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cartman0 2018/12/06
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seabornã§Matplotlibã®è¦‹ãŸç›®ã‚’è‰¯ãã™ã‚‹ | note.nkmk.me
seabornã¯matplotlibãƒ™ãƒ¼ã‚¹ã®çµ±è¨ˆãƒ‡ãƒ¼ã‚¿ãƒ“ã‚¸ãƒ¥ã‚¢ãƒ©ã‚¤ã‚¼ãƒ¼ã‚·ãƒ§ãƒ³ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã€‚ Seaborn is a Python visualization library based on matplotlib. seaborn: statistical data visualization â€” seaborn 0.6.0 documentation statisticalã¨éŠ˜æ‰“ã£ã¦ã„ã‚‹ã ã‘ã‚ã£ã¦ã€çµ±è¨ˆçš„ãªãƒ‡ãƒ¼ã‚¿ã‚’ãƒ—ãƒãƒƒãƒˆã™ã‚‹ãŸã‚ã®æ©Ÿèƒ½ãŒãŸãã•ã‚“ç”¨æ„ã•ã‚Œã¦ã„ã‚‹ãŒã€æ™®é€šã®æŠ˜ã‚Œç·šã‚°ãƒ©ãƒ•ã®è¦‹ãŸç›®ã‚’è‰¯ãã™ã‚‹ãŸã‚ã ã‘ã«ã‚‚ä½¿ãˆã‚‹ã€‚ import numpy as np import matplotlib.pyplot as plt import seaborn as sns sns.set() sns.set_style("whitegrid", {'grid.linestyle': '--'})
cartman0 2016/06/06
SNS

matplotlib

seaborn

Python
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%matplotlib inline import matplotlib.pyplot as plt import matplotlib.cm as cm import numpy as np import seaborn as sns import numpy.random as rd m = 10 s = 3 min_x = m-4*s max_x = m+4*s x = np.linspace(min_x, max_x, 201) y = (1/np.sqrt(2*np.pi*s**2))*np.exp(-0.5*(x-m)**2/s**2) plt.figure(figsize=(8,5)) plt.xlim(min_x, max_x) plt.ylim(0,max(y)*1.1) plt.plot(x,y) plt.show() ã“ã®å›³ã¯ã€å¹³å‡$\mu$ã€æ¨™æº–åå·®$\sigma$
cartman0 2015/11/25
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cartman0 2015/10/10
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cartman0 2015/08/18
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cartman0 2015/05/28
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