values as a list:
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values = list(data.values())Keep each key associated with its value
Use items() when each value needs to remain associated with its key:
pairs = list(data.items())The result contains tuples such as ("name", "Ada"). Calling data.items() by itself returns a dictionary view, not a list. Python documents keys, values, and items as views, which can be iterated directly; wrapping one in list() creates a separate, materialized list. See the Python dictionary documentation.
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Understand order and dictionary views
Dictionary iteration follows insertion order. That behavior is guaranteed for dictionaries in Python 3.7 and later, but it does not sort entries by key. The Python documentation states, “Dictionary order is guaranteed to be insertion order.” If you need sorted keys, sort them explicitly rather than relying on conversion:
sorted_keys = sorted(data)When you only need to process entries and do not need indexing or a stored snapshot, iterate over the view directly:
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for key, value in data.items():
print(key, value)Create a NumPy array from dictionary contents
NumPy creates ndarrays from sequences such as lists and tuples. Choose the dictionary content first, then pass that sequence to np.array(). For example, to create an array from numeric values:
import numpy as np
scores = {"Ada": 98, "Lin": 91}
values = np.array(list(scores.values()))A list of numbers produces a one-dimensional array; a list of lists can produce a two-dimensional array. A dictionary, however, can map keys to arbitrary objects, so its contents do not automatically form a useful homogeneous numeric array. Mixed or irregular nested values may need to be transformed or represented differently for the operation you intend.
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For named, record-like fields, NumPy provides structured arrays. Its documentation also notes that other projects may be more suitable for tabular-data manipulation; see NumPy structured arrays.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When to use Python’s typed array
Python’s standard-library array module provides typed arrays, distinct from both a list and NumPy’s ndarray. Consider it when the data are supported primitive values and you specifically need typed-array behavior. For a simple dictionary conversion, a list is usually the most direct choice. The Python array module documentation covers its supported operations, including converting an array back to a regular list.
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Common conversion mistakes
list(data)produces keys, not values; uselist(data.values())for values.data.items()is a view, not a list; uselist(data.items())when you need a materialized list.- Dictionary order is insertion order, not sorted order. Sort explicitly when alphabetical or numeric key order is required.
- A Python list, a NumPy ndarray, and an
array.arrayare different types. Choose the one required by the next operation or API. - If keys and values must stay together, convert the items rather than extracting only keys or only values.
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