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@@ -70,10 +70,10 @@ coords_terminologies = {
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}
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coords_defaults = {
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- "source": "Korea-GHG-Inventory",
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+ "source": "KOR-GHG-Inventory",
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"provenance": "measured",
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"area": "KOR",
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- "scenario": "Report_2020",
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+ "scenario": "BUR4",
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}
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coords_value_mapping = {
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@@ -111,7 +111,7 @@ df_all = None
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for sheet in sheets_to_read:
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# read current sheet (one sheet per gas)
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- df_current = pd.read_excel(inventory_file, sheet_name=sheet, skiprows=3, nrows=143, usecols=cols_to_read,
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+ df_current = pd.read_excel(input_folder / inventory_file, sheet_name=sheet, skiprows=3, nrows=143, usecols=cols_to_read,
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engine="openpyxl")
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# drop all rows where the index cols (category code and name) are both NaN
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# as without one of them there is no category information
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@@ -152,7 +152,7 @@ data_if = pm2.pm2io.convert_wide_dataframe_if(
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#filter_remove=filter_remove,
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#filter_keep=filter_keep,
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meta_data=meta_data,
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- convert_nan=True
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+ convert_str=True
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)
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filter_data(data_if, filter_remove=filter_remove)
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@@ -160,6 +160,8 @@ filter_data(data_if, filter_remove=filter_remove)
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# ###
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# save data to IF and native format
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# ###
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+if not output_folder.exists():
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+ output_folder.mkdir()
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pm2.pm2io.write_interchange_format(output_folder / (output_filename + coords_terminologies["category"]), data_if)
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data_pm2 = pm2.pm2io.from_interchange_format(data_if)
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