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Fix pandas 3.1 deprecation warnings in overview #341

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Fix pandas 3.1 deprecation warnings in overview #341

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24 changes: 16 additions & 8 deletions src/python/benchmark_models_petab/overview.py
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Original file line number Diff line number Diff line change
Expand Up @@ -177,14 +177,23 @@ def make_sbml4humans_urls(
]


def _fillna_str(df: pd.DataFrame, column: str, value: str) -> pd.DataFrame:
"""Fill missing values in a string column.

Columns without any values are read as float, which can't be filled with
strings.
"""
return df.astype({column: "string"}).fillna({column: value})


def get_noise_distributions(observable_df):
if petab.NOISE_DISTRIBUTION in observable_df.columns:
observable_df = observable_df.fillna(
value={petab.NOISE_DISTRIBUTION: petab.NORMAL}
observable_df = _fillna_str(
observable_df, petab.NOISE_DISTRIBUTION, petab.NORMAL
)
if petab.OBSERVABLE_TRANSFORMATION in observable_df.columns:
observable_df = observable_df.fillna(
value={petab.OBSERVABLE_TRANSFORMATION: petab.LIN}
observable_df = _fillna_str(
observable_df, petab.OBSERVABLE_TRANSFORMATION, petab.LIN
)
noise_distrs = [
tuple(e.values)
Expand All @@ -199,8 +208,8 @@ def get_noise_distributions(observable_df):

else:
if petab.OBSERVABLE_TRANSFORMATION in observable_df.columns:
observable_df = observable_df.fillna(
value={petab.OBSERVABLE_TRANSFORMATION: petab.LIN}
observable_df = _fillna_str(
observable_df, petab.OBSERVABLE_TRANSFORMATION, petab.LIN
)
noise_distrs = [
(e, petab.NORMAL)
Expand Down Expand Up @@ -337,8 +346,7 @@ def get_overview_df() -> pd.DataFrame:
summary = get_summary(petab_problem, petab_problem_id)
data.append(summary)
df = pd.DataFrame(data)
df.set_index([index_column], inplace=True)
return df
return df.set_index([index_column])


start_overview_table = "\n<!-- START OVERVIEW TABLE -->\n"
Expand Down
3 changes: 1 addition & 2 deletions src/python/benchmark_models_petab/overview_v2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,5 +160,4 @@ def get_overview_df() -> pd.DataFrame:
for petab_problem_id in v2.MODELS
]
df = pd.DataFrame(data, columns=list(columns))
df.set_index([index_column], inplace=True)
return df
return df.set_index([index_column])
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