names = [
    "Kevin",
    "Peter",
    "John"
]

names

['Kevin', 'Peter', 'John']

names.pop(0)

'Kevin'

names

['Peter', 'John']

entries = ['one', 2, 'three', False]

print(entries)

['one', 2, 'three', False]

print(entries[2:7])

['three', False]

entryTuple = (100, 200, 'three', 'four')
print(entryTuple)

(100, 200, 'three', 'four')

cities = ['Toronto', 'Monteal', 'Vancouver']
print(cities)

['Toronto', 'Monteal', 'Vancouver']

users = [
    ('Anders', 'A', 21),
    ('Balmer', 'B', 45),
    ('Stephe', 'S', 24)
]

print(users)

[('Anders …

import pandas as pd
from IPython.display import display

# Example list of tuples
data = [
    (1, 'Alice', 25),
    (2, 'Bob', 30),
    (3, 'Charlie', 35)
]

# Convert the list of tuples to a DataFrame
df = pd.DataFrame(data, columns=['ID', 'Name', 'Age'])

# Set display options
pd.set_option('display.max_rows', 100)
pd.set_option('display …

import pandas as pd
from IPython.display import display

# Example list of tuples
data = [
    (1, 'Alice', 25),
    (2, 'Bob', 30),
    (3, 'Charlie', 35)
]

# Convert the list of tuples to a DataFrame
df = pd.DataFrame(data, columns=['ID', 'Name', 'Age'])

# Set display options
pd.set_option('display.max_rows', 100)
pd.set_option('display …

one = "Toronto is nice"

one

'Toronto is nice'

one_array = one.split(" ")

two = "It is nice to be in Toronto"

two_array = two.split(" ")

two_array

['It', 'is', 'nice', 'to', 'be', 'in', 'Toronto']

all(x in two for x in one_array)

True

#Number Basics

import math

print(math.ceil(4.3))

5

print(math.floor(4.8))

4

print(math.floor(-4.2))

-5

print(math.fabs(-3.7))

3.7

print(math.fabs(3.7))

3.7

print(math.trunc(3.9)) 

3

print(math.trunc(-3.9))

-3

print(math …

import itertools as it
import more_itertools as mit

a = it.count(0, 2)
mit.take(10, a)

[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5, 6, 7]

y = [
    0,
    220,
    380,
    500,
    540,
    540,
    590,
]

y

[0, 220, 380, 500, 540, 540, 590]

plt.plot(x, y, 'ro')

# plt.axis([0, 10, 20, 100])

[<matplotlib.lines.Line2D at 0x211796c3830>]

def get_int(c):
    if(c == 'a'):
        return (200 + ord(c))

    if(c == 'e'):
        return (250 + ord(c))

    if(c == 'i'):
        return (300 + ord(c))

    if(c == 'o'):
        return (350 + ord(c))

    if(c == 'u'):
        return (400 + ord(c))

    return ord(c)

def get_name_meter(name,  cache={}):

    if name in cache: 
        return …

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: C:\\Users\\Afia Jahan\\anaconda3\\envs\\py312; pyv: 3.12.11 | packaged by Anaconda, Inc. | (main, Jun  5 2025, 12:58:53) [MSC v.1929 64 bit (AMD64)]'

print(pyu.ps2("pandas"))

Name: pandas
Version: 2.3.0
Summary: Powerful data structures …