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python中的叠加交互可视化_Python_Plot_Graph_Data Visualization_Visualization - Fatal编程技术网

python中的叠加交互可视化

python中的叠加交互可视化,python,plot,graph,data-visualization,visualization,Python,Plot,Graph,Data Visualization,Visualization,我想可视化两个数据之间的交互。原始(绿色)和预测(棕色)。顶行的长度从200到-20,底行的长度从-20到200 对于上表,我希望以下面的格式进行可视化 代码我已经试过了 def newline(p1, p2, color='black'): ax = plt.gca() fig, ax = plt.subplots(1,1,figsize=(5,5), dpi= 60) ax.hlines(y=1, xmin=-20, xmax=200, color='b

我想可视化两个数据之间的交互。原始(绿色)和预测(棕色)。顶行的长度从200到-20,底行的长度从-20到200

对于上表,我希望以下面的格式进行可视化

代码我已经试过了

    def newline(p1, p2, color='black'):
      ax = plt.gca()

   fig, ax = plt.subplots(1,1,figsize=(5,5), dpi= 60)
   ax.hlines(y=1, xmin=-20, xmax=200, color='black', alpha=0.7)
   ax.hlines(y=1.1, xmin=-20, xmax=200, color='black', alpha=0.7)


   plt.rcParams['xtick.bottom'] = plt.rcParams['xtick.labelbottom'] = True
   plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
   ax.yaxis.set_visible(False)
   plt.box(False)        

那会对你有帮助的


谢谢

请展示您的尝试。这不是免费的编码服务。从一些matplotlib示例开始,请发布代码的图像并解释您的方法。你是怎么解决的?那会对你有帮助的。
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd

def newline(p1, p2, color='black'):
ax = plt.gca()

df = pd.read_excel('visual.xlsx', sheet_name='Sheet2')
prediction_list = df['prediction'].tolist()
originale_list = df['original'].tolist()
result_prediction = []
result_original = []

for i in range(len(prediction_list)):
temp = []
test = prediction_list[i].split('&')
for j in range(len(test)):
temp = []
temp.append(200 - int(test[j].split(':')[0]))
temp.append(int(test[j].split(':')[1]))
result_prediction.append(temp)

for i in range(len(originale_list)):
temp = []
test = originale_list[i].split('&')
for j in range(len(test)):
temp = []
temp.append(200 - int(test[j].split(':')[0]))
temp.append(int(test[j].split(':')[1]))
result_original.append(temp)

fig, ax = plt.subplots(1,1,figsize=(20,5), dpi= 60)
ax.hlines(y=1, xmin=200, xmax=-20, color='black', alpha=0.7)
ax.hlines(y=2, xmin=200, xmax=-20, color='black', alpha=0.7)                                                                                                                                                                                                                                                     -20')

for i in range(len(result_prediction)):
plt.plot(result_prediction[i], [2, 1], color='brown')
for i in range(len(result_original)):
plt.plot(result_original[i], [2, 1], color='green')

plt.rcParams['xtick.bottom'] = plt.rcParams['xtick.labelbottom'] = True
plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
ax.yaxis.set_visible(False)
plt.box(False)

plt.savefig('test.png')
plt.show()