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@@ -140,7 +140,7 @@ class DataBase(object):
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NWP = cleaning(NWP, 'NWP')
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# NWP = self.split_time(NWP)
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NWP['C_TIME'] = NWP['C_TIME'].dt.strftime('%Y-%m-%d %H:%M:%S')
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- utils.saveData("NWP.csv", NWP)
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+ utils.savedata.saveData("NWP.csv", NWP)
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print("导出nwp数据")
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return NWP
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@@ -169,7 +169,7 @@ class DataBase(object):
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weather = self.exec_sql(weather_sql, engine)
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weather['C_TIME'] = pd.to_datetime(weather['C_TIME'])
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# weather = self.split_time(weather)
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- utils.saveData("/weather-{}.csv".format(i), weather)
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+ utils.savedata.saveData("/weather-{}.csv".format(i), weather)
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print("环境监测仪{}导出数据".format(i))
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def get_process_power(self):
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@@ -197,7 +197,7 @@ class DataBase(object):
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binary_map = {b'\x00': 0, b'\x01': 1}
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powers['C_IS_RATIONING_BY_AUTO_CONTROL'] = powers['C_IS_RATIONING_BY_AUTO_CONTROL'].map(binary_map)
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powers = rm_duplicated(powers)
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- utils.saveData("power.csv", powers)
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+ utils.savedata.saveData("power.csv", powers)
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def get_process_dq(self):
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"""
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@@ -215,7 +215,7 @@ class DataBase(object):
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# dq.drop('C_FORECAST_HOW_LONG_AGO', axis=1, inplace=True)
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dq = cleaning(dq, 'dq', cols=['C_FP_VALUE'])
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dq['C_TIME'] = dq['C_TIME'].dt.strftime('%Y-%m-%d %H:%M:%S')
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- utils.saveData("dq.csv", dq)
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+ utils.savedata.saveData("dq.csv", dq)
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print("导出dq数据")
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def get_process_cdq(self):
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@@ -233,7 +233,7 @@ class DataBase(object):
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cdq = cleaning(cdq, 'cdq', cols=['C_ABLE_VALUE'], dup=False)
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# cdq = cdq[cdq['C_FORECAST_HOW_LONG_AGO'] == int(str(self.opt.predict_point)[1:])]
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cdq['C_TIME'] = cdq['C_TIME'].dt.strftime('%Y-%m-%d %H:%M:%S')
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- utils.saveData("cdq.csv", cdq)
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+ utils.savedata.saveData("cdq.csv", cdq)
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def indep_process(self):
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"""
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@@ -244,7 +244,7 @@ class DataBase(object):
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for i in weatherloc:
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weather = readData("/weather-{}.csv".format(i))
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weather = cleaning(weather, 'weather', cols=['C_GLOBALR', 'C_DIRECTR', 'C_DIFFUSER', 'C_RH', 'C_AIRT', 'C_P', 'C_WS', 'C_WD'])
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- utils.saveData("/weather-{}-process.csv".format(i), weather)
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+ utils.savedata.saveData("/weather-{}-process.csv".format(i), weather)
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def data_process(self):
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"""
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liudawei