How to do with self.broker.getvalue() which return NAN when do portfolio with different public date?

[ArronTian]

when i run a portfolio strategy, the stocks have different public date, so I fill data with method ffill in python fillna, when i run the strategy, I find that i could not order buy or sell because when i get portfolio value by self.broker.getvalue which is NAN, i could not calculate the order size……help me, how to cope with it ?
the error is :
Traceback (most recent call last):
File "Z:/QEPM_BackTest/src/dev/Backtest/single_factor_backtrade.py", line 360, in <module>
run()
File "Z:/QEPM_BackTest/src/dev/Backtest/single_factor_backtrade.py", line 345, in run
thestrats = cerebro.run()
File "D:\Anaconda\lib\site-packages\backtrader\cerebro.py", line 1127, in run
runstrat = self.runstrategies(iterstrat)
File "D:\Anaconda\lib\site-packages\backtrader\cerebro.py", line 1293, in runstrategies
self._runonce(runstrats)
File "D:\Anaconda\lib\site-packages\backtrader\cerebro.py", line 1695, in _runonce
strat._oncepost(dt0)
File "D:\Anaconda\lib\site-packages\backtrader\strategy.py", line 309, in _oncepost
self.next()
File "Z:/QEPM_BackTest/src/dev/Backtest/single_factor_backtrade.py", line 249, in next
self.rebalance_portfolio()
File "Z:/QEPM_BackTest/src/dev/Backtest/single_factor_backtrade.py", line 284, in rebalance_portfolio
size = int(p_value / 100 / data.close[0]) * 100
ValueError: cannot convert float NaN to integer

the following is my code:
class S_factors(bt.Strategy):
params = dict(
period=20,
printlog=True, )

def __init__(self):
    print("\n" + "*" * 30 + " Start trading " + "*" * 30)
    self.order = None

def log(self, txt, dt=None, doprint=True):
    if self.params.printlog or doprint:
        dt = dt or self.datetime.date(0)
        print(f'{dt.isoformat()} {txt}')

def notify_order(self, order):
    if order.status in [order.Submitted, order.Accepted]:
        return
    if order.status in [order.Completed]:
        if order.isbuy():
            self.log(f'{self.broker.cash} {self.broker.getvalue()}')
        else:
            sself.log(f'{self.broker.cash} {self.broker.getvalue()}')
    elif order.status in [order.Canceled]:
        self.log(f'{self.broker.cash} {self.broker.getvalue()}')
    elif order.status in [order.Margin]:
       self.log(f'{self.broker.cash} {self.broker.getvalue()}')
    elif order.status in [order.Rejected]:
        self.log(f'{self.broker.cash} {self.broker.getvalue()}')
    self.order = None

def prenext(self):
    self.next() 

def next(self):
   self.broker.getcash())
    if len(self.datas[0]) == self.data0.buflen():
        return
    if self.datas[0].is_resetday[0] == 1 \
            and datetime.strptime(str(self.datetime.date(0)), "%Y-%m-%d") > datetime.strptime("2014-03-17", "%Y-%m-%d"):
        # print("resetday---->>>>>")
        self.rebalance_portfolio()

def rebalance_portfolio(self):
    factor_vl = pd.Series()
    for data in self.datas:
        if not pd.isnull(data.close[0]) and data.industry[0] == self.p.selected_ind and not pd.isnull(data.factor[0]):
            factor_vl[data._name] = data.factor[0]
    factor_vl.sort_values(ascending=False, inplace=True)

    layer_num = int(len(factor_vl) / self.p.layer_N)
    layer_num = max(layer_num, self.p.min_num_stk)
    long_list = [i for i in factor_vl.index[:layer_num]]
    for o in long_list:
        self.cancel(o)
    if len(long_list)==0:
        return
    total_value = self.broker.getvalue()
    p_value = total_value * 0.8 / layer_num

    self.datas.sort(key=lambda d: self.broker.getvalue([d]), reverse=True)

    for d in self.datas:
        print(data._name, self.broker.getvalue([d]))

    for data in self.datas:
        if data._name in long_list:
            size = int(p_value / 100 / data.close[0]) * 100
            # print(self.datetime.date(0), self.broker.getvalue(), self.broker.getcash())
            # print("OHLC:", data.open[0], data.high[0], data.low[0], data.close[0])
            self.order_target_size(data=data, target=size)
        else:
            self.close(data=data, exectype=bt.Order.Close)