def __correct_ex_data(cls, root_path, pkl_file_name, url, reflesh):
original_pkl_path = FileFunction.get_original_pkl_path(root_path, cls.COMPANY_NAME, pkl_file_name)
if reflesh or not os.path.exists(original_pkl_path):
decoded_data = FileFunction.get_decoded_data(url)
data_frame = cls.__parse(decoded_data)
FileFunction.create_pkl_file(original_pkl_path, data_frame)
return original_pkl_path
def __correct_ex_data(cls, root_path, pkl_file_name, url, reflesh):
original_pkl_path = FileFunction.get_original_pkl_path(root_path, cls.COMPANY_NAME, pkl_file_name)
if reflesh or not os.path.exists(original_pkl_path):
decoded_data = FileFunction.get_decoded_data(url)
# 「2016/10/1 1:00」とか余計な半角が存在するデータがあるので加工する。
tohokuepco_csv = cls.__get_tohokuepco_csv(decoded_data)
data_frame = cls.__parse(tohokuepco_csv)
FileFunction.create_pkl_file(original_pkl_path, data_frame)
return original_pkl_path
def __correct_ex_data(cls, root_path, pkl_file_name, url, reflesh):
original_pkl_path = FileFunction.get_original_pkl_path(root_path, cls.COMPANY_NAME, pkl_file_name)
if reflesh or not os.path.exists(original_pkl_path):
decoded_data = FileFunction.get_decoded_data(url)
# okidenは、空行が入っていたりするので、csv読み込み前にデータ補正が必要。
okiden_csv = cls.__get_okiden_csv(decoded_data)
data_frame = cls.__parse(okiden_csv)
data_frame.reset_index()
data_frame.reset_index()
FileFunction.create_pkl_file(original_pkl_path, data_frame)
return original_pkl_path
def __correct_ex_data(cls, root_path, pkl_file_name, url, reflesh):
original_pkl_path = FileFunction.get_original_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
if reflesh or not os.path.exists(original_pkl_path):
decoded_data = FileFunction.get_decoded_data(url)
# 末尾に余計な「,」が入っていることがあるので除去する。
# スキップすべき行が違うこともあるので対応する。
rikuden_csv = cls.__get_rikuden_csv(decoded_data)
data_frame = cls.__parse(rikuden_csv)
data_frame.reset_index()
FileFunction.create_pkl_file(original_pkl_path, data_frame)
return original_pkl_path
def __correct_ex_data(cls, root_path, pkl_file_name, url, reflesh):
original_pkl_path = FileFunction.get_original_pkl_path(
root_path, cls.COMPANY_NAME, pkl_file_name)
if reflesh or not os.path.exists(original_pkl_path):
if '.xls' in url:
data_frame_from_xls = pandas.read_excel(url,
header=None,
index_col=None,
skiprows=[0, 1, 2, 3])
hepco_csv = cls.__create_hepco_csv_from_xls(
data_frame_from_xls.to_csv(index=False))
data_frame = cls.__parse_csv_from_xls(hepco_csv)
FileFunction.create_pkl_file(original_pkl_path, data_frame)
else:
decoded_data = FileFunction.get_decoded_data(url)
# hepcoは、日時周りのフォーマットが他と違うので、csv読み込み前にデータ補正が必要。
hepco_csv = cls.__get_hepco_csv(decoded_data)
data_frame = cls.__parse(hepco_csv)
FileFunction.create_pkl_file(original_pkl_path, data_frame)
return original_pkl_path