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directly read in nan values

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lisazeyen 2024-08-07 10:47:22 +02:00
parent 7848e08bc7
commit 7e75aab295
1 changed files with 2 additions and 3 deletions
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5
scripts/build_energy_totals.py
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@ -170,6 +170,7 @@ def eurostat_per_country(input_eurostat: str, country: str) -> pd.DataFrame:
sheet_name=None, sheet_name=None,
skiprows=4, skiprows=4,
index_col=list(range(4)), index_col=list(range(4)),
na_values=":"
) )
sheet.pop("Cover") sheet.pop("Cover")
return pd.concat(sheet) return pd.concat(sheet)
@ -502,7 +503,7 @@ def idees_per_country(ct: str, base_dir: str) -> pd.DataFrame:
assert df.index[11] == "International - Extra-EEAwUK" assert df.index[11] == "International - Extra-EEAwUK"
ct_totals["total international aviation freight"] = df.iloc[11].sum() ct_totals["total international aviation freight"] = df.iloc[11]
ct_totals["total domestic aviation"] = ( ct_totals["total domestic aviation"] = (
ct_totals["total domestic aviation freight"] ct_totals["total domestic aviation freight"]
@ -607,8 +608,6 @@ def fill_missing_years(fill_values: pd.Series) -> pd.Series:
- Zero values in the original Series are replaced by the ffilled and bfilled - Zero values in the original Series are replaced by the ffilled and bfilled
value of their respective country group. value of their respective country group.
""" """
# Replace zero values with NaN for correct filling
fill_values = fill_values.replace(0, pd.NA)
# Forward fill and then backward fill within each country group # Forward fill and then backward fill within each country group
fill_values = fill_values.groupby(level="country").ffill().bfill() fill_values = fill_values.groupby(level="country").ffill().bfill()