# My Updated Home-Office Setup — If you do work from home sometimes, I do recommend getting some of these to brighten up your coding experience too! 1) A long long screen Mine is a 34-Inch monitor from Dell with a longer-than-normal screen aspect ratio. Longer screen == more screen real estate == happier coding 2) External screens I work from my laptop (16-Inch…

# Why ‘yield’ can make your Python code faster — And this problem gets worse the more data we deal with. What if there are 1000 people in the line? The ‘return’ keyword def add10(x): return x + 10 x = add10(4) # x = 14 def get_takoballs(orders): output = [] for order in orders: output.append(f'{order} …

# Stuff I wish I learnt earlier as a beginner — There are lots of concepts we need to grasp in Python. And everyone learns them differently, in different sequences. Here are some things I wish I learnt much earlier when I was still a Python beginner. 1) Tuple Unpacking + Tuple Unpacking With * person = ['bob', 30, 'male'] name, age, gender = person # name='bob, age=30, gender='male' …

# this list keeps getting longer — 1) We can set variables dynamically using globals() a = 4 b = 5 ^ this is the same as: globals()['a'] = 4 globals()['b'] = 5 globals() is a dictionary containing all global variables, and we can set variables by add key-value pairs into globals(). (don’t do this in production code tho) 2) re.sub can take in functions # replacing vowels with - import re x…

# Practice questions for absolute basics — Day 34 of experimenting with video content 1) Year of birth Write a Python script that prompts the user for his age, and prints the following output. enter your age: 30 your age is 30, and you were born in 1993 2) Average of 3 numbers Write a Python script that prompts the user for 3 numbers, and…

Day 33 of exprimenting with video content. 1) ~ can be used to invert stuff in Pandas import pandas as pd df = pd.DataFrame([ [1,2,3], [1,2,4], [None,2,4], [2,2,3], [None,2,4] ], columns=['a', 'b', 'c']) df1 = df[df['a'].isna()] print(df1) # a b c # 2 NaN 2 4 # 4 NaN 2 4 df2 = df[~df['a'].isna()] print(df2) #…

# and less painful when installing Python packages — Day 32 of experimenting with video content The 9 Commands pip install numpy # installs the external library numpy pip install numpy pandas colorama # installs numpy, pandas and colarama together pip install --upgrade numpy # upgrades numpy to latest version on repository pip install -r requirements.txt # installs everything inside requirements.txt

# Python From Zero To One — Part 7 — Day 31 of experimenting with video content input() in a nutshell name = input('what is your name? ') print(name) ^ the built-in input() function allows us to prompt the user to type in something eg. name, age etc. Whatever the user types will be stored as a string value in the name variable…

# eg. controlling object behaviour with ~ — Day 30 of experimenting with video content 1) reflected arithmetic operators class Dog: def __add__(self, x): return 'apple' def __radd__(self, x): return 'orange' dog = Dog() print(dog + 1) # apple print(1 + dog) # orange Reflected arithmetic magic methods are used when we use something + object rather than object + something. 2) __getattr__ vs __getattribute__