# Python | Using 2D Arrays / Lists the Right Way

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Method 1a

 ` # First way to create 1 D array ` ` N ` ` = ` ` 5 ` ` arr ` ` = ` ` [` ` 0 ` `] ` ` * ` ` N ` ` print ` ` (arr) `

Output:

` [0, 0, 0, 0, 0] `

Method 1b

 ` # Second way to create array 1 D ` ` N ` ` = ` ` 5 ` ` arr ` ` = ` ` [` ` 0 ` ` for ` ` i ` ` in ` ` range ` ` (N)] ` ` print ` ` (arr) `

Exit:

` [0, 0, 0, 0, 0 ] `

Extending the above, we can define 2-dimensional arrays in the following ways.
Method 2a

 ` # Using the above first method to create ` ` # 2D array ` ` rows, cols ` ` = ` ` (` ` 5 ` `, ` ` 5 ` `) ` ` arr ` ` = ` ` [[` ` 0 ` `] ` ` * ` ` cols] ` ` * ` ` rows ` ` print ` ` (arr) `

Exit:

` [[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0 ], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]] `

Method 2b

 ` # Using the above second method to create ` ` # 2D array ` ` rows, cols ` ` = ` ` (` ` 5 ` `, ` ` 5 ` `) ` ` arr ` ` = ` ` [[` ` 0 ` ` for ` ` i ` ` in ` ` range ` ` (cols)] ` ` for ` ` j ` ` in ` ` range ` ` (rows)] ` ` print ` ` (arr) `

Output:

` [[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]] `

Both methods seem to give the same result as now. Let’s replace one of the elements in the array of method 2a and method 2b.

 ` # Python 3 program to demonstrate how it works ` ` # method 1 and method 2. ` ` ` ` rows , cols ` ` = ` ` (` ` 5 ` `, ` ` 5 ` `) ` ` ` ` # method 2a ` ` arr ` ` = ` ` [[` ` 0 ` `] ` ` * ` ` cols] ` ` * ` ` rows ` ` # change the first element ` ` # first line to 1 and print the array ` ` arr [` ` 0 ` `] [` ` 0 ` `] ` ` = ` ` 1 ` ` ` ` for ` ` row ` ` in ` ` arr: ` ` print ` ` (row) ` ` # outputs the following ` ` # [1, 0, 0, 0, 0] ` ` # [1, 0, 0, 0, 0] ` ` # [1, 0, 0, 0, 0] ` ` # [1, 0, 0, 0, 0] ` ` # [1, 0, 0, 0, 0] ` ` # method 2b ` ` arr ` ` = ` ` [[` ` 0 ` ` for ` ` i ` ` in ` ` range ` ` (cols)] ` ` for ` ` j ` ` in ` ` range ` ` (rows)] ` ` # back to this new array lets you change ` ` # first element of the first row ` ` # to 1 and print the array ` ` arr [` ` 0 ` `] [` ` 0 ` `] ` ` = ` ` 1 ` ` for ` ` row ` ` in ` ` arr: ` ` print ` ` (row) ` ` # outputs the following as expected ` ` # [1, 0, 0, 0, 0] ` ` # [0, 0, 0, 0, 0] ` ` # [0, 0, 0, 0, 0] ` ` # [0, 0, 0, 0, 0] ` ` # [0, 0, 0, 0, 0] `

Exit:

` [1, 0, 0, 0, 0] [1, 0, 0, 0, 0] [1, 0, 0 , 0, 0] [1, 0, 0, 0, 0] [1, 0, 0, 0, 0] [1, 0, 0, 0, 0] [0, 0, 0, 0, 0] [ 0, 0, 0, 0, 0] [0, 0, 0, 0, 0] [0, 0, 0, 0, 0] `

We expect only the first element of the first line to change to 1, but the first element of each line will change to 1 in method 2a. This kind of functioning is due to the fact that Python uses shallow lists, which we will try to understand.

In method 1a, Python does not create 5 integer objects, but only creates one integer object, and all indexes of the arr array point to the same an int object as shown.

If we assign 0th index to another integer, say 1, then a new integer object is created with the value 1, and then 0th index now points to this new int object as shown below

Likewise, when we create a two-dimensional array like" arr = [[0] * cols] * row ", we are in fact, we are expanding the above analogy.
1. Only one integer object is created.
2. One list 1d is created, and all of its indices point to the same int object at point 1.
3. Now arr [0], arr [1], arr [2]‚Ä¶. arr [n-1] all point to the same list object above in step 2.

The above setting can be visualized in the image below.

Now let’s change the first element in the first line" arr "as
arr [0] [0] = 1

= & gt; arr [0] points to the same list object we created above (remember that arr [1], arr [2]‚Ä¶ arr [n-1] also point to the same list object)
= & gt ; Assigning arr [0] [0] will create a new int object with a value of 1, and arr [0] [0] will now point to this new int object. (And so it will be arr [1] [0], arr [2] [0]‚Ä¶ arr [n-1] [0])

This can be clearly seen in the image below.

So when 2d arrays are created in this way, changing the values ‚Äã‚Äãin a certain line will affect all strings, since there is essentially only one integer object and only one list object referenced by all the rows in the array.

As you would expect, track down errors caused by this use of shallow lists. complicated. Hence the best way to declare a 2d array is

 ` rows, cols ` ` = ` ` (` ` 5 ` `, ` ` 5 ` `) ` ` arr ` ` = ` ` [[` ` 0 ` ` for ` ` i ` ` in ` ` range ` ` (cols)] ` ` for ` ` j ` ` in ` ` range ` ` (rows )] `

Exit:

` `

This method creates 5 separate list objects as opposed to method 2a. One way to check this — use the "is" operator, which checks if two operands refer to the same object.

 ` rows, cols ` ` = ` ` (` ` 5 ` `, ` ` 5 ` `) ` ` # method 2b ` ` arr ` ` = ` ` [[` ` 0 ` ` for ` ` i ` ` in ` ` range ` ` (cols)] ` ` for ` ` j ` ` in ` ` range ` ` (rows)] ` ` # check if arr [0] and arr [1] refer to ` ` # same object ` ` print ` ` (arr [` ` 0 ` `] ` ` is ` ` arr [` ` 1 ` `] ) ` ` # prints False ` ` # method 2a ` ` arr ` ` = ` ` [[` ` 0 ` `] ` ` * ` ` cols] ` ` * ` ` rows ` ` ` ` # check if arr [0] and arr [1] refer to ` ` # that same object ` ` # prints True because there is only one ` ` # list of the object to create. ` ` print ` ` (arr [` ` 0 ` `] ` ` is ` ` arr [` ` 1 ` `]) `

Exit:

` False True `

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How do I merge two dictionaries in a single expression (taking union of dictionaries)?

By Carl Meyer

I have two Python dictionaries, and I want to write a single expression that returns these two dictionaries, merged (i.e. taking the union). The `update()` method would be what I need, if it returned its result instead of modifying a dictionary in-place.

``````>>> x = {"a": 1, "b": 2}
>>> y = {"b": 10, "c": 11}
>>> z = x.update(y)
>>> print(z)
None
>>> x
{"a": 1, "b": 10, "c": 11}
``````

How can I get that final merged dictionary in `z`, not `x`?

(To be extra-clear, the last-one-wins conflict-handling of `dict.update()` is what I"m looking for as well.)

5839

## How can I merge two Python dictionaries in a single expression?

For dictionaries `x` and `y`, `z` becomes a shallowly-merged dictionary with values from `y` replacing those from `x`.

• In Python 3.9.0 or greater (released 17 October 2020): PEP-584, discussed here, was implemented and provides the simplest method:

``````z = x | y          # NOTE: 3.9+ ONLY
``````
• In Python 3.5 or greater:

``````z = {**x, **y}
``````
• In Python 2, (or 3.4 or lower) write a function:

``````def merge_two_dicts(x, y):
z.update(y)    # modifies z with keys and values of y
return z
``````

and now:

``````z = merge_two_dicts(x, y)
``````

### Explanation

Say you have two dictionaries and you want to merge them into a new dictionary without altering the original dictionaries:

``````x = {"a": 1, "b": 2}
y = {"b": 3, "c": 4}
``````

The desired result is to get a new dictionary (`z`) with the values merged, and the second dictionary"s values overwriting those from the first.

``````>>> z
{"a": 1, "b": 3, "c": 4}
``````

A new syntax for this, proposed in PEP 448 and available as of Python 3.5, is

``````z = {**x, **y}
``````

And it is indeed a single expression.

Note that we can merge in with literal notation as well:

``````z = {**x, "foo": 1, "bar": 2, **y}
``````

and now:

``````>>> z
{"a": 1, "b": 3, "foo": 1, "bar": 2, "c": 4}
``````

It is now showing as implemented in the release schedule for 3.5, PEP 478, and it has now made its way into the What"s New in Python 3.5 document.

However, since many organizations are still on Python 2, you may wish to do this in a backward-compatible way. The classically Pythonic way, available in Python 2 and Python 3.0-3.4, is to do this as a two-step process:

``````z = x.copy()
z.update(y) # which returns None since it mutates z
``````

In both approaches, `y` will come second and its values will replace `x`"s values, thus `b` will point to `3` in our final result.

## Not yet on Python 3.5, but want a single expression

If you are not yet on Python 3.5 or need to write backward-compatible code, and you want this in a single expression, the most performant while the correct approach is to put it in a function:

``````def merge_two_dicts(x, y):
"""Given two dictionaries, merge them into a new dict as a shallow copy."""
z = x.copy()
z.update(y)
return z
``````

and then you have a single expression:

``````z = merge_two_dicts(x, y)
``````

You can also make a function to merge an arbitrary number of dictionaries, from zero to a very large number:

``````def merge_dicts(*dict_args):
"""
Given any number of dictionaries, shallow copy and merge into a new dict,
precedence goes to key-value pairs in latter dictionaries.
"""
result = {}
for dictionary in dict_args:
result.update(dictionary)
return result
``````

This function will work in Python 2 and 3 for all dictionaries. e.g. given dictionaries `a` to `g`:

``````z = merge_dicts(a, b, c, d, e, f, g)
``````

and key-value pairs in `g` will take precedence over dictionaries `a` to `f`, and so on.

Don"t use what you see in the formerly accepted answer:

``````z = dict(x.items() + y.items())
``````

In Python 2, you create two lists in memory for each dict, create a third list in memory with length equal to the length of the first two put together, and then discard all three lists to create the dict. In Python 3, this will fail because you"re adding two `dict_items` objects together, not two lists -

``````>>> c = dict(a.items() + b.items())
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for +: "dict_items" and "dict_items"
``````

and you would have to explicitly create them as lists, e.g. `z = dict(list(x.items()) + list(y.items()))`. This is a waste of resources and computation power.

Similarly, taking the union of `items()` in Python 3 (`viewitems()` in Python 2.7) will also fail when values are unhashable objects (like lists, for example). Even if your values are hashable, since sets are semantically unordered, the behavior is undefined in regards to precedence. So don"t do this:

``````>>> c = dict(a.items() | b.items())
``````

This example demonstrates what happens when values are unhashable:

``````>>> x = {"a": []}
>>> y = {"b": []}
>>> dict(x.items() | y.items())
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unhashable type: "list"
``````

Here"s an example where `y` should have precedence, but instead the value from `x` is retained due to the arbitrary order of sets:

``````>>> x = {"a": 2}
>>> y = {"a": 1}
>>> dict(x.items() | y.items())
{"a": 2}
``````

Another hack you should not use:

``````z = dict(x, **y)
``````

This uses the `dict` constructor and is very fast and memory-efficient (even slightly more so than our two-step process) but unless you know precisely what is happening here (that is, the second dict is being passed as keyword arguments to the dict constructor), it"s difficult to read, it"s not the intended usage, and so it is not Pythonic.

Here"s an example of the usage being remediated in django.

Dictionaries are intended to take hashable keys (e.g. `frozenset`s or tuples), but this method fails in Python 3 when keys are not strings.

``````>>> c = dict(a, **b)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: keyword arguments must be strings
``````

From the mailing list, Guido van Rossum, the creator of the language, wrote:

I am fine with declaring dict({}, **{1:3}) illegal, since after all it is abuse of the ** mechanism.

and

Apparently dict(x, **y) is going around as "cool hack" for "call x.update(y) and return x". Personally, I find it more despicable than cool.

It is my understanding (as well as the understanding of the creator of the language) that the intended usage for `dict(**y)` is for creating dictionaries for readability purposes, e.g.:

``````dict(a=1, b=10, c=11)
``````

``````{"a": 1, "b": 10, "c": 11}
``````

Despite what Guido says, `dict(x, **y)` is in line with the dict specification, which btw. works for both Python 2 and 3. The fact that this only works for string keys is a direct consequence of how keyword parameters work and not a short-coming of dict. Nor is using the ** operator in this place an abuse of the mechanism, in fact, ** was designed precisely to pass dictionaries as keywords.

Again, it doesn"t work for 3 when keys are not strings. The implicit calling contract is that namespaces take ordinary dictionaries, while users must only pass keyword arguments that are strings. All other callables enforced it. `dict` broke this consistency in Python 2:

``````>>> foo(**{("a", "b"): None})
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: foo() keywords must be strings
>>> dict(**{("a", "b"): None})
{("a", "b"): None}
``````

This inconsistency was bad given other implementations of Python (PyPy, Jython, IronPython). Thus it was fixed in Python 3, as this usage could be a breaking change.

I submit to you that it is malicious incompetence to intentionally write code that only works in one version of a language or that only works given certain arbitrary constraints.

`dict(x.items() + y.items())` is still the most readable solution for Python 2. Readability counts.

My response: `merge_two_dicts(x, y)` actually seems much clearer to me, if we"re actually concerned about readability. And it is not forward compatible, as Python 2 is increasingly deprecated.

`{**x, **y}` does not seem to handle nested dictionaries. the contents of nested keys are simply overwritten, not merged [...] I ended up being burnt by these answers that do not merge recursively and I was surprised no one mentioned it. In my interpretation of the word "merging" these answers describe "updating one dict with another", and not merging.

Yes. I must refer you back to the question, which is asking for a shallow merge of two dictionaries, with the first"s values being overwritten by the second"s - in a single expression.

Assuming two dictionaries of dictionaries, one might recursively merge them in a single function, but you should be careful not to modify the dictionaries from either source, and the surest way to avoid that is to make a copy when assigning values. As keys must be hashable and are usually therefore immutable, it is pointless to copy them:

``````from copy import deepcopy

def dict_of_dicts_merge(x, y):
z = {}
overlapping_keys = x.keys() & y.keys()
for key in overlapping_keys:
z[key] = dict_of_dicts_merge(x[key], y[key])
for key in x.keys() - overlapping_keys:
z[key] = deepcopy(x[key])
for key in y.keys() - overlapping_keys:
z[key] = deepcopy(y[key])
return z
``````

Usage:

``````>>> x = {"a":{1:{}}, "b": {2:{}}}
>>> y = {"b":{10:{}}, "c": {11:{}}}
>>> dict_of_dicts_merge(x, y)
{"b": {2: {}, 10: {}}, "a": {1: {}}, "c": {11: {}}}
``````

Coming up with contingencies for other value types is far beyond the scope of this question, so I will point you at my answer to the canonical question on a "Dictionaries of dictionaries merge".

## Less Performant But Correct Ad-hocs

These approaches are less performant, but they will provide correct behavior. They will be much less performant than `copy` and `update` or the new unpacking because they iterate through each key-value pair at a higher level of abstraction, but they do respect the order of precedence (latter dictionaries have precedence)

You can also chain the dictionaries manually inside a dict comprehension:

``````{k: v for d in dicts for k, v in d.items()} # iteritems in Python 2.7
``````

or in Python 2.6 (and perhaps as early as 2.4 when generator expressions were introduced):

``````dict((k, v) for d in dicts for k, v in d.items()) # iteritems in Python 2
``````

`itertools.chain` will chain the iterators over the key-value pairs in the correct order:

``````from itertools import chain
z = dict(chain(x.items(), y.items())) # iteritems in Python 2
``````

## Performance Analysis

I"m only going to do the performance analysis of the usages known to behave correctly. (Self-contained so you can copy and paste yourself.)

``````from timeit import repeat
from itertools import chain

x = dict.fromkeys("abcdefg")
y = dict.fromkeys("efghijk")

def merge_two_dicts(x, y):
z = x.copy()
z.update(y)
return z

min(repeat(lambda: {**x, **y}))
min(repeat(lambda: merge_two_dicts(x, y)))
min(repeat(lambda: {k: v for d in (x, y) for k, v in d.items()}))
min(repeat(lambda: dict(chain(x.items(), y.items()))))
min(repeat(lambda: dict(item for d in (x, y) for item in d.items())))
``````

In Python 3.8.1, NixOS:

``````>>> min(repeat(lambda: {**x, **y}))
1.0804965235292912
>>> min(repeat(lambda: merge_two_dicts(x, y)))
1.636518670246005
>>> min(repeat(lambda: {k: v for d in (x, y) for k, v in d.items()}))
3.1779992282390594
>>> min(repeat(lambda: dict(chain(x.items(), y.items()))))
2.740647904574871
>>> min(repeat(lambda: dict(item for d in (x, y) for item in d.items())))
4.266070580109954
``````
``````\$ uname -a
Linux nixos 4.19.113 #1-NixOS SMP Wed Mar 25 07:06:15 UTC 2020 x86_64 GNU/Linux
``````

## Resources on Dictionaries

5839

In your case, what you can do is:

``````z = dict(list(x.items()) + list(y.items()))
``````

This will, as you want it, put the final dict in `z`, and make the value for key `b` be properly overridden by the second (`y`) dict"s value:

``````>>> x = {"a":1, "b": 2}
>>> y = {"b":10, "c": 11}
>>> z = dict(list(x.items()) + list(y.items()))
>>> z
{"a": 1, "c": 11, "b": 10}

``````

If you use Python 2, you can even remove the `list()` calls. To create z:

``````>>> z = dict(x.items() + y.items())
>>> z
{"a": 1, "c": 11, "b": 10}
``````

If you use Python version 3.9.0a4 or greater, then you can directly use:

``````x = {"a":1, "b": 2}
y = {"b":10, "c": 11}
z = x | y
print(z)
``````
``````{"a": 1, "c": 11, "b": 10}
``````

5839

An alternative:

``````z = x.copy()
z.update(y)
``````

We hope this article has helped you to resolve the problem. Apart from Python | Using 2D Arrays / Lists the Right Way, check other Arrays-related topics.

Want to excel in Python? See our review of the best Python online courses 2022. If you are interested in Data Science, check also how to learn programming in R.

By the way, this material is also available in other languages:

Davies Wu

Prague | 2022-12-08

Maybe there are another answers? What Python | Using 2D Arrays / Lists the Right Way exactly means?. Will use it in my bachelor thesis

Angelo Gonzalez

Milan | 2022-12-08

I was preparing for my coding interview, thanks for clarifying this - Python | Using 2D Arrays / Lists the Right Way in Python is not the simplest one. Checked yesterday, it works!

Olivia Robinson

Moscow | 2022-12-08

Thanks for explaining! I was stuck with Python | Using 2D Arrays / Lists the Right Way for some hours, finally got it done 🤗. Checked yesterday, it works!

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