我有一個問題陳述要在5 個 CSV演算法檔案上繪制圖形并比較其中更好的演算法
csv 檔案僅包含100 行 * 4 列 的浮點數 我繪制了 kdeplot 比較5 個 csv 檔案的第一列
所以我這樣編碼問題：
from cProfile import label
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
plt.style.use("fivethirtyeight")
sns.set_theme()
sns.color_palette("bright")
data1 = pd.read_csv("D:/C /Programs/Python/Input/appendicitis/alg1/AverageIter1000.csv", on_bad_lines='skip', nrows= 100 , usecols=[0,1,2,3] , header = None)
data2 = pd.read_csv("D:/C /Programs/Python/Input/appendicitis/alg2/AverageIter1000.csv", on_bad_lines='skip', nrows= 100 , usecols=[0,1,2,3] , header = None)
data3 = pd.read_csv("D:/C /Programs/Python/Input/appendicitis/alg3/AverageIter1000.csv", on_bad_lines='skip', nrows= 100 , usecols=[0,1,2,3] , header = None)
data4 = pd.read_csv("D:/C /Programs/Python/Input/appendicitis/alg4/AverageIter1000.csv", on_bad_lines='skip', nrows= 100 , usecols=[0,1,2,3] , header = None)
data5 = pd.read_csv("D:/C /Programs/Python/Input/appendicitis/alg5/AverageIter1000.csv", on_bad_lines='skip', nrows= 100 , usecols=[0,1,2,3] , header = None)
sns.kdeplot(np.array(data1[0]), shade = True, linewidth = 2, label = 'arg1')
sns.kdeplot(np.array(data2[0]), shade = True, linewidth = 2, label = 'arg2')
sns.kdeplot(np.array(data3[0]), shade = True, linewidth = 2, label = 'arg3')
sns.kdeplot(np.array(data4[0]), shade = True, linewidth = 2, label = 'arg4')
sns.kdeplot(np.array(data5[0]), shade = True, linewidth = 2, label = 'arg5')
plt.xlabel("Accuracy")
plt.ylabel("Accuracy-Density")
plt.title("Accuracy graph visualisation")
plt.legend()
plt.show()
它可以繪制圖表，但我主要需要的是突出顯示每個圖表中的平均點。那么如何做到這一點請幫助我
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標籤：Python 熊猫 CSV matplotlib 海运