Python Lists: A Quick Reference π
* Definition: Lists are ordered, mutable collections that can contain various data types and duplicates.
* Creating Lists: Creating empty, numerical, mixed, nested lists, and lists with duplicates.
* Accessing List Elements: Accessing elements using positive and negative indexing, as well as slicing with
.
* Common Operations: Adding, inserting, concatenating, deleting, clearing, searching, sorting, and reversing lists.
* List Methods:
,
,
,
,
,
,
,
,
, and
.
* List Comprehension: Quickly creating lists using expressions and conditions.
* List vs. Tuple: Differences between mutable lists and immutable tuples.
* Important Points: Specifics of indexing, slicing, data types, and working with lists.
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* Definition: Lists are ordered, mutable collections that can contain various data types and duplicates.
* Creating Lists: Creating empty, numerical, mixed, nested lists, and lists with duplicates.
* Accessing List Elements: Accessing elements using positive and negative indexing, as well as slicing with
start:end:step
.
* Common Operations: Adding, inserting, concatenating, deleting, clearing, searching, sorting, and reversing lists.
* List Methods:
append()
,
insert()
,
extend()
,
remove()
,
pop()
,
clear()
,
index()
,
count()
,
sort()
, and
reverse()
.
* List Comprehension: Quickly creating lists using expressions and conditions.
* List vs. Tuple: Differences between mutable lists and immutable tuples.
* Important Points: Specifics of indexing, slicing, data types, and working with lists.
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1. Think Python β OβReilly
https://t.co/X7y3pX68IW
2. The Big Book of Small Python Projects
https://inventwithpython.com/bigbookpython/
3. Data Structures
https://opendatastructures.org/ods-python.pdf
4. Data Science Handbook
https://t.co/9aOLdiAbim
5. Data Analysis
https://wesmckinney.com/book/
6. Data Science
https://t.co/TusyBWGfrx
7. Machine Learning
https://t.co/7veOwESe8q
8. Statistics
https://t.co/waWDQylQpY
9. Think Bayes
https://allendowney.github.io/ThinkBayes2/
10. Clean Code in Python β Packt
https://t.co/OHhVgF1L65
#Python #FreeBooks #Programming #DataScience #MachineLearning #Coding
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https://substack.com/@husseinsheikho?utm_source=share&utm_medium=android&r=3hwnr8
Follow me to more posts and useful content
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In Python 3.15, a single asterisk replaces nested loops. πβ¨
Previously, to flatten a list, you would write:
Now, you can simply use:
A double asterisk merges dictionaries: π¦
When keys overlap, the last value wins β this is convenient for combining settings from multiple sources. βοΈ
Unpacking removes one level of nesting. In Python 3.14, this syntax within comprehensions will raise a
https://peps.python.org/pep-0798/
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Previously, to flatten a list, you would write:
rows = [[1, 2], [3], [4, 5]]
flat = [x for row in rows for x in row]
Now, you can simply use:
flat = [*row for row in rows]
# [1, 2, 3, 4, 5]
A double asterisk merges dictionaries: π¦
configs = [
{"debug": False, "timeout": 10},
{"timeout": 30},
]
config = {**part for part in configs}
# {'debug': False, 'timeout': 30}
When keys overlap, the last value wins β this is convenient for combining settings from multiple sources. βοΈ
Unpacking removes one level of nesting. In Python 3.14, this syntax within comprehensions will raise a
SyntaxError. π«https://peps.python.org/pep-0798/
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Python Enhancement Proposals (PEPs)
PEP 798 β Unpacking in Comprehensions | peps.python.org
This PEP proposes extending list, set, and dictionary comprehensions, as well as generator expressions, to allow unpacking notation (* and **) at the start of the expression, providing a concise way of combining an arbitrary number of iterables into one...
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