[ํ์ด์ฌ] pandas
pandas์ DataFrameNumPy๋ณต์กํ ์ํ ์ฐ์ฐ์ ํ ๋ ์ฌ์ฉNumPy array ๋จ์ - ๊ฐ๋
์ฑ์ด ๋จ์ด์ง- ์ ๋ณด์ ๋ํ ๋ ์ด๋ธ ์ฝ์
๋ถ๊ฐ- ํ ๊ฐ์ง ๋ฐ์ดํฐ ํ์
๋ง ์ฌ์ฉ ๊ฐ๋ฅ pandasNumPy๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๋ง๋ค์ด์ง ๋ฐ์ดํฐ ๋ถ์ ๋ผ์ด๋ธ๋ฌ๋ฆฌ๋ฐ์ดํฐ ๋ถ๋ฌ์ค๊ธฐ, ๊ฐ๊ณตํ๊ธฐ, ๋ถ์ํ๊ธฐ, ์๊ฐํํ๊ธฐ ๋ฑ ํ ํํ์ ๋ฐ์ดํฐ๋ฅผ ๊ฐํธํ๊ฒ ๋ค๋ฃจ๊ณ ์ถ์ ๋ ์ฌ์ฉ 4๊ฐ์ ํ(๋ก์ฐ) 3๊ฐ์ ์ด(์ปฌ๋ผ)0,1,2,3 = ๋ก์ฐ์ ์ด๋ฆ/์ธ๋ฑ์ค DataFrame์ ๋ง๋๋ ๋ค์ํ ๋ฐฉ๋ฒimport pandas as pdimport numpy as npdict_df = pd.DataFrame({ 'category': ['skirt', 'sweater', 'coat', 'jeans'], 'quantity': [10, 15, 6..
2025. 2. 25.
[ํ์ด์ฌ] Matplotlib
Matplotlib๊ณผ ๋ฐ์ดํฐ ์๊ฐํํ์ด์ฌ๊ณผ ๋ํ์ด๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๋ฐ์ดํฐ๋ฅผ ์๊ฐํํ๋ ๋ผ์ด๋ธ๋ฌ๋ฆฌ ๋ค์ํ ๊ทธ๋ํ ๊ทธ๋ ค๋ณด๊ธฐ ์ค์ตimport numpy as npimport matplotlib.pyplot as pltsales_array = np.array([10, 13, 8, 15, 6, 11, 4])category_array = ['skirt', 't-shirt', 'dress', 'sweater', 'coat', 'jeans', 'shoes']# ์ฌ๊ธฐ์ ์ฝ๋๋ฅผ ์์ฑํ์ธ์.plt.bar(category_array, sales_array)plt.show()๊ฒฐ๊ณผ ๊ทธ๋ํ ๊ฐ๋จํ๊ฒ ๊พธ๋ฏธ๊ธฐ ๊ทธ์ธ ์ต์
matplotlib.markers — Matplotlib 3.10.0 documentationmatplotlib.mark..
2025. 2. 25.
[ํ์ด์ฌ] NumPy
NumPy๋?Numerical Python ์์น์ ์ธ ์ฐ์ฐ์ ์ต์ ํ๋ ํ์ด์ฌ ๋๊ตฌ NumPy์ array ์ธ๋ฑ์ฑ๊ณผ ์ฌ๋ผ์ด์ฑ: 1์ฐจ์ array ์ค์ตimport numpy as npbitcoin_array = np.array([970, 1180, 1072, 1348, 2286, 2481, 2875, 4703, 4339, 6468, 10234, 14156])# ์ฌ๊ธฐ์ ์ฝ๋๋ฅผ ์์ฑํ์ธ์.bitcoin_array[6:9]#๊ฒฐ๊ณผ#array([2875, 4703, 4339]) ์ธ๋ฑ์ฑ๊ณผ ์ฌ๋ผ์ด์ฑ: 2์ฐจ์ array ์ค์ตimport numpy as npbitcoin_array = np.array([[970, 1180, 1072, 1348, 2286, 2481, ..
2025. 2. 25.
[ํ์ด์ฌ] ๋ฆฌ์คํธ/์ฌ์ ๊ณผ for ๋ฐ๋ณต๋ฌธ
๋ฆฌ์คํธ๋ฆฌ์คํธ์ ์์, ์ธ๋ฑ์ฑ# ๋ฆฌ์คํธ (list)numbers = [2, 3, 5, 7, 11, 13]names = ['์ค์',' ํ๋ฆฐ', 'ํํธ', '์ํ']print(numbers)print(names)# [2, 3, 5, 7, 11, 13]# ['์ค์', ' ํ๋ฆฐ', 'ํํธ', '์ํ']#์ธ๋ฑ์ฑ (indexing)print(names[1]) #ํ๋ฆฐprint(numbers[1] + numbers[3]) #10num_1 = numbers[1]num_3 = numbers[3]print(num_1 + num_3) #10#๋ง์ด๋์ค ์ธ๋ฑ์ฑprint(numbers[-1]) #13print(numbers[-6]) #2#๋ฆฌ์คํธ ์ฌ๋ผ์ด์ฑ (list slicing)print(numbers[0:4]) #[2,..
2025. 2. 24.