#python #coding #numpy # dtype = Keyword argument that tells NumPy what kind of values are stored in an array # Otherwise NumPy guesses the best data type based on your data # Manually setting dtype improves performance # & is more memory efficient (especially when working with large data sets) # integer (int8, int16, int32, int64) # float (float16, float32, float64) # boolean (bool_) # string (str_) # object (object_) # int8 = -128 to 127 # int16 = –32,768 to 32,767 # int32 = –2,147,483,648 to 2,147,483,647 # int64 = –9.22e18 to 9.22e18 # float16 = ~3-4 decimal digit precision # float32 = ~7-8 decimal digit precision # float64 = ~15-17 decimal digit precision

#python #coding #programming We're going to walkthrough how to create an mp3 music player using Python. This video is meant for beginner to intermediate Python programmers to serve as a practice project for the Python playlist.

#python #coding #numpy 00:00:00 save NumPy array 00:01:53 load NumPy array 00:02:30 save multiple arrays 00:04:29 savez_compressed() 00:05:01 load multiple arrays import numpy as np # -------------------------------------------- # Save a NumPy array # -------------------------------------------- array = np.array([[1, 2, 3], [4, 5, 6]]) np.save("data", array) print("File saved!") # -------------------------------------------- # Load a single NumPy array # -------------------------------------------- array = np.load("data.npy") print(array) # -------------------------------------------- # Save multiple NumPy arrays # -------------------------------------------- array1 = np.array([[1, 2, 3], [4, 5, 6]]) array2 = np.array([2022, 2023, 2024, 2025]) array3 = np.array([1.1, 2.2, 3.3, 4.4, 5.5]) np.savez("data", array1, array2, array3) print("NumPy data was saved!") # -------------------------------------------- # Load multiple NumPy arrays # -------------------------------------------- arrays = np.load("data.npz") print(arrays["arr_0"]) print(arrays["arr_1"]) print(arrays["arr_2"])

#python #coding #programming # Data Class = A special kind of class that's designed mostly for holding data # without writing a lot of the boilerplate code for regular classes. # They automatically generate: __init__, __repr__, __eq__ # (Python 3.7+)

#python #coding #programming 00:00:00 zeros() 00:01:29 ones() 00:01:52 full() 00:02:16 eye() 00:03:09 empty() 00:03:59 arange() 00:05:16 linspace() import numpy as np # Creates an array with zeros array = np.zeros((2, 3, 10)) print(array) # Creates an array with ones array = np.ones((2, 3, 10)) print(array) # Creates an array with a given value array = np.full((2, 3), 9) print(array) # Creates an array w/o initializing entries array = np.empty((2, 3)) print(array) # Creates an identity matrix with 0s and 1s array = np.eye(5) print(array) # Creates an array with evenly spaced values up to a given range array = np.arange(0, 100, 0.1) # (start, stop, step) print(array) # Creates an array with a set number of values that are evenly spaced array = np.linspace(0, 10, 5) # (start, stop, num) print(array)

#python #coding #programming # In a terminal: pip install qrcode[pil] import qrcode url = input("Enter the URL: ").strip() file_path = "qrcode.png" qr = qrcode.QRCode() qr.add_data(url) img = qr.make_image() img.save(file_path) print("QR Code was generated!")

#python #coding #programming # Iterator = An object that returns elements one at a time # from a sequence (or data stream) # and remembers its position between calls. # A Python object is an iterator if it has: # __iter__() → Returns the iterator object itself # __next__() → Returns the next item in the sequence # (raises StopIteration when there's no more items)

#python #coding #numpy # reshape() = Changes the shape of an array # w/o altering its underlying data # array.reshape(rows, columns) import numpy as np array = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]) array = array.reshape(2, 6) array = array.reshape(3, 4) # array = array.reshape(4, 4) # Too many elements # array = array.reshape(2, 4) # Too few elements array = array.reshape(4, 3) array = array.reshape(2, 2, 3) # 3D array = array.reshape(3, 2, 2) # 3D # -1 NumPy will automatically infer the correct size for that dimension array = array.reshape(1, -1) array = array.reshape(-1, 1) print(array)

#python #coding #programming # Generator Expression = Similar to a list comprehension but uses () instead of [] # Creates a generator (iterator) that yields values one at a time # No need to define a function or use yield # Less flexible than a gen func and not reusable # gen object = (expression for value in iterable if condition)

#python #coding #programming # Generator = Function that behaves like an iterator (it can be used in a for loop) # Pauses a function, returns a value, then resumes # Uses 'yield' instead or 'return' # Iterate without loading everything into memory (ex. reading large files) # return = Pouring bucket # yield = Drip faucet

#python #coding #programming # zip() = Combines multiple iterables (lists, tuples, sets, dict) # into a single iterator of tuples. # Makes managing multiple indices easier. names = ["Spongebob", "Patrick", "Squidward"] ages = [30, 35, 50] jobs = ["Cook", "Unemployed", "Cashier"] data = zip(names, ages, jobs) for name, age, job in data: print(f"{name} is a {age} year old {job}")

#python #coding #matplotlib This video serves as an introduction to the Matplotlib Python library. We’ll cover the basics of Matplotlib so you can start working with it on your own. After finishing this video, I recommend learning either linear algebra, Scikit-learn, or more advanced Matplotlib topics. 00:00:00 Matplotlib intro 📊 00:07:01 plot customization 00:16:18 labels 00:21:07 grid lines 00:23:54 bar charts 00:28:03 pie charts 00:34:09 scatter plots 00:40:56 histograms 00:47:11 subplots 00:54:07 Pandas + Matplotlib

#python #coding #matplotlib This video serves as a project where we will create a bar chart based on the primary Type of the original 150 Pokémon. Here is a list you can copy to a CSV file: No,Name,Type1,Type2,Height,Weight,Legendary 1,Bulbasaur,Grass,Poison,0.7,6.9,0 2,Ivysaur,Grass,Poison,1,13,0 3,Venusaur,Grass,Poison,2,100,0 4,Charmander,Fire,,0.6,8.5,0 5,Charmeleon,Fire,,1.1,19,0 6,Charizard,Fire,Flying,1.7,90.5,0 7,Squirtle,Water,,0.5,9,0 8,Wartortle,Water,,1,22.5,0 9,Blastoise,Water,,1.6,85.5,0 10,Caterpie,Bug,,0.3,2.9,0 11,Metapod,Bug,,0.7,9.9,0 12,Butterfree,Bug,Flying,1.1,32,0 13,Weedle,Bug,Poison,0.3,3.2,0 14,Kakuna,Bug,Poison,0.6,10,0 15,Beedrill,Bug,Poison,1,29.5,0 16,Pidgey,Normal,Flying,0.3,1.8,0 17,Pidgeotto,Normal,Flying,1.1,30,0 18,Pidgeot,Normal,Flying,1.5,39.5,0 19,Rattata,Normal,,0.3,3.5,0 20,Raticate,Normal,,0.7,18.5,0 21,Spearow,Normal,Flying,0.3,2,0 22,Fearow,Normal,Flying,1.2,38,0 23,Ekans,Poison,,2,6.9,0 24,Arbok,Poison,,3.5,65,0 25,Pikachu,Electric,,0.4,6,0 26,Raichu,Electric,,0.8,30,0 27,Sandshrew,Ground,,0.6,12,0 28,Sandslash,Ground,,1,29.5,0 29,Nidoran♀,Poison,,0.4,7,0 30,Nidorina,Poison,,0.8,20,0 31,Nidoqueen,Poison,Ground,1.3,60,0 32,Nidoran♂,Poison,,0.5,9,0 33,Nidorino,Poison,,0.9,19.5,0 34,Nidoking,Poison,Ground,1.4,62,0 35,Clefairy,Fairy,,0.6,7.5,0 36,Clefable,Fairy,,1.3,40,0 37,Vulpix,Fire,,0.6,9.9,0 38,Ninetales,Fire,,1.1,19.9,0 39,Jigglypuff,Normal,Fairy,0.5,5.5,0 40,Wigglytuff,Normal,Fairy,1,12,0 41,Zubat,Poison,Flying,0.8,7.5,0 42,Golbat,Poison,Flying,1.6,55,0 43,Oddish,Grass,Poison,0.5,5.4,0 44,Gloom,Grass,Poison,0.8,8.6,0 45,Vileplume,Grass,Poison,1.2,18.6,0 46,Paras,Bug,Grass,0.3,5.4,0 47,Parasect,Bug,Grass,1,29.5,0 48,Venonat,Bug,Poison,1,30,0 49,Venomoth,Bug,Poison,1.5,12.5,0 50,Diglett,Ground,,0.2,0.8,0 51,Dugtrio,Ground,,0.7,33.3,0 52,Meowth,Normal,,0.4,4.2,0 53,Persian,Normal,,1,32,0 54,Psyduck,Water,,0.8,19.6,0 55,Golduck,Water,,1.7,76.6,0 56,Mankey,Fighting,,0.5,28,0 57,Primeape,Fighting,,1,32,0 58,Growlithe,Fire,,0.7,19,0 59,Arcanine,Fire,,1.9,155,0 60,Poliwag,Water,,0.6,12.4,0 61,Poliwhirl,Water,,1,20,0 62,Poliwrath,Water,Fighting,1.3,54,0 63,Abra,Psychic,,0.9,19.5,0 64,Kadabra,Psychic,,1.3,56.5,0 65,Alakazam,Psychic,,1.5,48,0 66,Machop,Fighting,,0.8,19.5,0 67,Machoke,Fighting,,1.5,70.5,0 68,Machamp,Fighting,,1.6,130,0 69,Bellsprout,Grass,Poison,0.7,4,0 70,Weepinbell,Grass,Poison,1,6.4,0 71,Victreebel,Grass,Poison,1.7,15.5,0 72,Tentacool,Water,Poison,0.9,45.5,0 73,Tentacruel,Water,Poison,1.6,55,0 74,Geodude,Rock,Ground,0.4,20,0 75,Graveler,Rock,Ground,1,105,0 76,Golem,Rock,Ground,1.4,300,0 77,Ponyta,Fire,,1,30,0 78,Rapidash,Fire,,1.7,95,0 79,Slowpoke,Water,Psychic,1.2,36,0 80,Slowbro,Water,Psychic,1.6,78.5,0 81,Magnemite,Electric,Steel,0.3,6,0 82,Magneton,Electric,Steel,1,60,0 83,Farfetch'd,Normal,Flying,0.8,15,0 84,Doduo,Normal,Flying,1.4,39.2,0 85,Dodrio,Normal,Flying,1.8,85.2,0 86,Seel,Water,,1.1,90,0 87,Dewgong,Water,Ice,1.7,120,0 88,Grimer,Poison,,0.9,30,0 89,Muk,Poison,,1.2,30,0 90,Shellder,Water,,0.3,4,0 91,Cloyster,Water,Ice,1.5,132.5,0 92,Gastly,Ghost,Poison,1.3,0.1,0 93,Haunter,Ghost,Poison,1.6,0.1,0 94,Gengar,Ghost,Poison,1.5,40.5,0 95,Onix,Rock,Ground,8.8,210,0 96,Drowzee,Psychic,,1,32.4,0 97,Hypno,Psychic,,1.6,75.6,0 98,Krabby,Water,,0.4,6.5,0 99,Kingler,Water,,1.3,60,0 100,Voltorb,Electric,,0.5,10.4,0 101,Electrode,Electric,,1.2,66.6,0 102,Exeggcute,Grass,Psychic,0.4,2.5,0 103,Exeggutor,Grass,Psychic,2,120,0 104,Cubone,Ground,,0.4,6.5,0 105,Marowak,Ground,,1,45,0 106,Hitmonlee,Fighting,,1.5,49.8,0 107,Hitmonchan,Fighting,,1.4,50.2,0 108,Lickitung,Normal,,1.2,65.5,0 109,Koffing,Poison,,0.6,1,0 110,Weezing,Poison,,1.2,9.5,0 111,Rhyhorn,Ground,Rock,1,115,0 112,Rhydon,Ground,Rock,1.9,120,0 113,Chansey,Normal,,1.1,34.6,0 114,Tangela,Grass,,1,35,0 115,Kangaskhan,Normal,,2.2,80,0 116,Horsea,Water,,0.4,8,0 117,Seadra,Water,,1.2,25,0 118,Goldeen,Water,,0.6,15,0 119,Seaking,Water,,1.3,39,0 120,Staryu,Water,,0.8,34.5,0 121,Starmie,Water,Psychic,1.1,80,0 122,Mr. Mime,Psychic,Fairy,1.3,54.5,0 123,Scyther,Bug,Flying,1.5,56,0 124,Jynx,Ice,Psychic,1.4,40.6,0 125,Electabuzz,Electric,,1.1,30,0 126,Magmar,Fire,,1.3,44.5,0 127,Pinsir,Bug,,1.5,55,0 128,Tauros,Normal,,1.4,88.4,0 129,Magikarp,Water,,0.9,10,0 130,Gyarados,Water,Flying,6.5,235,0 131,Lapras,Water,Ice,2.5,220,0 132,Ditto,Normal,,0.3,4,0 133,Eevee,Normal,,0.3,6.5,0 134,Vaporeon,Water,,1,29,0 135,Jolteon,Electric,,0.8,24.5,0 136,Flareon,Fire,,0.9,25,0 137,Porygon,Normal,,0.8,36.5,0 138,Omanyte,Rock,Water,0.4,7.5,0 139,Omastar,Rock,Water,1,35,0 140,Kabuto,Rock,Water,0.5,11.5,0 141,Kabutops,Rock,Water,1.3,40.5,0 142,Aerodactyl,Rock,Flying,1.8,59,0 143,Snorlax,Normal,,2.1,460,0 144,Articuno,Ice,Flying,1.7,55.4,1 145,Zapdos,Electric,Flying,1.6,52.6,1 146,Moltres,Fire,Flying,2,60,1 147,Dratini,Dragon,,1.8,3.3,0 148,Dragonair,Dragon,,4,16.5,0 149,Dragonite,Dragon,Flying,2.2,210,0 150,Mewtwo,Psychic,,2,122,1

#python #coding #matplotlib In this video I will show you how to create subplots using Matplotlib.

#python #coding #matplotlib In this video we will create a basic histogram using Matplotlib.