def input_csv_to_df(self, input_file, date_range):
csv_converter = CSVConverter(self.parser, self.logger)
# "TAO_T0N110W_D_ADCP.ascii" => "T0N110W"
column_str = input_file.filename.split("_")[1]
columns = self.columns(column_str)
csv_converter.input_csv_to_df(input_file, date_range, columns,
column_str)
self.pandas_tools.concat_df(csv_converter.pandas_tools.df)
def input_csv_to_df(self, input_file, date_range, plot_output_path):
csv_converter = CSVConverter(self.parser, self.logger)
# "0_0.csv" => "0_0"
column_str = input_file.filename.split(".")[0]
columns = [
column_str + '_' + column for column in ['GHI', 'DNI', 'DHI']
]
csv_converter.input_csv_to_df(input_file, date_range, columns)
df = csv_converter.pandas_tools.df.copy()
ParserSolarAnywhere.plot(plot_output_path, input_file.filename, df)
self.pandas_tools.concat_df(csv_converter.pandas_tools.df)
def input_csv_to_df(self, input_file, date_range):
csv_converter = CSVConverter(self.parser, self.logger)
# "TAO_T5N140W_D_SST_10min.ascii" => "T5N140W"
column = input_file.filename.split("_")[1]
csv_converter.input_csv_to_df(input_file, date_range, [column])
self.pandas_tools.concat_df(csv_converter.pandas_tools.df)