๐Ÿ“’ Today I Learn/๐Ÿ Python

๋ถˆ๋ฆฌ์–ธ ์ธ๋ฑ์‹ฑ๐Ÿ’ก ๋ถˆ๋ฆฌ์–ธ((Boolean) ์ž๋ฃŒํ˜• : ์ฃผ์–ด์ง„ ์กฐ๊ฑด์ด ์ฐธ(True) ๋˜๋Š” ๊ฑฐ์ง“(False)์„ ๋‚˜ํƒ€๋‚ด๋Š” ๋ฐ ์‚ฌ์šฉ1. ๋ถˆ๋ฆฌ์–ธ ๋ฐฐ์—ด์„ ํ™œ์šฉํ•œ ์ธ๋ฑ์‹ฑarr = np.array([1, 2, 3, 4, 5])condition = np.array([True, False, True, False, True])# ๋ถˆ๋ฆฌ์–ธ ์ธ๋ฑ์‹ฑ์„ ์‚ฌ์šฉํ•˜์—ฌ ์กฐ๊ฑด์— ๋งž๋Š” ์š”์†Œ ์„ ํƒresult = arr[condition]print("Result using boolean indexing:", result) ## ์ถœ๋ ฅ: [1 3 5]๋ฐฐ์—ด arr๊ณผ ์กฐ๊ฑด์„ ๋‹ด์€ ๋ถˆ๋ฆฌ์–ธ ๋ฐฐ์—ด condition์„ ์ƒ์„ฑ๋ถˆ๋ฆฌ์–ธ ์ธ๋ฑ์‹ฑ : arr[๋ถˆ๋ฆฌ์–ธ ๋ฐฐ์—ด]2. ๋ถˆ๋ฆฌ์–ธ ์ธ๋ฑ์‹ฑevens = arr[arr % 2 == 0]print("Even numbers u..
glob๐ŸŒŽ glob : ํ˜„์žฌ/ ์›ํ•˜๋Š” ๋””๋ ‰ํ† ๋ฆฌ์— ์žˆ๋Š” ํŒŒ์ผ ์ •๋ณด ์ฐพ๊ธฐimport globโ€‹ํ˜„์žฌ ๊ฒฝ๋กœ์˜ ๋ชจ๋“  ํŒŒ์ผ ์ฐพ๊ธฐfile_list1 = glob.glob('*')→ ํŠน์ • ๋””๋ ‰ํ† ๋ฆฌ ์•ˆ์˜ ํŒŒ์ผ์„ ์ฐพ๊ณ  ์‹ถ๋‹ค๋ฉด `glob.glob('sample_data/*')`์™€ ๊ฐ™์ด 'ํŒŒ์ผ ๊ฒฝ๋กœ/ *'์˜ ํ˜•ํƒœ๋กœ ์ž‘์„ฑํ•˜๋ฉด๋œ๋‹ค. ๐Ÿ—‚๏ธ ํŒŒ์ผ ๊ฒฝ๋กœ ์ฐพ๊ธฐ์— ์œ ์šฉํ•œ ์™€์ผ๋“œ ์นด๋“œ ๋ฌธ์ž๋”๋ณด๊ธฐํŒŒ์ผ ๊ฒฝ๋กœ ์ฐพ๊ธฐ์— ์œ ์šฉํ•œ ์™€์ผ๋“œ ์นด๋“œ ๋ฌธ์ž* : ๋ชจ๋“  ํŒŒ์ผ ๋ถˆ๋Ÿฌ์˜ค๊ธฐ→ * .txt : ํ•ด๋‹น ๋””๋ ‰ํ† ๋ฆฌ์—์„œ ๋ชจ๋“  ํ…์ŠคํŠธ ํŒŒ์ผ ์ฐพ๊ธฐ[] : ๊ด„ํ˜ธ ์•ˆ์— ํฌํ•จ๋œ ๋ฌธ์ž ์ค‘ ํ•˜๋‚˜์™€ ์ผ์น˜ํ•˜๋Š” ํŒŒ์ผ ์ฐพ๊ธฐ{} : ๊ด„ํ˜ธ ์•ˆ์— ํฌํ•จ๋œ ๋ฌธ์ž์—ด ์ค‘ ํ•˜๋‚˜์™€ ์ผ์น˜ํ•˜๋Š” ํŒŒ์ผ ์ฐพ๊ธฐํŠน์ • ํ™•์žฅ์ž๋ฅผ ๊ฐ€์ง„ ํŒŒ์ผ๋งŒ ์ฐพ๊ธฐfile_list4 = glob.glob('*.csv')→ ํ˜„์žฌ ๋””๋ ‰..
๋ฆฌ์ŠคํŠธ ์ปดํ”„๋ฆฌํ—จ์…˜๐Ÿ’ก ๋ฆฌ์ŠคํŠธ ์ปดํ”„๋ฆฌํ—จ์…˜ :  ํŒŒ์ด์ฌ์—์„œ ๋ฆฌ์ŠคํŠธ๋ฅผ ๊ฐ„๊ฒฐํ•˜๊ฒŒ ์ƒ์„ฑํ•˜๋Š” ๋ฐฉ๋ฒ• # ๊ธฐ๋ณธ์ ์ธ ๊ตฌ์กฐ[ํ‘œํ˜„์‹ for ํ•ญ๋ชฉ in iterable if ์กฐ๊ฑด๋ฌธ]ํ‘œํ˜„์‹ :  ๊ฐ ํ•ญ๋ชฉ์— ๋Œ€ํ•œ ๊ณ„์‚ฐ์ด๋‚˜ ๋ณ€ํ™˜ํ•ญ๋ชฉ :  ๋ฐ˜๋ณต๋˜๋Š” ๊ฐ’iterable : ๋ฐ˜๋ณต ๊ฐ€๋Šฅํ•œ ๊ฐ์ฒด์˜ˆ์‹œ 1) 1๋ถ€ํ„ฐ 10๊นŒ์ง€์˜ ์ˆซ์ž๋ฅผ ์ œ๊ณฑํ•œ ๋ฆฌ์ŠคํŠธ ์ƒ์„ฑsquares = [x**2 for x in range(1, 11)]print(squares) ## ์ถœ๋ ฅ: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]`range(1,11)`: 1๋ถ€ํ„ฐ 10๊นŒ์ง€ ์ž์—ฐ์ˆ˜๋ฅผ`for x `: x ๋กœ ๋ฐ›์•„์„œ`x**2`: ์ œ๊ณฑ์˜ˆ์‹œ 2) ๋ฆฌ์ŠคํŠธ ์ปดํ”„๋ฆฌํ—จ์…˜์„ ์ค‘์ฒฉํ•˜์—ฌ 2์ฐจ์› ๋ฆฌ์ŠคํŠธ ์ƒ์„ฑmatrix = [[i for i in range(1, 4)] for..
ํŒŒ์ผ ๋ถˆ๋Ÿฌ์˜ค๊ธฐ ๋ฐ ์ €์žฅํ•˜๊ธฐํ™•์žฅ์ž์— ๋”ฐ๋ฅธ ํŒŒ์ผ ๋ถˆ๋Ÿฌ์˜ค๊ธฐcsv ํŒŒ์ผimport pandas as pddf = pd.read_csv('file.csv')excel ํŒŒ์ผpythonimport pandas as pddf = pd.read_excel('file.xlsx')txt ํŒŒ์ผimport pandas as pddf = pd.read_csv('file.txt', delimiter='\t')→ ๋งŒ์•ฝ ํƒญ์œผ๋กœ ๊ตฌ๋ถ„๋˜์–ด ์žˆ๋‹ค๋ฉด `delimiter='\t'`๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค.ํŒŒ์ผ ์ €์žฅํ•˜๊ธฐcsv ํŒŒ์ผ ์ €์žฅํ•˜๊ธฐimport pandas as pddf = pd.DataFrame(data)df.to_csv(ํŒŒ์ผ ๊ฒฝ๋กœ, index = False)txt ํŒŒ์ผ ์ €์žฅํ•˜๊ธฐwith open(ํ…์ŠคํŠธํŒŒ์ผ ์ €์žฅํ•  ๊ฒฝ๋กœ, 'w') as ํŒŒ์ผ๋ช…: ..
๋ฒ ์ด์ง ๋ฌธํ•ญ1. ๋ฐ์ดํ„ฐ ๋ถˆ๋Ÿฌ์˜ค๊ธฐํƒ€์ดํƒ€๋‹‰ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถˆ๋Ÿฌ์˜จ ๋‹ค์Œ df๋ผ๋Š” ๋ณ€์ˆ˜์— ๋‹ด๊ณ  ๋ฐ์ดํ„ฐ์˜ ๋‚ด์šฉ์„ ํ™•์ธํ•˜์„ธ์š”.import pandas as pddf = pd.read_csv('train.csv')print(df)ํ™•์žฅ์ž์— ๋”ฐ๋ฅธ ํŒŒ์ผ ๋ฐ์ดํ„ฐ ํ”„๋ ˆ์ž„์œผ๋กœ ๋ถˆ๋Ÿฌ์˜ค๊ธฐ → Pandas library ํ™œ์šฉํ•˜๊ธฐread_csv : csv ํŒŒ์ผ ๋ถˆ๋Ÿฌ์˜ค๊ธฐread_excel : excel ํŒŒ์ผ ๋ถˆ๋Ÿฌ์˜ค๊ธฐ2. ์ƒ์กด์ž ์ˆ˜ ๊ณ„์‚ฐํƒ€์ดํƒ€๋‹‰ ์ „์ฒด ์ƒ์กด์ž ์ˆ˜์™€ ์‚ฌ๋ง์ž ์ˆ˜๋ฅผ ๊ณ„์‚ฐํ•˜๊ณ  ์ถœ๋ ฅํ•˜์„ธ์š”.survival = df['Survived']dead =0survived =0for i in survival: if i ==0: dead+=1 else: survived +=1print(f"์‚ฌ๋ง์ž๋Š” {dead}๋ช…, ์ƒ..
240501 Today I Learn๋งค๊ฐœ๋ณ€์ˆ˜ vs. ์ธ์ˆ˜๐Ÿ’ก ๋งค๊ฐœ๋ณ€์ˆ˜ vs. ์ธ์ˆ˜* ๋งค๊ฐœ๋ณ€์ˆ˜ : ํ•จ์ˆ˜๋ฅผ ์ •์˜ํ•  ๋•Œ ํ•จ์ˆ˜๊ฐ€ ๋ฐ›์•„๋“ค์ด๋Š” ๊ฐ’* ์ธ์ˆ˜ : ํ•จ์ˆ˜ ํ˜ธ์ถœ ์‹œ ํ•จ์ˆ˜์— ์ „๋‹ฌ๋˜๋Š” ๊ฐ’ โ–ถ๏ธŽ ์˜ˆ์‹œ 1#1def greet(name): print("Hello, " + name + "!")#2greet("Alice")#1์˜ name์€ ํ•จ์ˆ˜๋ฅผ ์ •์˜ํ•  ๋•Œ ์‚ฌ์šฉ๋˜๋Š” ๊ฐ’์œผ๋กœ ๋งค๊ฐœ๋ณ€์ˆ˜์ด๋‹ค.#2์—์„œ "hello ์ด๋ฆ„ !"์„ ๋ฐ˜ํ™˜ํ•˜๋Š” greetํ•จ์ˆ˜ ์•ˆ์— ์žˆ๋Š” Alice๋Š” ํ•จ์ˆ˜์— ์ „๋‹ฌ๋˜๋Š” ๊ฐ’์œผ๋กœ ์ธ์ˆ˜์ด๋‹ค.โ–ถ๏ธŽ ์˜ˆ์‹œ 2) ๊ฐ€์กฑ์„ ๊ฐ€์ง„ ์Šน๊ฐ๋“ค ์ค‘์—์„œ ๊ฐ€์žฅ ๋งŽ์€ ๊ฐ€์กฑ์„ ๊ฐ€์ง„ ์Šน๊ฐ์„ ์ฐพ๋Š” ํ•จ์ˆ˜๋ฅผ ๋งŒ๋“ค์–ด๋ผ.def largest_family(df): family = df['SibSp']+df['Parch'] answer..
ny:D
'๐Ÿ“’ Today I Learn/๐Ÿ Python' ์นดํ…Œ๊ณ ๋ฆฌ์˜ ๊ธ€ ๋ชฉ๋ก (7 Page)