Skip to content

Pandas.Panel is deprecated since version 0.20.0 and removed #3

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Pandas.Panel is deprecated since version 0.20.0 and removed #3

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
18 changes: 9 additions & 9 deletions raw_data_fetch.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -155,8 +155,8 @@ def create_indicator_m_by_q(self, raw_data_dir, raw_data_field, indicator_name,
del dat['Unnamed: 0']
panel[d] = dat
print(d)
datpanel = pd.Panel(panel)
datpanel = datpanel.to_frame().stack().unstack(level=(0,1)) #貌似某些情况下会有BUG,有索引但是没数据
datpanel = pd.concat(panel, axis=0)
datpanel = datpanel.stack().unstack(level=(1, -1))
#开始计算结果指标(月频),在每个时间截面逐个处理每只股票
df = pd.DataFrame(index=all_stocks_info.index, columns=mdays)
for d in df.columns: #每月最后一天
Expand Down Expand Up @@ -191,6 +191,7 @@ def create_indicator_m_by_q_ex(self, raw_data_dir, raw_data_field, indicator_nam
del dat['Unnamed: 0']
panel[d] = dat
print(d)
# no access to wind, no way to test, thus not changed.
datpanel = pd.Panel(panel)
datpanel = datpanel.swapaxes(0, 1)
#开始计算结果指标(月频),在每个时间截面逐个处理每只股票
Expand Down Expand Up @@ -655,8 +656,8 @@ def create_month_tdays_begin_end(self, latest_month_end_tradeday=None):
''' 每月第一个和最后一个交易日映射
'''
tdays = self.tradedays
months_start = tdays[0:1] + list(after_d for before_d, after_d in zip(tdays[:-1], tdays[1:]) if before_d.month != after_d.month)
months_end = list(before_d for before_d, after_d in zip(tdays[:-1], tdays[1:]) if before_d.month != after_d.month) + tdays[-1:]
months_end = tdays[0:1] + list(after_d for before_d, after_d in zip(tdays[:-1], tdays[1:]) if before_d.month != after_d.month)
months_start = list(before_d for before_d, after_d in zip(tdays[:-1], tdays[1:]) if before_d.month != after_d.month) + tdays[-1:]
if latest_month_end_tradeday is None:
latest_month_end_tradeday = self.month_map.index[-1]
if months_end[-1] > latest_month_end_tradeday:
Expand Down Expand Up @@ -929,9 +930,8 @@ def create_pcf_ocf_ttm_m(self):
del dat['Unnamed: 0']
panel[d] = dat
print(d)
panel = pd.Panel(panel)
panel = panel.to_frame()
panel = panel.stack().unstack(level=(0,1))
panel = pd.concat(panel, axis=0)
panel = panel.stack().unstack(level=(1, -1))
#-------------------------------------------------------
#开始计算结果指标(月频)
df_result = pd.DataFrame(index=all_stocks_info.index, columns=new_caldays)
Expand Down Expand Up @@ -1001,8 +1001,8 @@ def create_profit_ttm_G_m(self):
del dat['Unnamed: 0']
panel[d] = dat
print(d)
panel = pd.Panel(panel)
panel = panel.to_frame()
panel = pd.concat(panel, axis=0)
panel = panel.stack().unstack(level=(1, -1))
'''
2009-03-31 2009-06-30 2009-09-30 2009-12-31 2010-03-31 2010-06-30 2010-09-30 2010-12-31 2011-03-31 2011-06-30 2011-09-30 2011-12-31 2012-03-31 2012-06-30 2012-09-30 2012-12-31 2013-03-31 2013-06-30 2013-09-30 2013-12-31 2014-03-31 2014-06-30 2014-09-30 2014-12-31 2015-03-31 2015-06-30 2015-09-30 2015-12-31 2016-03-31 2016-06-30 2016-09-30 2016-12-31 2017-03-31 2017-06-30 2017-09-30 2017-12-31 2018-03-31 2018-06-30 2018-09-30 2018-12-31 2019-03-31 2019-06-30 2019-09-30 2019-12-31
major minor
Expand Down
11 changes: 4 additions & 7 deletions single_factor_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -198,9 +198,7 @@ def test_yearly(factors=None, start_year=2012, end_year=2019):
df.to_csv(os.path.join(sf_test_save_path, save_name+'.csv'), encoding='gbk')

#存储检验结果表格
test_result = pd.Panel(test_result)
test_result = test_result.swapaxes(2, 0)
test_result = test_result.swapaxes(1, 2)
test_result = pd.concat(test_result)
test_result.to_excel(os.path.join(sf_test_save_path, 'T检验&IC检验结果.xlsx'), encoding='gbk')

#绘制单因子检验图，并进行存储
Expand Down Expand Up @@ -676,8 +674,8 @@ def get_stock_weight(self, equal_weight=True):
dates = self.factor_data.columns
stk_weights = [self.get_stock_weight_by_group(self.factor_data[date], equal_weight) for date in dates]
result = {date: stk_weight for date, stk_weight in zip(dates, stk_weights)}
result = pd.Panel.from_dict(result)
result = [result.minor_xs(group) for group in result.minor_axis]
result = pd.concat(result)
result = [result[col].unstack(level=0) for col in result.columns]
return result

def get_stock_weight_by_group(self, factor, equal_weight=False):
Expand Down Expand Up @@ -749,8 +747,7 @@ def panel_to_matrix(factors, factor_path=factor_path, save_path=sf_test_save_pat
date = pd.to_datetime(f.split('.')[0])
datpanel[date] = datdf[factors]

datpanel = pd.Panel(datpanel)
datpanel = datpanel.swapaxes(0, 2)
datpanel = pd.concat(datpanel)
for factor in datpanel.items:
dat = datpanel.loc[factor]
save_name = factor.replace('/', '_div_') if '/' in factor else factor
Expand Down