貌似是在吴军的谷歌方法论中看到过类似的论述，国家的竞争最终是人的竞争，企业的竞争也是一样。一家企业的人均利润如果逐年呈现上升态势，说明企业正走在正确的发展道路上。
所以我使用聚款数据将我期待的数据进行了查找并呈现，选取的股票都是多数机构评级较高的股票。
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from jqdata import finance
def profit_per_employ(stock_code):
d_employee = finance.run_query(
query(
finance.STK_EMPLOYEE_INFO
).filter(
finance.STK_EMPLOYEE_INFO.code==stock_code
).order_by(
finance.STK_EMPLOYEE_INFO.end_date.desc()
).limit(10)
)
d_employee['profit'] = None
d_employee['pro_rate'] = None
p = np.zeros(len(d_employee))
for i in range(len(d_employee)):
d_temp = get_fundamentals(
query(
income.net_profit
).filter(
income.code == stock_code
),date = d_employee.end_date.iloc[i]
)
if len(d_temp)>0:
p[i] = d_temp.net_profit.iloc[0].copy()
d_employee.profit = p
d_employee = d_employee.drop(
['id','company_id','graduate_rate','middle_rate','college_rate','pub_date','retirement'] ,
axis = 1)
d_employee.pro_rate = (d_employee.profit / d_employee.employee).values
d_employee.index = d_employee.end_date
#d_employee.pro_rate.plot()
return d_employee.name.iloc[0],d_employee.code.iloc[0],d_employee.pro_rate
s = '000776.002007.002371.002594.002677.002707.002747.300012.300037.\
300070.300073.300144.300251.300747.300750.600030.600036.600054.\
600305.600315.600588.600660.600754.600837.601211.601633.601688.\
601766.603027.603288.603799.603866.603877.603899.000002.000024.\
000063.000333.000568.000661.000858.001979.002024.002475.002511.\
002624.002916.300003.600031.600048.600104.600323.600426.600438.\
600486.600519.600809.600872.600887.601012.601155.601233.601336.\
601888.603517.603588'
s = s.split('.')
s = np.sort(s)
lenth_s = len(s)
fig,axes = plt.subplots(33,2,figsize=(20,120))
fig.subplots_adjust( hspace = 0.5)
for i,ax in enumerate(axes.flat):
n = normalize_code(s[i])
name,code,pro_rate = profit_per_employ(n)
ax.plot(pro_rate,'-')
title = code + '.' + name
ax.set_title(title)
plt.show()
