def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(
original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# DateとTimeで分割されているので結合した項目を作る。
DataFrameFunction.generate_data_time_field(data_frame)
data_frame.set_index('date_time')
# 2,500みたいなデータがあるので取り除く。
data_frame['demand'] = data_frame['demand'].astype(str).str.replace(
',', '').astype(int)
data_frame['total_supply_capacity'] = data_frame[
'total_supply_capacity'].astype(str).str.replace(',',
'').astype(int)
# 後続で計算できないのでfloatに変換している。
data_frame['thermal'] = data_frame['thermal'].astype(str).str.replace(
',', '').astype(float)
# 他の電力に合わせて万kwからMWhに揃える。
DataFrameFunction.to_mwh(data_frame)
processed_pkl_path = FileFunction.get_processed_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(
original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# DateとTimeで分割されているので結合した項目を作る。
DataFrameFunction.generate_data_time_field(data_frame)
data_frame.set_index('date_time')
# TOTAL算出 Total Supply Capacity
data_frame[
'total_supply_capacity'] = DataFrameFunction.get_total_supply_capacity(
data_frame)
# 後続で計算できないのでfloatに変換している。
data_frame['solar_output_control'] = data_frame[
'solar_output_control'].astype(str).str.replace(',', '')
data_frame['solar_output_control'] = data_frame[
'solar_output_control'].astype(str).str.replace('−', '0')
data_frame['solar_output_control'] = data_frame[
'solar_output_control'].astype(float)
data_frame['wind_output_control'] = data_frame[
'wind_output_control'].astype(str).str.replace(',', '')
data_frame['wind_output_control'] = data_frame[
'wind_output_control'].astype(str).str.replace('−', '0')
data_frame['wind_output_control'] = data_frame[
'wind_output_control'].astype(float)
processed_pkl_path = FileFunction.get_processed_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(
original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# DateとTimeで分割されているので結合した項目を作る。
DataFrameFunction.generate_data_time_field(data_frame)
processed_pkl_path = FileFunction.get_processed_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# tohokuepcoは、日時で持っているのでTepcoに合わせて分割する。
DataFrameFunction.create_date_and_time_from_datetime(data_frame)
# Date型に変換しておく。
data_frame['date_time'] = pandas.to_datetime(data_frame['date_time'], format='%Y/%m/%d %H:%M')
# TOTAL算出 Total Supply Capacity
data_frame['total_supply_capacity'] = DataFrameFunction.get_total_supply_capacity(data_frame)
processed_pkl_path = FileFunction.get_processed_pkl_path(root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# DateとTimeで分割されているので結合した項目を作る。
DataFrameFunction.generate_data_time_field(data_frame)
data_frame.set_index('date_time')
# 沖縄にない電力項目は0で埋める。
data_frame['nuclear'] = 0
data_frame['geothermal'] = 0
data_frame['pumping'] = 0
data_frame['interconnection'] = 0
processed_pkl_path = FileFunction.get_processed_pkl_path(root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(
original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# DateとTimeで分割されているので結合した項目を作る。
DataFrameFunction.generate_data_time_field(data_frame)
data_frame.set_index('date_time')
# TOTAL算出 Total Supply Capacity
data_frame[
'total_supply_capacity'] = DataFrameFunction.get_total_supply_capacity(
data_frame)
processed_pkl_path = FileFunction.get_processed_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(
original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# DateとTimeで分割されているので結合した項目を作る。
DataFrameFunction.generate_data_time_field(data_frame)
data_frame.set_index('date_time')
# 後続で計算できないのでfloatに変換している。
# 地熱がハイフンなので0扱いにする。
data_frame['geothermal'] = data_frame['geothermal'].astype(
str).str.replace('－', '0').astype(float)
# 他の電力に合わせて万kwからMWhに揃える。
DataFrameFunction.to_mwh(data_frame)
processed_pkl_path = FileFunction.get_processed_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path
def __process_ex_data(cls, original_pkl_path, root_path, pkl_file_name):
data_frame = DataFrameFunction.get_data_frame_from_pkl(original_pkl_path)
data_frame['company'] = cls.COMPANY_NAME
# Kyudenは、日時で持っているのでTepcoに合わせて分割する。
DataFrameFunction.create_date_and_time_from_datetime(data_frame)
# 2,500みたいなデータがあるので取り除く。
data_frame['demand'] = data_frame['demand'].astype(str).str.replace(',', '').astype(float)
# 後続で計算できないのでfloatに変換している。
data_frame['nuclear'] = data_frame['nuclear'].astype(str).str.replace(',', '').astype(float)
data_frame['thermal'] = data_frame['thermal'].astype(str).str.replace(',', '').astype(float)
data_frame['solar_output_control'] = data_frame['solar_output_control'].astype(str).str.replace('None', '0')
data_frame['solar_output_control'] = data_frame['solar_output_control'].str.replace('nan', '0')
data_frame['solar_output_control'] = data_frame['solar_output_control'].str.replace(',', '')
data_frame['solar_output_control'] = data_frame['solar_output_control'].astype(float)
data_frame['pumping'] = data_frame['pumping'].astype(str).str.replace('None', '0')
data_frame['pumping'] = data_frame['pumping'].str.replace('nan', '0')
data_frame['pumping'] = data_frame['pumping'].str.replace(',', '')
data_frame['pumping'] = data_frame['pumping'].astype(float)
data_frame['interconnection'] = data_frame['interconnection'].astype(str).str.replace('None', '0')
data_frame['interconnection'] = data_frame['interconnection'].str.replace('nan', '0')
data_frame['interconnection'] = data_frame['interconnection'].str.replace(',', '')
data_frame['interconnection'] = data_frame['interconnection'].astype(float)
# Date型に変換しておく。
data_frame['date_time'] = pandas.to_datetime(data_frame['date_time'], format='%Y/%m/%d %H:%M')
# TOTAL算出 Total Supply Capacity
data_frame['total_supply_capacity'] = DataFrameFunction.get_total_supply_capacity(data_frame)
processed_pkl_path = FileFunction.get_processed_pkl_path(root_path, cls.COMPANY_NAME, pkl_file_name)
FileFunction.create_pkl_file(processed_pkl_path, data_frame)
return processed_pkl_path