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脂酰CoA经肉碱转运到线粒体中进行β-氧化(脱氧→水化→再脱氧→硫解)。import matplotlib.pyplot as pltpd.options.display.mpl_style = 'default' # Sets the plotting display theme to ggplot2df.plot(kind = 'box')# Import the seaborn libraryimport seaborn as sns# Do the boxplotplt.show(sns.boxplot(df, widths = 0.5, color = "pastel"))import numpy as npimport scipy.stats as ssdef case(n = 10, mu = 3, sigma = np.sqrt(5), p = 0.025, rep = 100): m = np.zeros((rep, 4)) for i in range(rep): norm = np.random.normal(loc = mu, scale = sigma, size = n) xbar = np.mean(norm) low = xbar - ss.norm.ppf(q = 1 - p) * (sigma / np.sqrt(n)) up = xbar + ss.norm.ppf(q = 1 - p) * (sigma / np.sqrt(n)) if (mu > low) & (mu < up): rem = 1 else: rem = 0 m[i, :] = [xbar, low, up, rem] inside = np.sum(m[:, 3]) per = inside / rep desc = "There are " + str(inside) + " confidence intervals that contain " "the true mean (" + str(mu) + "), that is " + str(per) + " percent of the total CIs" return {"Matrix": m, "Decision": desc}import numpy as npimport scipy.stats as ssdef case2(n = 10, mu = 3, sigma = np.sqrt(5), p = 0.025, rep = 100): scaled_crit = ss.norm.ppf(q = 1 - p) * (sigma / np.sqrt(n)) norm = np.random.normal(loc = mu, scale = sigma, size = (rep, n)) xbar = norm.mean(1) low = xbar - scaled_crit up = xbar + scaled_crit rem = (mu > low) & (mu < up) m = np.c_[xbar, low, up, rem] inside = np.sum(m[:, 3]) per = inside / rep desc = "There are " + str(inside) + " confidence intervals that contain " "the true mean (" + str(mu) + "), that is " + str(per) + " percent of the total CIs" return {"Matrix": m, "Decision": desc}12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758h3d动漫在线观sum(df['ability’]) 计算整个列的和

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