下面尝试使您的代码具有可复制性:
import numpy as np
import matplotlib.pyplot as plt
# note: it is much better than a printout of the variable, you can
# actually use this data in *days* variable to work with your example
days = [350.0, 641.0, 389.0, 130.0, 344.0, 92.0, 392.0, 51.0, 28.0, 358.0,
309.0, 64.0, 380.0, 491.0, 332.0, 410.0, 66.0, 435.0, 156.0, 294.0,
75.0, 284.0, 105.0, 34.0, 50.0, 155.0, 427.0, 327.0, 116.0, 97.0,
274.0, 315.0, 99.0, 70.0, 62.0, 241.0, 397.0, 50.0, 41.0, 231.0,
238.0, 216.0, 105.0, 36.0, 192.0, 38.0, 122.0, 37.0, 236.0, 175.0,
138.0, 146.0, 125.0, 144.0, 166.0, 19.0, 155.0, 130.0, 54.0, 120.0,
65.0, 95.0, 158.0, 92.0, 65.0, 52.0, 91.0, 67.0, 38.0, 72.0, 36.0,
14.0, 74.0, 155.0, 503.0, 110.0, 338.0, 444.0, 408.0, 107.0, 214.0,
291.0, 91.0, 277.0, 96.0, 325.0, 154.0, 314.0, 377.0, 147.0, 48.0,
224.0, 75.0, 268.0, 135.0, 177.0, 133.0, 306.0, 187.0, 145.0, 353.0,
148.0, 182.0, 95.0, 82.0, 64.0, 143.0, 79.0, 168.0, 141.0, 224.0, 82.0,
202.0, 107.0, 169.0, 153.0, 156.0, 79.0, 49.0, 126.0, 44.0, 67.0, 64.0,
102.0, 74.0, 56.0, 102.0, 285.0, 386.0, 176.0, 106.0, 6.0, 322.0, 72.0,
192.0, 429.0, 101.0, 159.0, 168.0, 319.0, 178.0, 323.0, 295.0, 151.0,
286.0, 93.0, 336.0, 252.0, 111.0, 49.0, 113.0, 214.0, 230.0, 77.0,
192.0, 219.0, 166.0, 72.0, 143.0, 166.0, 140.0, 191.0, 113.0, 83.0,
41.0, 28.0, 84.0, 78.0, 28.0, 202.0, 223.0, 188.0, 238.0, 212.0, 133.0,
235.0, 212.0, 243.0, 176.0, 167.0, 69.0, 108.0, 11.0, 35.0, 63.0, 38.0,
111.0, 135.0, 143.0, 70.0, 143.0]
def get_bounds(ys):
quartile_1, quartile_3 = np.percentile(ys, [25, 75])
iqr = quartile_3 - quartile_1
lower_bound = quartile_1 - (iqr * 1.5)
upper_bound = quartile_3 + (iqr * 1.5)
return lower_bound, upper_bound
def get_upper_outliers(ys):
lower_bound, upper_bound = get_bounds(days)
return [y for y in ys if y >= upper_bound]
def get_lower_outliers(ys):
lower_bound, upper_bound = get_bounds(days)
return [y for y in ys if y <= lower_bound]
max_outliers = get_upper_outliers(days)
min_outliers = get_lower_outliers(days)
assert max_outliers== [641.0, 491.0, 503.0]
assert min_outliers == []
percentiles = np.array([0, 25, 50, 75, 100])
x_p = np.percentile(days, percentiles)
y_p = percentiles
_ = plt.plot(x_p, y_p, marker='D', color='red', linestyle='none')
ax=plt.gca()
# my approximation of ax.fill_betweenx does not look right, but it is close
# note ax.fill_betweenx and ax.fill_between are different fucntions!
if min_outliers:
ax.fill_betweenx(y_p, 0, np.max(min_outliers), facecolor='red', alpha=0.3)
if max_outliers:
ax.fill_betweenx(y_p, np.min(max_outliers), x_p[4], facecolor='red', alpha=0.3)
