def findWeightAverage(x,
n=12,
t=configger.T,
sort_column='date',
value_column='净利润',
last_date=''):
index = x.index[0]
x = x.copy()
x.sort_values(by=[sort_column], ascending=False, inplace=True)
if (last_date != ''):
x = x.loc[x[sort_column] >= last_date]
else:
x = x[0:n]
x = deleteNullColumn(x, value_column)
x.reset_index(inplace=True)
x = x[[value_column, sort_column]]
profit = pd.Series(dtype=float)
weight = pd.Series(dtype=float)
result = pd.DataFrame()
n = len(x)
for i in range(0, n):
date = pd.to_datetime(x.loc[i, sort_column])
date = Period(date, freq='Q')
date = date.strftime('%yQ%q')
column = str(date) + value_column
weight.loc[column] = float(math.pow(math.e, -i * t))
profit.loc[column] = float(x.loc[i, value_column])
result.loc[index, column] = float(x.loc[i, value_column])
weightAverage = (weight * profit).sum() / weight.sum()
result.loc[index, 'weightAverage'] = weightAverage
return result
def test_strftime(self):
p = Period('2000-1-1 12:34:12', freq='S')
res = p.strftime('%Y-%m-%d %H:%M:%S')
assert res == '2000-01-01 12:34:12'
assert isinstance(res, text_type) # GH3363
from datetime import datetime
import pandas as pd
# operation=pd.DataFrame()
# operation.loc[0,'name']='tb_today_industry'
# operation.loc[0,'updateTime']=datetime.now().date()
# print(operation)
from pandas import Period
a = datetime.now()
a = Period(a, freq='Q')
a.strftime(('%F-Q%q'))
print(a)
def test_strftime(self):
p = Period('2000-1-1 12:34:12', freq='S')
res = p.strftime('%Y-%m-%d %H:%M:%S')
assert res == '2000-01-01 12:34:12'
assert isinstance(res, text_type) # GH3363
def test_strftime(self):
# GH#3363
p = Period("2000-1-1 12:34:12", freq="S")
res = p.strftime("%Y-%m-%d %H:%M:%S")
assert res == "2000-01-01 12:34:12"
assert isinstance(res, str)
