如何添加多个趋势线熊猫

Question

我绘制了一个带有两个y轴的图形，现在想为每个y图添加两条不同的趋势线。

这是我的代码：

import matplotlib.pyplot as plt 
import pandas as pd
import numpy as np
%matplotlib inline

amp_costs=pd.read_csv('/Users/Ampicillin_Costs.csv', index_col=None, usecols=[0,1,2])
amp_costs.columns=['PERIOD', 'ITEMS', 'COST PER ITEM']

ax=amp_costs.plot(x='PERIOD', y='COST PER ITEM', color='Blue', style='.', markersize=10)
amp_costs.plot(x='PERIOD', y='ITEMS', secondary_y=True,
color='Red', style='.', markersize=10, ax=ax)

非常感谢有关如何将这两条趋势线绘制到此图表的任何指导！

Answer 1

以下是如何使用sklearn.linear_model.LinearRegression制作趋势线的快速示例。

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
plt.style.use('ggplot')
%matplotlib inline

period = np.arange(10)
items = -2*period +1 + np.random.randint(-2,2,len(period))
cost = 35000*period +15000 + np.random.randint(-25000,25000,len(period))
data = np.vstack((period,items,cost)).T
df = pd.DataFrame(data, columns=\['P','ITEMS', 'COST'\]).set_index('P')


lmcost = LinearRegression().fit(period.reshape(-1,1), cost.reshape(-1,1))
lmitems = LinearRegression().fit(period.reshape(-1,1), items.reshape(-1,1))

df['ITEMS_LM'] = lmitems.predict(period.reshape(-1,1))
df['COST_LM'] = lmcost.predict(period.reshape(-1,1))

fig,ax = plt.subplots()


df.ITEMS.plot(ax = ax, color = 'b')
df.ITEMS_LM.plot(ax = ax,color= 'b', linestyle= 'dashed')
df.COST.plot(ax = ax, secondary_y=True, color ='g')
df.COST_LM.plot(ax = ax, secondary_y=True, color = 'g', linestyle='dashed')