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Sequence Containers Indexing
Base Types
Python 3 Cheat Sheet
©2012-2015 - Laurent Pointal License Creative Commons Attribution 4
Latest version on : https://perso.limsi.fr/pointal/python:memento
int 783 0 -
float 9.23 0.0 -1.7e- bool True False
"One\nTwo"
'I'm'
str
"""X\tY\tZ
1\t2\t3"""
× 10 -
escaped tab
escaped new line
Multiline string:
Container Types
list [^1 ,^5 ,^9 ]^ ["x",^11 ,8.9]^ ["mot"]^ [] tuple (^1 ,^5 ,^9 )^11 ,"y",7.4^ ("mot",)^ ()
dict
{ 1 :"one", 3 :"three", 2 :"two",3.14:"π"}
{"key":"value"}
set
◾ ordered sequences , fast index access, repeatable values
set()
◾ key containers , no a priori order, fast key access, each key is unique
{"key1","key2"}
Non modifiable values (immutables)
Variables assignment
x=1.2+ 8 +sin(y)
y,z,r=9.2,-7.6, 0
a…zA…Z_ followed by a…zA…Z_0… 9
◽ diacritics allowed but should be avoided
◽ language keywords forbidden
◽ lower/UPPER case discrimination
☝ expression with only comas → tuple
dictionary
collection
integer, float, boolean, string, bytes
Identifiers
☺ a toto x7 y_max BigOne ☹ 8y and for
x+= 3 x-= 2
increment ⇔ x=x+ 3
decrement ⇔ x=x- 2
Conversions
for lists, tuples, strings, bytes…
int("15") → 15 int("3f", 16 ) → 63 can specify integer number base in 2nd^ parameter int(15.56) → 15 truncate decimal part float("-11.24e8") → -1124000000. round(15.56, 1 )→ 15.6 rounding to 1 decimal (0 decimal → integer number) bool(x) False for null x, empty container x , None or False x ; True for other x str(x)→ "…" representation string of x for display (cf. formatting on the back) chr( 64 )→'@' ord('@')→ 64 code ↔ char repr(x)→ "…" literal representation string of x bytes([ 72 , 9 , 64 ]) → b'H\t@' list("abc") → ['a','b','c'] dict([( 3 ,"three"),( 1 ,"one")]) → { 1 :'one', 3 :'three'} set(["one","two"]) → {'one','two'} separator str and sequence of str → assembled str ':'.join(['toto','12','pswd']) → 'toto:12:pswd' str splitted on whitespaces → list of str "words with spaces".split() → ['words','with','spaces'] str splitted on separator str → list of str "1,4,8,2".split(",") → ['1','4','8','2'] sequence of one type → list of another type (via list comprehension) [int(x) for x in ('1','29','-3')] → [ 1 , 29 ,-3]
type( expression )
lst=[10, 20, 30, 40, 50]
lst[ 1 ] → 20 lst[-2] → 40
-5 -4 -3 -2 -1 Individual access to items via lst[ index ]
positive index
negative index
negative slice -5 -4 -3 -2 -
positive slice
Access to sub-sequences via lst[ start slice : end slice : step ]
len(lst) → 5
lst[ 1 : 3 ]→[20,30]
lst[:: 2 ]→[10,30,50]
lst[-3:-1]→[30,40]
lst[:-1]→[10,20,30,40] lst[:^3 ]→[10,20,30] lst[ 1 :-1]→[20,30,40] lst[^3 :]→[40,50] lst[:]→[10,20,30,40,50]
Missing slice indication → from start / up to end.
On mutable sequences ( list ), remove with del lst[ 3 : 5 ] and modify with assignment lst[ 1 : 4 ]=[15,25]
Conditional Statement
if age<= 18 : state="Kid" elif age> 65 : state="Retired" else: state="Active"
Boolean Logic Statements Blocks
parent statement : statement block 1… ⁝ parent statement : statement block2… ⁝
next statement after block 1
indentation!
Comparisons : < > <= >= == !=
a and b
a or b
not a
logical and
logical or
logical not
one or other or both
both simulta- -neously
if logical condition :
statements block
statement block executed only
if a condition is true
Can go with several elif , elif ... and only one final else. Only the block of first true condition is executed.
lst[-1] → 50
lst[ 0 ] → 10 ⇒ last one
⇒ first one
x=None « undefined » constant value
Maths
Operators: + - * / // % **
× ÷
integer ÷ ÷ remainder
ab^
from math import sin,pi…
sin(pi/4)→0.707… cos(2pi/3)→-0.4999… sqrt(81)→9.0 √ log(e*2)→2. ceil(12.5)→ floor(12.5)→
escaped '
☝ floating numbers… approximated values angles in radians
abs(-3.2)→3.
round(3.57, 1 )→3.
pow( 4 , 3 )→64.
for variables, functions, modules, classes… names
Mémento v2.0.
str (ordered sequences of chars / bytes)
(key/value associations)
☝ pitfall : and and or return value of a or of b (under shortcut evaluation). ⇒ ensure that a and b are booleans.
(boolean results)
a=b=c= 0 assignment to same value multiple assignments a,b=b,a values swap a,*b=seq *a,b=seq
unpacking of sequence in item and list
bytes
bytes
b"toto\xfe\775"
hexadecimal octal
0b010 0o642 0xF
binary octal hexa
empty
dict(a=3,b=4,k="v")
Items count
☝ keys=hashable values (base types, immutables…)
True
False True and False constants^
☝ configure editor to insert 4 spaces in place of an indentation tab.
lst[::-1]→[50,40,30,20,10] lst[::-2]→[50,30,10]
_1) evaluation of right side expression value
- assignment in order with left side names_
= ☝ assignment ⇔ binding of a name with a value
☝ immutables
On mutable sequences ( list ), remove with
del lst[ 3 ] and modify with assignment
lst[ 4 ]= 25
del x remove name x
b""
@ → matrix × python3.5+ numpy
☝ index from 0
(here from 0 to 4)
frozenset immutable set
Priority (…)
☝ usual order of operations
modules math, statistics, random, decimal, fractions, numpy, etc. (cf. doc)
Modules/Names Imports
from monmod import nom1,nom2 as fct
module truc ⇔file truc.py
→direct access to names, renaming with as
import monmod →access via monmod.nom1 …
☝ modules and packages searched in python path (cf sys.path)
?
yes no
shallow copy of sequence
?
yes no
and *= /= %= …
☝ with a var x : if bool(x)==True: ⇔ if x: if bool(x)==False: ⇔ if not x:
raise ExcClass(…)
Signaling an error:
Errors processing:
try:
normal procesising block
except Exception as e:
error processing block
normal
processing
error processing error processing
raise X() raise
zero
☝ finally block for final processing in all cases.
Exceptions on Errors
"modele{} {} {}".format(x,y,r)
"{ selection : formatting! conversion }"
◽ Selection : 2 nom 0.nom 4[key] 0[2]
str
print("v=", 3 ,"cm :",x,",",y+ 4 )^ Display
print options:
◽ sep=" " items separator, default space
◽ end="\n" end of print, default new line
◽ file=sys.stdout print to file, default standard output
items to display : literal values, variables, expressions
loop on dict/set ⇔ loop on keys sequences use slices to loop on a subset of a sequence
statements block executed as long as^ Conditional Loop Statement
condition is true
while logical condition : statements block
s = 0 i = 1
while i <= 100 : s = s + i** 2 i = i + 1 print("sum:",s)
initializations before the loop condition with a least one variable value (here i )
s = (^) ∑ i = 1
i = 100 i
2 ☝ make condition variable change!
statements block executed for each
item of a container or iterator
for var in sequence : statements block
s = "Some text" cnt = 0
for c in s: if c == "e": cnt = cnt + 1 print("found",cnt,"'e'")
Go over sequence's values
Algo: count number of e in the string.
Go over sequence's index
◽ modify item at index
◽ access items around index (before / after)
lst = [11,18,9,12,23,4,17] lost = [] for idx in range(len(lst)): val = lst[idx] if val > 15 : lost.append(val) lst[idx] = 15 print("modif:",lst,"-lost:",lost)
Algo: limit values greater than 15, memorizing of lost values.
☝^
beware of infinite loops
initializations before the loop
loop variable, assignment managed by for statement
formating directives values to format
Integer Sequences
Files
s = input("Instructions:")
☝ input always returns a string , convert it to required type
(cf. boxed Conversions on the other side).
range( 5 )→ 0 1 2 3 4 range( 2 , 12 , 3 )→ 2 5 8 11 range( 3 , 8 )→ 3 4 5 6 7 range( 20 , 5 ,-5)→ 20 15 10 range(len( seq )) → sequence of index of values in seq ☝ range provides an immutable sequence of int constructed as needed
range( [start,] end [,step] )
f = open("file.txt","w",encoding="utf8")
storing data on disk, and reading it back
opening mode ◽ 'r' read ◽ 'w' write ◽ 'a' append ◽ …'+' 'x' 'b' 't'
encoding of chars for text files : utf8 ascii latin1 …
name of file on disk (+path…)
file variable for operations
f.write("coucou") f.writelines( list of lines )
writing reading
f.read( [n] ) → next chars
if n not specified, read up to end! f.readlines( [n] ) → list of next lines f.readline() → next line
with open(…) as f:
for line in f :
# processing of line
cf. modules os, os.path and pathlib
f.close() ☝ dont forget to close the file after use!
Very common: opening with a guarded block (automatic closing) and reading loop on lines of a text file:
Function Definition
def fct(x,y,z): """documentation""" # statements block, res computation, etc. return res
function name (identifier)
result value of the call, if no computed result to return: return None ☝ parameters and all variables of this block exist only in the block and during the function call (think of a “black box ” )
named parameters
r = fct( 3 ,i+ 2 , 2 *i) Function Call
☝ read empty string if end of file
len(c)→ items count
min(c) max(c) sum(c)
sorted(c)→ list sorted copy
val in c → boolean, membership operator in (absence not in)
enumerate(c)→ iterator on (index, value)
zip(c1,c2…)→ iterator on tuples containing ci items at same index
all(c)→ True if all c items evaluated to true, else False
any(c)→ True if at least one item of c evaluated true, else False
☝ modify original list
lst.append( val ) add item at end
lst.extend( seq ) add sequence of items at end
lst.insert( idx , val ) insert item at index
lst.remove( val ) remove first item with value val
lst.pop( [idx] ) →value remove & return item at index idx (default last)
lst.sort() lst.reverse() sort / reverse liste in place
"{:+2.3f}".format(45.72793) →'+45.728' "{1:>10s}".format( 8 ,"toto") →' toto' "{x!r}".format(x="I'm") →'"I'm"'
☝ start default 0, end not included in sequence, step signed, default 1
◽ Conversion : s (readable text) or r (literal representation)
< > ^ = 0 at start for filling with 0 integer: b binary, c char, d decimal (default), o octal, x or X hexa… float: e or E exponential, f or F fixed point, g or G appropriate (default), string: s … % percent
◽ Formatting : fill char alignment sign mini width. precision~maxwidth type
Operations on Dictionaries Operations on Sets
Operators: | → union (vertical bar char) & → intersection
- ^ → difference/symmetric diff. < <= > >= → inclusion relations Operators also exist as methods.
d.update( d2 ) update/add
associations
Note: For dictionaries and sets, these operations use keys.
Specific to ordered sequences containers (lists, tuples, strings, bytes…)
reversed(c) → inversed iterator c* 5 → duplicate c+c2→ concatenate
c.index( val ) → position c.count( val ) → events count
Operations on Lists
d[ key ]= value
d[ key ] → value
d.keys()
d.values()
d.items()
d.clear()
del d[ key ]
→iterable views on
keys/values/associations
Examples
d.pop( key[,default] ) → value
d.popitem() → (key,value)
d.get( key[,default] ) → value
d.setdefault( key[,default] ) →value
s.update( s2 ) s.copy()
s.add( key ) s.remove( key )
s.discard( key ) s.clear()
s.pop()
Loop Control
Go simultaneously over sequence's index and values :
for idx,val in enumerate(lst):
☝^
good habit : don't modify loop variable
Advanced: def fct(x,y,z,args,a= 3 ,b= 5 ,kwargs): _args variable positional arguments (→_ tuple ), default values, **kwargs variable named arguments (→ dict )
one argument per parameter
storage/use of returned value
Algo:
f.flush() write cache
f.tell() →position
reading/writing progress sequentially in the file, modifiable with:
f.seek( position[,origin] )
f.truncate( [size] ) resize
Advanced: *sequence **dict
s.startswith( prefix[,start[,end]] ) s.endswith( suffix[,start[,end]] ) s.strip( [chars] ) s.count( sub[,start[,end]] ) s.partition( sep ) → (before,sep,after) s.index( sub[,start[,end]] ) s.find( sub[,start[,end]] ) s.is…() tests on chars categories (ex. s.isalpha() ) s.upper() s.lower() s.title() s.swapcase() s.casefold() s.capitalize() s.center( [width,fill] ) s.ljust( [width,fill] ) s.rjust( [width,fill] ) s.zfill( [width] ) s.encode( encoding ) s.split( [sep] ) s.join( seq )
?
yes no
next finish
…
Input
import copy copy.copy(c)→ shallow copy of container copy.deepcopy(c)→ deep copy of container
☝ this is the use of function name with parentheses which does the call
fct()
fct
fct
☝ text mode t by default (read/write str ), possible binary mode b (read/write bytes ). Convert from/to required type!
break immediate exit
continue next iteration
☝ else block for normal loop exit.
Iterative Loop Statement
Operations on Strings
Formatting
Generic Operations on Containers
by Dave Child (DaveChild) via cheatography.com/1/cs/19/
Python Time Methods Python Time Methods
replace() utcoffset()
isoformat() dst()
str() tzname()
strftime(format)
Python Date Formatting Python Date Formatting
%a Abbreviated weekday (Sun)
%A Weekday (Sunday)
%b Abbreviated month name (Jan)
%B Month name (January)
%c Date and time
%d Day (leading zeros) (01 to 31)
%H 24 hour (leading zeros) (00 to 23)
%I 12 hour (leading zeros) (01 to 12)
%j Day of year (001 to 366)
%m Month (01 to 12)
%M Minute (00 to 59)
%p AM or PM
%S Second (00 to 61⁴)
%U Week number¹ (00 to 53)
%w Weekday² (0 to 6)
%W Week number³ (00 to 53)
%x Date
%X Time
%y Year without century (00 to 99)
%Y Year (2008)
%Z Time zone (GMT)
%% A literal "%" character (%)
¹ Sunday as start of week. All days in a new year preceding the first Sunday are
considered to be in week 0. ² 0 is Sunday, 6 is Saturday.
³ Monday as start of week. All days in a new year preceding the first Monday are
considered to be in week 0. ⁴ This is not a mistake. Range takes
account of leap and double-leap seconds.
By Dave ChildDave Child (DaveChild) cheatography.com/davechild/
aloneonahill.com
Published 19th October, 2011. Last updated 3rd November, 2020.
Page 2 of 2.
Sponsored by ApolloPad.comApolloPad.com Everyone has a novel in them. Finish
Yours! https://apollopad.com
Selecting List Elements
Import libraries
>>> import numpy
>>> import numpy as np
Selective import
>>> from math import pi
>>> help(str)
Python For Data Science Cheat Sheet
Python Basics Learn More Python for Data Science Interactively at www.datacamp.com
Variable Assignment
Strings
>>> x=
>>> x
>>> x+ 2 Sum of two variables
7
>>> x- 2 Subtraction of two variables
3
>>> x* 2 Multiplication of two variables
10
>>> x** 2 Exponentiation of a variable
25
>>> x% 2 Remainder of a variable
1
>>> x/float(2) Division of a variable
Variables and Data Types
str() '5', '3.45', 'True'
int() 5, 3, 1
float() 5.0, 1.
bool() True, True, True
Variables to strings
Variables to integers
Variables to floats
Variables to booleans
Lists
>>> a = 'is'
>>> b = 'nice'
>>> my_list = ['my', 'list', a, b]
>>> my_list2 = [[4,5,6,7], [3,4,5,6]]
Subset
>>> my_list[1]
>>> my_list[-3]
Slice
>>> my_list[1:3]
>>> my_list[1:]
>>> my_list[:3]
>>> my_list[:]
Subset Lists of Lists
>>> my_list2[1][0]
>>> my_list2[1][:2]
Also see NumPy Arrays
>>> my_list.index(a)
>>> my_list.count(a)
>>> my_list.append('!')
>>> my_list.remove('!')
>>> del(my_list[0:1])
>>> my_list.reverse()
>>> my_list.extend('!')
>>> my_list.pop(-1)
>>> my_list.insert(0,'!')
>>> my_list.sort()
Get the index of an item
Count an item
Append an item at a time
Remove an item
Remove an item
Reverse the list
Append an item
Remove an item
Insert an item
Sort the list
Index starts at 0
Select item at index 1
Select 3rd last item
Select items at index 1 and 2
Select items after index 0
Select items before index 3
Copy my_list
my_list[list][itemOfList]
Libraries
my_string.upper() my_string.lower() my_string.count('w') my_string.replace('e', 'i') my_string.strip()
>>> my_string = 'thisStringIsAwesome'
>>> my_string
'thisStringIsAwesome'
Numpy Arrays
my_list = [1, 2, 3, 4] my_array = np.array(my_list) my_2darray = np.array([[1,2,3],[4,5,6]])
>>> my_array.shape
>>> np.append(other_array)
>>> np.insert(my_array, 1, 5)
>>> np.delete(my_array,[1])
>>> np.mean(my_array)
>>> np.median(my_array)
>>> my_array.corrcoef()
>>> np.std(my_array)
Asking For Help
>>> my_string[3]
>>> my_string[4:9]
Subset
>>> my_array[1]
2 Slice
>>> my_array[0:2]
array([1, 2]) Subset 2D Numpy arrays
>>> my_2darray[:,0]
array([1, 4])
>>> my_list + my_list
['my', 'list', 'is', 'nice', 'my', 'list', 'is', 'nice']
>>> my_list * 2
['my', 'list', 'is', 'nice', 'my', 'list', 'is', 'nice']
>>> my_list2 > 4
True
>>> my_array > 3
array([False, False, False, True], dtype=bool)
>>> my_array * 2
array([2, 4, 6, 8])
>>> my_array + np.array([5, 6, 7, 8])
array([6, 8, 10, 12])
>>> my_string * 2
'thisStringIsAwesomethisStringIsAwesome'
>>> my_string + 'Innit'
'thisStringIsAwesomeInnit'
>>> 'm' in my_string
True DataCamp Learn Python for Data Science Interactively
Scientific computing
Data analysis
2D plotting
Machine learning
Also see Lists
Get the dimensions of the array Append items to an array Insert items in an array Delete items in an array Mean of the array Median of the array Correlation coefficient Standard deviation
String to uppercase String to lowercase Count String elements Replace String elements Strip whitespaces
Select item at index 1
Select items at index 0 and 1
my_2darray[rows, columns]
Install Python
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Types and Type Conversion
String Operations
List Operations
List Methods
Index starts at 0
String Methods
String Operations
Selecting Numpy Array Elements Index starts at 0
Numpy Array Operations
Numpy Array Functions
Python Basics: Gettin Started
Main Python Data Types
How to Create a Strin in Python
Math Operators
How to Store Strins in Variables
Built-in Functions in Python
How to Define a Function
List
List Comprehensions
Tuples
Dictionaries
If Statements (Conditional Statements) in Python
Python Loops
Class
Dealin with Python Exceptions (Errors)
How to Troubleshoot the Errors
Conclusion
03
04
05
06
07
08
10
12
16
16
17
19
21
22
23
24
25
Table of Contents
Python Basics: Gettin Started
What is IDLE (Interated Development and Learnin)
Most Windows and Mac computers come with Python pre-installed. You can check
that via a Command Line search. The particular appeal of Python is that you can
write a proram in any text editor, save it in .py format and then run via a Command
Line. But as you learn to write more complex code or venture into data science, you
miht want to switch to an IDE or IDLE.
IDLE (Interated Development and Learnin Environment) comes with every
Python installation. Its advantae over other text editors is that it hihlihts
important keywords (e.. strin functions), makin it easier for you to interpret code.
Shell is the default mode of operation for Python IDLE. In essence, it’s a simple loop
that performs that followin four steps:
- Reads the Python statement
- Evaluates the results of it
- Prints the result on the screen
- And then loops back to read the next statement.
Python shell is a reat place to test various small code snippets.
WebsiteSetup.or - Python Cheat Sheet
How to Create a Strin in Python
Basic Python Strin
Strin Concatenation
You can create a strin in three ways usin sinle , double or triple quotes. Here’s an
example of every option:
IMP! Whichever option you choose, you should stick to it and use it consistently
within your proram.
As the next step, you can use the print() function to output your strin in the console
window. This lets you review your code and ensure that all functions well.
Here’s a snippet for that:
my_string = “Let’s Learn Python!”
another_string = ‘It may seem difficult first, but you
can do it!’
a_long_string = ‘’’Yes, you can even master multi-line
strings
that cover more than one line
with some practice’’’
The next thin you can master is concatenation — a way to add two strins
toether usin the “+” operator. Here’s how it’s done:
Note: You can’t apply + operator to two different data types e.. strin + inteer. If
you try to do that, you’ll et the followin Python error:
string_one = “I’m reading “
string_two = “a new great book!”
string_three = string_one + string_two
TypeError: Can’t convert ‘int’ object to str implicitly
print(“Let’s print out a string!”)
WebsiteSetup.or - Python Cheat Sheet
Strin Replication
Math Operators
As the name implies, this command lets you repeat the same strin several times.
This is done usin ***** operator. Mind that this operator acts as a replicator only with
strin data types. When applied to numbers, it acts as a multiplier.
Strin replication example:
For reference, here’s a list of other math operations you can apply towards numbers:
And with print ()
And your output will be Alice written five times in a row.
‘Alice’ * 5 ‘AliceAliceAliceAliceAlice’
print(“Alice” * 5 )
Operators Operation Example
**** Exponent 2 ** 3 = 8**
% Modulus/Remainder 22 % 8 = 6
// Integer division 22 // 8 = 2
/ Division 22 / 8 = 2.
*** Multiplication 3 * 3 = 9**
- (^) Subtraction 5 - 2 = 3
+ Addition 2 + 2 = 4
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Built-in Functions in Python
Input() Function
len() Function
You already know the most popular function in Python — print(). Now let’s take a
look at its equally popular cousins that are in-built in the platform.
When you run this short proram, the results will look like this:
Output:
input() function is a simple way to prompt the user for some input (e.. provide their
name). All user input is stored as a strin.
Here’s a quick snippet to illustrate this:
len() function helps you find the lenth of any strin, list, tuple, dictionary, or another
data type. It’s a handy command to determine excessive values and trim them to
optimize the performance of your proram.
Here’s an input function example for a strin:
Hi! What’s your name? “Jim”
Nice to meet you, Jim!
How old are you? 25
So, you are already 25 years old, Jim!
The lenth of the strin is: 35
name = input(“Hi! What’s your name? “)
print(“Nice to meet you “ + name + “!”)
age = input(“How old are you “)
print(“So, you are already “ + str(age) + “ years old, “
+ name + “!”)
# testing len()
str1 = “Hope you are enjoying our tutorial!”
print(“The length of the string is :”, len(str1))
WebsiteSetup.or - Python Cheat Sheet
filter()
Use the Filter() function to exclude items in an iterable object (lists, tuples,
dictionaries, etc)
(Optional: The PDF version of the checklist can also include a full table of all the in-built
functions).
ages = [ 5 , 12 , 17 , 18 , 24 , 32 ]
def myFunc(x):
if x < 18 :
return False
else:
return True
adults = filter(myFunc, ages)
for x in adults:
print(x)
WebsiteSetup.or - Python Cheat Sheet
How to Pass Keyword Aruments to a Function
In this case, you pass the number 1 in for the x parameter, 2 in for the y parameter,
and 3 in for the z parameter. The proram will that do the simple math of addin up
the numbers:
Output:
A function can also accept keyword aruments. In this case, you can use
parameters in random order as the Python interpreter will use the provided
keywords to match the values to the parameters.
Here’s a simple example of how you pass a keyword arument to a function.
Output:
# Define function with parameters
def product_info(product name, price):
print(“productname: “ + product name)
print(“Price “ + str(dollars))
# Call function with parameters assigned as above
product_info(“White T-shirt”, 15 dollars)
# Call function with keyword arguments
product_info(productname=”jeans”, price= 45 )
Productname: White T-shirt
Price: 15
Productname: Jeans
Price: 45
a = 1 + 2
b = 1 + 3
c = 2 + 3
WebsiteSetup.or - Python Cheat Sheet
3
Product Name: White T-Shirt
Price: 15
Product Name: Jeans
Price: 45
4
def product_info (product name, price):
print(”Product Name: “ + product_name)
print(”Price: “ + str(price))
5
# Define function with parameters
product_info(”White T-Shirt: “, 15 )
# Call function with parameters assigned as above
product_info(productname=”Jeans“, price= 45 )
# Call function with keyword arguments
Lists
Example lists
How to Add Items to a List
Lists are another cornerstone data type in Python used to specify an ordered
sequence of elements. In short, they help you keep related data toether and
perform the same operations on several values at once. Unlike strins, lists are
mutable (=chaneable).
Each value inside a list is called an item and these are placed between square
brackets.
Alternatively, you can use list() function to do the same:
You have two ways to add new items to existin lists.
The first one is usin append() function:
The second option is to insert() function to add an item at the specified index:
my_list = [ 1 , 2 , 3 ]
my_list2 = [“a”, “b”, “c”]
my_list3 = [“4”, d, “book”, 5 ]
beta_list = [“apple”, “banana”, “orange”]
beta_list.append(“grape”)
print(beta_list)
beta_list = [“apple”, “banana”, “orange”]
beta_list.insert(“2 grape”)
print(beta_list)
alpha_list = list((“1”, “2”, “3”))
print(alpha_list)
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2,“grape”
Sort a List
Slice a List
Chane Item Value on Your List
Loop Throuh the List
Use the sort() function to oranize all items in your list.
Now, if you want to call just a few elements from your list (e.. the first 4 items),
you need to specify a rane of index numbers separated by a colon [x:y]. Here’s an
example:
You can easily overwrite a value of one list items:
Usin for loop you can multiply the usae of certain items, similarly to what *
operator does. Here’s an example:
Output:
alpha_list = [ 34 , 23 , 67 , 100 , 88 , 2 ]
alpha_list.sort()
alpha_list
[ 2 , 23 , 34 , 67 , 88 , 100 ]
alpha_list[ 0 : 4 ]
[ 2 , 23 , 34 , 67 ]
beta_list = [“apple”, “banana”, “orange”]
beta_list[ 1 ] = “pear”
print(beta_list)
for x in range( 1 , 4 ):
beta_list += [‘fruit’]
print(beta_list)
[‘apple’, ‘pear’, ‘cherry’]
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Copy a List
Use the built-in copy() function to replicate your data:
Alternatively, you can copy a list with the list() method:
beta_list = [“apple”, “banana”, “orange”]
beta_list = beta_list.copy()
print(beta_list)
beta_list = [“apple”, “banana”, “orange”]
beta_list = list (beta_list)
print(beta_list)
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