我正在為我的公司調整機器，并且與參考相比，我正在制作有關機器偏移的報告。
我想可視化我所做的措施的手段和不確定性。我在每臺機器的 3 個不同溫度下進行了 3 次測量，我想在 1 個圖表中可視化所有這些結果。我目前對每個溫度范圍都有一個圖表。這是我目前擁有的圖片：
我盡力在這里表達我想要的東西：
有人可以幫助我嗎？
您會注意到我的資料可能沒有以正確的方式構建以獲得我想要的結果，如果你們也對此有所了解，那將非常感激。
import matplotlib.pyplot as plt
import pandas as pd
MachineName= ["54711819", "54711829", "54713465", "54713479", "54713491", "54713489", "54711832", "54711840", "54713470", "54711807", "54711831", "54711824"]
## Results at 23 degrees ##
Means= [0.120443092,0.159498955,0.134366394,0.12231916,0.251042458,0.146193291,-0.027391228,0.036317345,0.215634285, 0.20710271,0.137419749,0.160709506] ## 23 degré
Incertitudek2 = [0.0126929,0.014290776,0.018074659,0.0178294, 0.016065171,0.027976306,0.015061493,0.019834669,0.026091469,0.017817986,0.021138409,0.016838815] ## 23 degré
## Results at 38 degrees ##
#Means= [0.1365,0.2642,0.0511,0.0929,0.3322,0.1179,0.0380,-0.05033,0.1530,0.229472906,0.206441519,0.071041205] ## 38 degré
#Incertitudek2 = [0.0260,0.0707,0.0364,0.0247,0.0660,0.0320,0.0406,0.0615,0.0331,0.027292924,0.035794638,0.024939662] ## 38 degré
## Results at 8 degrees ##
#Means= [0.1087,-0.0625,0.1808,0.1400,0.0986,0.1576,-0.1249,0.1309,0.2684,0.137355552,-0.010638585,0.271221119] ## 8 degré
#Incertitudek2 = [0.0246,0.0379,0.0190,0.0268,0.0355,0.0296,0.0334,0.0250,0.0324,0.025887426,0.033329347,0.030091242] ## 8 degré
plt.errorbar(MachineName, Means, yerr =Incertitudek2,fmt='o',ecolor = 'black',color='red', elinewidth=3)
plt.axhline(y=0.0, color='r', linestyle='-')
plt.grid()
plt.xlabel("Sonde #")
plt.ylabel("écart de température (°C)")
plt.title("[Range 23°C] Calcul sur 50 points par rapport à une sonde référence incertitude K=2")
plt.ylim((-0.2,0.42))
plt.show()
uj5u.com熱心網友回復：
我確信使用 Pandas 有一種很好且快速的方法，但這個答案將向您展示如何使用 Matplotlib 獲得它。請注意，我不會說法語，所以您可能需要更改標題 :)
第一個解決方案：與您提出的有點不同，因為它顯示的是圖例而不是輔助 x 軸。您可以使用 和 的值offset來figsize為圖表提供或多或少的間距。
MachineName = ["54711819", "54711829", "54713465", "54713479", "54713491", "54713489", "54711832", "54711840", "54713470", "54711807", "54711831", "54711824"]
Means_23 = [0.120443092,0.159498955,0.134366394,0.12231916,0.251042458,0.146193291,-0.027391228,0.036317345,0.215634285, 0.20710271,0.137419749,0.160709506]
Incertitudek2_23 = [0.0126929,0.014290776,0.018074659,0.0178294, 0.016065171,0.027976306,0.015061493,0.019834669,0.026091469,0.017817986,0.021138409,0.016838815]
Means_38 = [0.1365,0.2642,0.0511,0.0929,0.3322,0.1179,0.0380,-0.05033,0.1530,0.229472906,0.206441519,0.071041205]
Incertitudek2_38 = [0.0260,0.0707,0.0364,0.0247,0.0660,0.0320,0.0406,0.0615,0.0331,0.027292924,0.035794638,0.024939662]
Means_8 = [0.1087,-0.0625,0.1808,0.1400,0.0986,0.1576,-0.1249,0.1309,0.2684,0.137355552,-0.010638585,0.271221119]
Incertitudek2_8 = [0.0246,0.0379,0.0190,0.0268,0.0355,0.0296,0.0334,0.0250,0.0324,0.025887426,0.033329347,0.030091242]
x = np.arange(0, len(MachineName))
plt.figure(figsize=(13, 5))
offset = 0.15
plt.errorbar(x-offset, Means_8, yerr=Incertitudek2_8,fmt='o', elinewidth=3, label="8°C")
plt.errorbar(x, Means_23, yerr=Incertitudek2_23,fmt='o', elinewidth=3, label="23°C")
plt.errorbar(x offset, Means_38, yerr=Incertitudek2_38,fmt='o', elinewidth=3, label="38°C")
plt.axhline(y=0.0, color='r', linestyle='-')
plt.grid()
plt.xlabel("Sonde #")
plt.ylabel("écart de température (°C)")
plt.title("[Range 23°C] Calcul sur 50 points par rapport à une sonde référence incertitude K=2")
plt.xticks(x, MachineName)
plt.ylim((-0.2,0.42))
plt.legend()
plt.show()
第二種解決方案：為了更接近您的建議，我們需要添加一個輔助 x 軸。
x = np.arange(0, len(MachineName))
f = plt.figure(figsize=(13, 5))
ax1 = f.add_subplot(1, 1, 1)
ax2 = ax1.twiny()
ax2.xaxis.set_ticks_position("bottom")
ax2.xaxis.set_label_position("bottom")
offset_cat = 0.25
offset_axis_label = 40
ax1.errorbar(x-offset_cat, Means_8, yerr=Incertitudek2_8,fmt='o', elinewidth=3)
ax1.errorbar(x, Means_23, yerr=Incertitudek2_23,fmt='o', elinewidth=3)
ax1.errorbar(x offset_cat, Means_38, yerr=Incertitudek2_38,fmt='o', elinewidth=3)
ax1.axhline(y=0.0, color='r', linestyle='-')
ax1.grid()
ax1.set_xlabel("Sonde #", labelpad=offset_axis_label/3)
ax1.set_ylabel("écart de température (°C)")
ax1.set_title("[Range 23°C] Calcul sur 50 points par rapport à une sonde référence incertitude K=2")
ax1.set_xticks(x, MachineName)
ax1.tick_params(axis='x', direction='out', pad=offset_axis_label)
ax1.set_xlim(x[0] - 1, x[-1] 1)
ax1.set_ylim((-0.2,0.42))
xticks = np.zeros(3 * len(MachineName))
xtick_labels = []
for i in range(len(MachineName)):
xticks[3*i:3*i 3] = [i - offset_cat, i, i offset_cat]
# NOTE: these labels must have the same order of the ax1.errorbar commands
xtick_labels = ["8°C", "23°C", "38°C"]
ax2.set_xticks(xticks, xtick_labels, rotation=90)
ax2.set_xlim(x[0] - 1, x[-1] 1)
plt.show()
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