๐Ÿ“’ Today I Learn

240513 Today I LearnBasic data structures in pandasํŒ๋‹ค์Šค์—์„œ ์ œ๊ณตํ•˜๋Š” ๋‘๊ฐ€์ง€ ๋ฐ์ดํ„ฐ ํƒ€์ž…Series : 1์ฐจ์› ํ˜•ํƒœ์˜ ๋ฐ์ดํ„ฐ (ํŒŒ์ด์ฌ์˜ ๋Œ€๋ถ€๋ถ„์˜ ํƒ€์ž…๋“ค์ด ๋“ค์–ด๊ฐˆ ์ˆ˜ ์žˆ์Œ)DataFrame : 2์ฐจ์› ํ˜•ํƒœ์˜ ํ‘œ๋กœ ์ด๋ฃจ์–ด์ง„ ๋ฐ์ดํ„ฐ (ํ–‰,์—ด์˜ ๊ฐœ๋…์ด ์กด์žฌํ•จ)๐Ÿ’ก ๋ฐ์ดํ„ฐ์—์„œ ์ด์•ผ๊ธฐํ•˜๋Š” ์ฐจ์›์ด๋ž€?๋ฐ์ดํ„ฐ์˜ ์†์„ฑ(Attribute) ๊ฐœ์ˆ˜์— ๋”ฐ๋ผ ์ฐจ์›์„ ๊ตฌ๋ถ„ํ•œ๋‹ค.0์ฐจ์› : schalar(์Šค์นผ๋ผ) → ๊ฐ’1์ฐจ์› : vector(๋ฒกํ„ฐ)  → ๋ฆฌ์ŠคํŠธ2์ฐจ์› : matrix(ํ–‰๋ ฌ)  → 2์ค‘ ์ค‘์ฒฉ ๋ฆฌ์ŠคํŠธ3์ฐจ์›์ด์ƒ : tensor(ํ…์„œ) → 3์ค‘ ์ด์ƒ ์ค‘์ฒฉ ๋ฆฌ์ŠคํŠธObject Creation1. Series ๋งŒ๋“ค๊ธฐ : ๋ฆฌ์ŠคํŠธ์— ๊ฐ’์„ ๋„ฃ์–ด์„œ ๋งŒ๋“ค๊ธฐs = pd.Series([1,3,5,np.na..
240513 Today I Learn๋ฌธ์ œ์ƒํ™ฉ  ํ”„๋กœ๊ทธ๋ž˜๋จธ์Šค์ฝ”๋“œ ์ค‘์‹ฌ์˜ ๊ฐœ๋ฐœ์ž ์ฑ„์šฉ. ์Šคํƒ ๊ธฐ๋ฐ˜์˜ ํฌ์ง€์…˜ ๋งค์นญ. ํ”„๋กœ๊ทธ๋ž˜๋จธ์Šค์˜ ๊ฐœ๋ฐœ์ž ๋งž์ถคํ˜• ํ”„๋กœํ•„์„ ๋“ฑ๋กํ•˜๊ณ , ๋‚˜์™€ ๊ธฐ์ˆ  ๊ถํ•ฉ์ด ์ž˜ ๋งž๋Š” ๊ธฐ์—…๋“ค์„ ๋งค์นญ ๋ฐ›์œผ์„ธ์š”.programmers.co.krdef solution(nums): answer = [] for i in range(0, len(nums)): for j in range(i+1, len(nums)): for k in range(j+1, len(nums)): answer.append(nums[i]+nums[j]+nums[k]) for n in answer: cnt = [] ..
240513 Today I Learn๋ฐ์ดํ„ฐ ์ „์ฒ˜๋ฆฌํ•˜๊ธฐiris ๋ฐ์ดํ„ฐ์…‹์„ ํ™œ์šฉํ•ด์„œ ๋ฐ์ดํ„ฐ ์ „์ฒ˜๋ฆฌiris_data = sns.load_dataset('iris')iris_data.head()Q1. 'species' ์—ด ๊ฐ’์ด 'setosa'์ธ ๋ฐ์ดํ„ฐ ์„ ํƒํ•˜๊ธฐiris_data[iris_data['species']=='setosa']→ ์กฐ๊ฑด ์ธ๋ฑ์‹ฑํ•˜๊ธฐ dataframe[์กฐ๊ฑด]→ .loc๋ฅผ ํ™œ์šฉํ•  ์ˆ˜๋„ ์žˆ์Œ. `iris_data.loc[iris_data['species'] == 'setosa']`Q2. 10๋ถ€ํ„ฐ 20๊นŒ์ง€์˜ ํ–‰๊ณผ 1๋ถ€ํ„ฐ 3๊นŒ์ง€์˜ ์—ด ์„ ํƒํ•˜๊ธฐiris_data.iloc[10:21,1:4] ๐Ÿ‘‡ .iloc : ์ธ๋ฑ์Šค๋ฅผ ์ด์šฉํ•ด์„œ ๋ฐ์ดํ„ฐ ํ”„๋ ˆ์ž„ ์Šฌ๋ผ์ด์‹ฑํ•˜๊ธฐ  [Pandas] ๋ฐ์ดํ„ฐ ์ „์ฒ˜๋ฆฌ (2) ๊ฒฐ์ธก์น˜ ํ™•์ธํ•˜..
๐Ÿ‘Œ FACTS[5/7 - 5/10 ์ง„๋„ ์ •๋ฆฌ]๋ฐ์ดํ„ฐ ๋ถ„์„ ํŒŒ์ด์ฌ ์ข…ํ•ฉ๋ฐ˜ ๋ณต์Šต๋ฐ์ดํ„ฐ ์ „์ฒ˜๋ฆฌ ๋ฐ ์‹œ๊ฐํ™” ๊ฐ•์˜ ์™„๊ฐ•python ์ฝ”๋“œํƒ€์นด๐Ÿ’“ FEELINGSํŒŒ์ด์ฌ์„ ์–ด๋–ป๊ฒŒ ํ•ด์•ผํ• ์ง€ ๋ง‰๋ง‰ํ•˜๋‹ค๊ณ  ๋Š๊ผˆ๋˜๊ฒŒ ์–ด์ œ๊ฐ™์€๋ฐ, ์ด์ œ๋Š” ์ œ๋ฒ• ํŒŒ์ด์ฌ์„ ๋ณด๋Š” ๋ˆˆ์ด ์ƒ๊ธด ๊ฒƒ ๊ฐ™๋‹ค. ์˜ต์…˜์ด ๋„ˆ๋ฌด ๋งŽ์•„์„œ ๋ชจ๋“ ๊ฒƒ์„ ์™ธ์›Œ๋‚˜๊ฐ€๋Š”๋ฐ๋Š” ์—ฐ์Šต์ด ๋งŽ์ด ํ•„์š”ํ• ๊ฒƒ ๊ฐ™์ง€๋งŒ, ์ ์  ์ƒ๊ฐํ•˜๋Š” ํž˜์ด ๊ธธ๋Ÿฌ์ง€๋Š” ๊ฒƒ ๊ฐ™์•„์„œ ๋ฟŒ๋“ฏํ•˜๋‹ค. ์ด๋ฒˆ์ฃผ๋„ ์ˆ˜๊ณ ํ–ˆ๋‹ค.๐Ÿ’ก FINDINGSpandas, seaborn, matplotlib ํŒจํ‚ค์ง€๋ฅผ ์‚ฌ์šฉํ•˜๋ฉด์„œ ๋‹ค์–‘ํ•œ ํŒจํ‚ค์ง€๋ฅผ ํ™œ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ๋ฐฐ์› ๋‹ค. ๋ฐ์ดํ„ฐ ์‹œ๋ฆฌ์ฆˆ์™€ ๋ฐ์ดํ„ฐ ํ”„๋ ˆ์ž„์˜ ์ฐจ์ด์— ๋Œ€ํ•ด ๋ฐฐ์› ๋‹ค.๐Ÿ”ฎ FUTURE์•„์ง์€ ๋ถ€์กฑํ•จ์ด ๋งŽ์ง€๋งŒ, ์ด๋ฒˆ ์ฃผ ๋ฐฐ์šด ํŒ๋‹ค์Šค ๊ธฐ์ดˆ์™€ ํŒŒ์ด์ฌ ์ „์ฒ˜๋ฆฌ ๋ฐ ์‹œ๊ฐํ™”๋ฅผ ์•ž์œผ๋กœ์˜ ๋ถ„์„์— ๋ฌด๊ถ๋ฌด์ง„ํ•˜๊ฒŒ ํ™œ์šฉํ•  ..
240510 Today I Learn๐Ÿ’ก matplotlib์‹œ๊ฐํ™”๋ฅผ ์œ„ํ•œ ํŒŒ์ด์ฌ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ ์ค‘ ํ•˜๋‚˜๋กœ, ๋‹ค์–‘ํ•œ ์ข…๋ฅ˜์˜ ๊ทธ๋ž˜ํ”„๋ฅผ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ๋„๊ตฌ๋ฅผ ์ œ๊ณต2D ๊ทธ๋ž˜ํ”ฝ์„ ์ƒ์„ฑํ•˜๋Š” ๋ฐ ์ฃผ๋กœ ์‚ฌ์šฉ์„  ๊ทธ๋ž˜ํ”„, ๋ง‰๋Œ€ ๊ทธ๋ž˜ํ”„, ํžˆ์Šคํ† ๊ทธ๋žจ, ์‚ฐ์ ๋„, ํŒŒ์ด ์ฐจํŠธ ๋“ฑ ๋‹ค์–‘ํ•œ ์‹œ๊ฐํ™” ๋ฐฉ์‹์„ ์ง€์›๊ทธ๋ž˜ํ”„๋ฅผ ์ƒ‰์ƒ, ์Šคํƒ€์ผ, ๋ ˆ์ด๋ธ”, ์ถ• ๋ฒ”์œ„ ๋“ฑ์„ ์กฐ์ ˆํ•˜์—ฌ ์›ํ•˜๋Š” ํ˜•ํƒœ๋กœ ์‹œ๊ฐํ™”ํ•  ์ˆ˜ ์žˆ์Œ๊ทธ๋ž˜ํ”„ ๊ทธ๋ฆฌ๊ธฐ ๋„๊ตฌmatplotlib๋กœ ๊ทธ๋ž˜ํ”„ ๊ทธ๋ฆฌ๊ธฐimport pandas as pdimport matplotlib.pyplot as plt ๐Ÿ’ฝ ์˜ˆ์‹œ ๋ฐ์ดํ„ฐ์…‹๋”๋ณด๊ธฐnewjeans = pd.DataFrame({ 'name' : ['Minji','Hanni','Danielle','Haerin', 'Hyein'], 'age' : [20, ..
240510 Today I Learn๐Ÿ‘พ UnboundLocalError: local variable referenced before assignmentํ•จ์ˆ˜ ๋ฐ–์—์„œ ์„ ์–ธํ•œ ๋ณ€์ˆ˜(Global Variable)๋ฅผ ํ•จ์ˆ˜ ๋‚ด(Local Variable)์—์„œ ์‚ฌ์šฉ/๋ณ€๊ฒฝ ํ–ˆ์„ ๋•Œ ๋ฐœ์ƒํ•˜๋Š” ์—๋Ÿฌ๋ฌธ์ œ์ƒํ™ฉ ํ”„๋กœ๊ทธ๋ž˜๋จธ์Šค์ฝ”๋“œ ์ค‘์‹ฌ์˜ ๊ฐœ๋ฐœ์ž ์ฑ„์šฉ. ์Šคํƒ ๊ธฐ๋ฐ˜์˜ ํฌ์ง€์…˜ ๋งค์นญ. ํ”„๋กœ๊ทธ๋ž˜๋จธ์Šค์˜ ๊ฐœ๋ฐœ์ž ๋งž์ถคํ˜• ํ”„๋กœํ•„์„ ๋“ฑ๋กํ•˜๊ณ , ๋‚˜์™€ ๊ธฐ์ˆ  ๊ถํ•ฉ์ด ์ž˜ ๋งž๋Š” ๊ธฐ์—…๋“ค์„ ๋งค์นญ ๋ฐ›์œผ์„ธ์š”.programmers.co.krdef solution(answers): tf={} answer = {'1':cnt1, '2':cnt2, '3':cnt3} math = {'1' :[1,2,3,4,5],'2':[2,1,2,3,2,4,2,5], '..
ny:D
'๐Ÿ“’ Today I Learn' ์นดํ…Œ๊ณ ๋ฆฌ์˜ ๊ธ€ ๋ชฉ๋ก (9 Page)