๋ณธ๋ฌธ ๋ฐ”๋กœ๊ฐ€๊ธฐ
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normalization

3/18 ๊ธˆ ๋ถˆ๊ธˆ! ๐Ÿ˜ป DataFrame์ด ์ œ๊ณตํ•˜๋Š” ๋ถ„์„์šฉ ํ•จ์ˆ˜๋“ค๋กœ ๊ธฐ์ˆ  ๋ถ„์„(Descriptive Analysis)์— ํ•„์š”ํ•œ ํ‰๊ท , ํ‘œ์ค€ํŽธ์ฐจ, ๋ถ„์‚ฐ, ๊ณต๋ถ„์‚ฐ, ์ƒ๊ด€๊ณ„์ˆ˜, ์‚ฌ๋ถ„์œ„ ๊ตฌํ•จ 1. ์ง‘๊ณ„ ํ•จ์ˆ˜๋ฅผ ์ด์šฉํ•  ๋•Œ axis๋ฅผ ์ง€์ •ํ•˜์ง€ ์•Š์œผ๋ฉด default๋Š” 0, ํ–‰ ๋ฐฉํ–ฅ. ์—ด๋ผ๋ฆฌ ๋”ํ•จ. dropna=True๊ฐ€ default์ด๋ฏ€๋กœ ์—ฐ์‚ฐ์—์„œ ์ œ์™ธ import numpy as np import pandas as pd data = np.array([[2, np.nan], # np.nan ๊ฒฐ์น˜๊ฐ’ [7, -3], [np.nan, np.nan], [1, -2]]) # print(data) df = pd.DataFrame(data, columns=['one', 'two'], index=['a', 'b', 'c', 'd']) disp.. ๋”๋ณด๊ธฐ
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